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eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/omni/isaac/shapenet/shapenet/menu.py | # Copyright (c) 2018-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import omni.ui as ui
from omni.kit.menu.utils import add_menu_items, remove_menu_items, MenuItemDescription
import weakref
from .settings import ShapenetSettings
from .globals import *
EXTENSION_NAME = "ShapeNet Loader"
HELP_TEXT = (
" This omni.isaac.shapenet plugin allows you to add ShapeNetCore.V2 models from shapenet.org to your stage in Omniverse Kit.\n\n"
" You can use the ShapeNet menu to add shapes.\n\n"
" If should already have ShapeNetCore V2 installed locally, this plugin will use the local files. Use the env var SHAPENET_LOCAL_DIR to set that location (IMPORTANT NOTE: Make sure there are no periods, ., in the path name), otherwise, omni.isaac.shapenet will use the default ${data}/shapenet folder. By using local folders, you can edit shapenet models before their conversion to usd. If you want to keep the original file, just save the modified file as "
' "models/modified/model.obj" in that shape\'s /models folder.\n\n'
" If the shape is already on the omniverse server at g_omni_shape_loc (defaults to /Projects/shapenet), then that model will be used instead of the locally saved or modified shapenet obj file.\n\n"
)
class ShapenetMenu:
def __init__(self):
self._window = None
self._settings_ui = None
self._models = {}
self._menu_items = [
MenuItemDescription(name=EXTENSION_NAME, onclick_fn=lambda a=weakref.proxy(self): a._create_window())
]
add_menu_items(self._menu_items, "Isaac Utils")
# self._create_window() # comment this out to prevent window from being visible until menu is clicked
def _create_window(self):
if self._window == None:
""" build ShapeNet window"""
self._window = ui.Window(
title="ShapeNet Loader",
width=400,
height=150,
visible=True,
dockPreference=ui.DockPreference.LEFT_BOTTOM,
)
self._window.deferred_dock_in("Console", ui.DockPolicy.DO_NOTHING)
with self._window.frame:
with ui.VStack():
with ui.HStack(height=20):
self._models["add_button"] = ui.Button(
"Add A Model", width=0, clicked_fn=lambda b=None: self._settings_ui._on_add_model_fn()
)
ui.Spacer()
self._models["help_button"] = ui.Button(
"Help", width=0, clicked_fn=lambda b=None: self._on_help_menu_click()
)
with ui.HStack(height=20):
self._create_settings_ui()
# TODO need this? self._models["add_button"].visible = True
self._window.visible = True
def _create_settings_ui(self):
self._settings_ui = ShapenetSettings()
def _on_help_menu_click(self):
help_message = HELP_TEXT
flags = ui.WINDOW_FLAGS_NO_RESIZE | ui.WINDOW_FLAGS_MODAL
flags |= ui.WINDOW_FLAGS_NO_SCROLLBAR
self._help_window = ui.Window("Shapenet Help", width=500, height=0, flags=flags)
with self._help_window.frame:
with ui.VStack(name="root", style={"VStack::root": {"margin": 10}}, height=0, spacing=20):
ui.Label(help_message, alignment=ui.Alignment.LEFT, word_wrap=True)
def shutdown(self):
remove_menu_items(self._menu_items, "Isaac Utils")
self._menu_items = None
self._settings_ui = None
| 3,975 | Python | 46.333333 | 468 | 0.630189 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/omni/isaac/shapenet/shapenet/global_constants.py | # Copyright (c) 2018-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
g_default_omni_server = "localhost"
g_omni_shape_loc = "/Projects/shapenet"
g_root_usd_namespace_path = "/shapenet"
g_pickle_file_name = "/shapenet_db2.pickle.bz2"
| 598 | Python | 41.785711 | 76 | 0.785953 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/omni/isaac/shapenet/shapenet/shape.py | # Copyright (c) 2018-2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import omni.client
import omni.kit
import omni.usd
import asyncio
import os
from pxr import UsdGeom, Gf, Tf
import requests
import urllib.request
import shutil
import sys
from .globals import *
# parse the text of a web pate and get the <a href="LINKS">Links</a>
def get_links(html):
# Find the reference to <a href="
found = html.find('<a href="')
links = []
while found > -1:
q_loc = html.find('"', found + 9)
links.append(html[found + 9 : q_loc])
found = html.find('<a href="', found + 1)
return links
def download_file(local_filename, url):
with urllib.request.urlopen(url) as response:
with open(local_filename, "wb") as f:
f.write(response.read())
# download all the files at url, which should be a director
# to the local folder
def download_folder(local_folder, url):
if not os.path.exists(local_folder):
os.makedirs(local_folder)
for href in get_links(requests.get(url).text):
if not href[0] == "?":
# not a reference to Name, Last Modified, Size, or Description
if not href[0] == "/":
# not the parent directory
if href[-1] == "/":
# sub directory, add all files in it.
download_folder(local_folder + href, url + href)
else:
print(f"--Downloading {url+href} to {local_folder + href}.")
download_file(local_folder + href, url + href)
def file_exists_on_omni(file_path):
result, _ = omni.client.stat(file_path)
if result == omni.client.Result.OK:
return True
return False
async def create_folder_on_omni(folder_path):
if not file_exists_on_omni(folder_path):
result = await omni.client.create_folder_async(folder_path)
return result == omni.client.Result.OK
async def convert(in_file, out_file):
# This import causes conflicts when global?
import omni.kit.asset_converter as assetimport
# Folders must be created first through usd_ext of omni won't be able to create the files creted in them in the current session.
out_folder = out_file[0 : out_file.rfind("/") + 1]
# only call create_folder_on_omni if it's connected to an omni server
if out_file.startswith("omniverse://"):
await create_folder_on_omni(out_folder + "materials")
def progress_callback(progress, total_steps):
pass
converter_context = omni.kit.asset_converter.AssetConverterContext()
# setup converter and flags
converter_context.as_shapenet = True
converter_context.single_mesh = True
converter_context.merge_all_meshes = True
converter_context.keep_all_materials = True
converter_context.embed_textures = True
instance = omni.kit.asset_converter.get_instance()
task = instance.create_converter_task(in_file, out_file, progress_callback, converter_context)
success = await task.wait_until_finished()
return success
# This is the main entry point for any function that wants to add a shape to the scene.
# Care must be taken when running this on a seperate thread from the main thread because
# it calls c++ modules from python which hold the GIL.
def addShapePrim(
omniverseServer, synsetId, modelId, pos, rot, scale, auto_add_physics, use_convex_decomp, do_not_place=False
):
# use shapenet v2 for models
shape_url = g_shapenet_url + "2/" + synsetId + "/" + modelId + "/"
# Get the local file system path and the omni server path
local_folder = get_local_shape_loc() + "/" + synsetId + "/" + modelId + "/"
local_path = local_folder + "models/model_normalized.obj"
local_modified_path = local_folder + "models/modified/model.obj"
global g_omni_shape_loc
omni_shape_loc = "omniverse://" + omniverseServer + g_omni_shape_loc
(result, entry) = asyncio.new_event_loop().run_until_complete(omni.client.stat_async(omni_shape_loc))
if not result == omni.client.Result.OK:
print("Saving converted files locally since omniverse server is not connected")
omni_shape_loc = get_local_shape_loc() + "/local-converted-USDs"
omni_path = (
omni_shape_loc + "/n" + synsetId + "/i" + modelId + "/"
) # don't forget to add the name at the end and .usd
omni_modified_path = omni_shape_loc + "/n" + synsetId + "/i" + modelId + "/modified/"
stage = omni.usd.get_context().get_stage()
if not stage:
return "ERROR Could not get the stage."
# Get the name of the shapenet object reference in the stage if it exists
# (i.e. it has been added already and is used in another location on the stage).
synsetID_path = g_root_usd_namespace_path + "/n" + synsetId
over_path = synsetID_path + "/i" + modelId
# Get the name of the instance we will add with the transform, this is the actual visible prim
# instance of the reference to the omniverse file which was converted to local disk after
global g_shapenet_db
g_shapenet_db = get_database()
if g_shapenet_db == None:
shape_name = ""
print("Please create an Shapenet ID Database with the menu.")
else:
shape_name = Tf.MakeValidIdentifier(g_shapenet_db[synsetId][modelId][4])
if shape_name == "":
shape_name = "empty_shape_name"
prim_path = str(stage.GetDefaultPrim().GetPath()) + "/" + shape_name
prim_path_len = len(prim_path)
shape_name_len = len(shape_name)
# if there is only one instance, we don't add a _# postfix, but if there is multiple, then the second instance
# starts with a _1 postfix, and further additions increase that number.
insta_count = 0
while stage.GetPrimAtPath(prim_path):
insta_count += 1
prim_path = f"{prim_path[:prim_path_len]}_{insta_count}"
shape_name = f"{shape_name[:shape_name_len]}_{insta_count}"
omni_path = omni_path + shape_name + ".usd"
omni_modified_path = omni_modified_path + shape_name + ".usd"
# If the prim refernce to the omnivers file is not already on
# the stage the stage we will need to add it.
place_later = False
if not stage.GetPrimAtPath(over_path):
print(f"-Shapenet is adding {shape_name} to the stage for the first time.")
# If the files does not already exist in omniverse we will have to add it there
# with our automatic conversion of the original shapenet file.
# We need to check if the modified file is on disk, so if it's not on the omni server it will
# be added there even if the non modified one already exists on omni.
if os.path.exists(local_modified_path) or file_exists_on_omni(omni_modified_path):
omni_path = omni_modified_path
if not file_exists_on_omni(omni_path):
# If the original omniverse file does not exist locally, we will have to pull
# it from Stanford's shapenet database on the web.
if os.path.exists(local_modified_path):
local_path = local_modified_path
omni_path = omni_modified_path
if not os.path.exists(local_path):
# Pull the shapenet files to the local drive for conversion to omni:usd
print(f"--Downloading {local_folder} from {shape_url}.")
download_folder(local_folder, shape_url)
# Add The file to omniverse here, if you add them asyncronously, then you have to do the
# rest of the scene adding later.
print(f"---Converting {shape_name}...")
status = asyncio.get_event_loop().run_until_complete(convert(local_path, omni_path))
if not status:
return f"ERROR OmniConverterStatus is {status}"
print(f"---Added to Omniverse as {omni_path}.")
# Add the over reference of the omni file to the stage here.
print(f"----Adding over of {over_path} to stage.")
if not do_not_place and not place_later:
over = stage.OverridePrim(over_path)
over.GetReferences().AddReference(omni_path)
# Add the instance of the shape here.
if not do_not_place and not place_later:
prim = stage.DefinePrim(prim_path, "Xform")
prim.GetReferences().AddInternalReference(over_path)
metersPerUnit = UsdGeom.GetStageMetersPerUnit(stage)
scaled_scale = scale / metersPerUnit
addobject_fn(prim.GetPath(), pos, rot, scaled_scale)
# add physics
if auto_add_physics:
from omni.physx.scripts import utils
print("Adding PHYSICS to ShapeNet model")
shape_approximation = "convexHull"
if use_convex_decomp:
shape_approximation = "convexDecomposition"
utils.setRigidBody(prim, shape_approximation, False)
return prim
return None
def get_min_max_vert(obj_file_name):
min_x = min_y = min_z = sys.float_info.max
max_x = max_y = max_z = -sys.float_info.max
with open(obj_file_name, "r") as fi:
for ln in fi:
if ln.startswith("v "):
vx = float(ln[2:].partition(" ")[0])
vy = float(ln[2:].partition(" ")[2].partition(" ")[0])
vz = float(ln[2:].partition(" ")[2].partition(" ")[2])
min_x = min(min_x, vx)
min_y = min(min_y, vy)
min_z = min(min_z, vz)
max_x = max(max_x, vx)
max_y = max(max_y, vy)
max_z = max(max_z, vz)
return Gf.Vec3f(min_x, min_y, min_z), Gf.Vec3f(max_x, max_y, max_z)
# Got this From Lou Rohan... Thanks Lou!
# objectpath - path in omniverse - omni:/Projects/Siggraph2019/AtticWorkflow/Props/table_cloth/table_cloth.usd
# objectname - name you want it to be called in the stage
# xform - Gf.Matrix4d
def addobject_fn(path, position, rotation, scale):
# The original model was translated by the centroid, and scaled to be normalized by the length of the
# hypotenuse of the bbox
translate_mtx = Gf.Matrix4d()
rotate_mtx = Gf.Matrix4d()
scale_mtx = Gf.Matrix4d()
translate_mtx.SetTranslate(position) # centroid/metersPerUnit)
rotate_mtx.SetRotate(rotation)
scale_mtx = scale_mtx.SetScale(scale)
transform_matrix = scale_mtx * rotate_mtx * translate_mtx
omni.kit.commands.execute("TransformPrimCommand", path=path, new_transform_matrix=transform_matrix)
| 10,818 | Python | 40.934108 | 132 | 0.646885 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/omni/isaac/shapenet/shapenet/settings.py | # Copyright (c) 2018-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import carb
from omni.kit.widget.settings import create_setting_widget, SettingType
import omni.ui as ui
from pxr import Gf
from .globals import *
from .shape import addShapePrim
from .globals import g_default_omni_server
class ShapenetSettings:
def __init__(self):
self._settings = carb.settings.get_settings()
# note: Not sure this is the best place to set default values.
self._settings.set_default_string("/isaac/shapenet/omniverseServer", g_default_omni_server)
self._settings.set_default_string("/isaac/shapenet/synsetId", "random")
self._settings.set_default_string("/isaac/shapenet/modelId", "random")
self._settings.set_float_array("/isaac/shapenet/pos", [0.0, 0.0, 0.0])
self._settings.set_float_array("/isaac/shapenet/rotaxis", [0.0, 0.0, 0.0])
self._settings.set_default_float("/isaac/shapenet/rotangle", 0.0)
self._settings.set_default_float("/isaac/shapenet/scale", 1.0)
self._settings.set_default_bool("/isaac/shapenet/auto_add_physics", False)
self._settings.set_default_bool("/isaac/shapenet/use_convex_decomp", False)
self._build_ui()
def _build_ui(self):
""" Add Shape Settings """
with ui.CollapsableFrame(title="Add Model Parameters"):
with ui.VStack(spacing=2):
with ui.HStack(height=20):
ui.Label("Omniverse Server", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/omniverseServer", SettingType.STRING)
with ui.HStack(height=20):
ui.Label("synsetId and modelId", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/synsetId", SettingType.STRING)
ui.Spacer()
create_setting_widget("/isaac/shapenet/modelId", SettingType.STRING)
with ui.HStack(height=20):
ui.Label("X Y Z Position", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/pos", SettingType.DOUBLE3)
with ui.HStack(height=20):
ui.Label("X Y Z Axis Angle", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/rotaxis", SettingType.DOUBLE3)
ui.Spacer()
create_setting_widget("/isaac/shapenet/rotangle", SettingType.FLOAT)
with ui.HStack(height=20):
ui.Label("Scale of add", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/scale", SettingType.FLOAT)
with ui.HStack(height=20):
ui.Label("Automatically add physics", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/auto_add_physics", SettingType.BOOL)
with ui.HStack(height=20):
ui.Label("Use convex decomponsition", word_wrap=True, width=ui.Percent(35))
create_setting_widget("/isaac/shapenet/use_convex_decomp", SettingType.BOOL)
def _on_add_model_fn(self):
pos = self.getPos()
rot = self.getRot()
scale = self.getScale()
global g_shapenet_db
g_shapenet_db = get_database()
if g_shapenet_db == None:
print(
"Please create an Shapenet ID by logging into shapenet.org with the UI, or by downloading it manually and setting the SHAPENET_LOCAL_DIR environment variable."
)
return
synsetId = self.getSynsetId()
modelId = self.getModelId()
return addShapePrim(
self._settings.get("/isaac/shapenet/omniverseServer"),
synsetId,
modelId,
pos,
rot,
scale,
self._settings.get("/isaac/shapenet/auto_add_physics"),
self._settings.get("/isaac/shapenet/use_convex_decomp"),
)
def getPos(self):
pos = self._settings.get("/isaac/shapenet/pos")
return Gf.Vec3d(pos[0], pos[1], pos[2])
def getRot(self):
axis = self._settings.get("/isaac/shapenet/rotaxis")
a = self._settings.get("/isaac/shapenet/rotangle")
return Gf.Rotation(Gf.Vec3d(axis[0], axis[1], axis[2]), a)
def getScale(self):
s = self._settings.get("/isaac/shapenet/scale")
return s
def getSynsetId(self):
s = self._settings.get("/isaac/shapenet/synsetId")
return s
def getModelId(self):
s = self._settings.get("/isaac/shapenet/modelId")
return s
| 5,073 | Python | 43.902654 | 175 | 0.617189 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/docs/CHANGELOG.md | # Changelog
## [2.0.1] - 2023-01-06
### Fixed
- onclick_fn warning when creating UI
## [2.0.0] - 2022-07-29
### Removed
- web access to models
- http server for receiving external commands
## [1.0.2] - 2022-05-24
### Fixed
- Make webserver thread a daemon so it does not block fast exit
## [1.0.1] - 2022-01-07
### Changed
- Add defaults to http commands
- clearer message when shapenet.org login fails
- allow random ids to work outside the ui
### Fixed
- jupyter_notebook.sh can now take file names with spaces in them
## [1.0.0] - 2021-08-13
### Added
- Initial version of Isaac Sim ShapeNet Extension
| 615 | Markdown | 18.249999 | 65 | 0.686179 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/docs/README.md | # Usage
To enable this extension, go to the Extension Manager menu and enable omni.isaac.shapenet extension.
| 111 | Markdown | 21.399996 | 100 | 0.792793 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.shapenet/docs/index.rst | ShapeNet [omni.isaac.shapenet]
################################################################
.. automodule:: omni.isaac.shapenet.utils
:members:
:undoc-members:
:exclude-members: get_local_shape_loc, convert
:no-show-inheritance:
| 250 | reStructuredText | 26.888886 | 64 | 0.52 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/PACKAGE-LICENSES/omni.isaac.synthetic_recorder-LICENSE.md | Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
NVIDIA CORPORATION and its licensors retain all intellectual property
and proprietary rights in and to this software, related documentation
and any modifications thereto. Any use, reproduction, disclosure or
distribution of this software and related documentation without an express
license agreement from NVIDIA CORPORATION is strictly prohibited. | 412 | Markdown | 57.999992 | 74 | 0.839806 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/config/extension.toml | [core]
reloadable = true
order = 0
[package]
version = "1.5.0"
title = "Isaac Sim Synthetic Data Recorder"
description = "Tool to record synthetic data"
authors = ["NVIDIA"]
repository = ""
keywords = ["isaac", "synthetic", "recorder"]
changelog = "docs/CHANGELOG.md"
category = "Simulation"
readme = "docs/README.md"
icon = "data/icon.png"
writeTarget.kit = true
[dependencies]
"omni.replicator.core" = {}
"omni.timeline" = {}
"omni.kit.viewport.utility" = {}
"omni.kit.window.extensions" = {}
[[python.module]]
name = "omni.isaac.synthetic_recorder"
| 555 | TOML | 20.384615 | 45 | 0.695495 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/omni/isaac/synthetic_recorder/__init__.py | # Copyright (c) 2018-2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
from .synthetic_recorder_extension import *
| 478 | Python | 42.545451 | 76 | 0.807531 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/omni/isaac/synthetic_recorder/synthetic_recorder_extension.py | # Copyright (c) 2018-2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import os
import gc
import time
import asyncio
import json
import carb
import carb.events
import omni.kit.ui
import omni.ui as ui
import omni.replicator.core as rep
import omni.timeline
from omni.kit.viewport.utility import get_active_viewport
from omni.kit.window.extensions.utils import open_file_using_os_default
from omni.replicator.core import orchestrator
from pxr import Semantics
from functools import lru_cache
from enum import Enum
PARAM_TOOLTIPS = {
"rgb": "Produces an array of type np.uint8 with shape (width, height, 4), where the four channels correspond to R,G,B,A.",
"bounding_box_2d_tight": "Outputs tight 2d bounding box of each entity with semantics in the camera's viewport.\nTight bounding boxes bound only the visible pixels of entities.\nCompletely occluded entities are ommited.\nBounds only visible pixels.",
"bounding_box_2d_loose": "Outputs loose 2d bounding box of each entity with semantics in the camera's field of view.\nLoose bounding boxes bound the entire entity regardless of occlusions.\nWill produce the loose 2d bounding box of any prim in the viewport, no matter if is partially occluded or fully occluded.",
"semantic_segmentation": "Outputs semantic segmentation of each entity in the camera's viewport that has semantic labels.\nIf colorize is set to True (mapping from color to semantic labels), the image will be a 2d array of types np.uint8 with 4 channels.\nIf colorize is set to False (mapping from semantic id to semantic labels), the image will be a 2d array of types np.uint32 with 1 channel, which is the semantic id of the entities.",
"colorize_semantic_segmentation": "If True, semantic segmentation is converted to an image where semantic ids are mapped to colors and saved as a uint8 4 channel PNG image.\nIf False, the output is saved as a uint32 PNG image.",
"instance_id_segmentation": "Outputs instance id segmentation of each entity in the camera's viewport.\nThe instance id is unique for each prim in the scene with different paths.\nIf colorize is set to True (mapping from color to usd prim path of that entity), the image will be a 2d array of types np.uint8 with 4 channels.\nIf colorize is set to False (mapping from instance id to usd prim path of that entity), the image will be a 2d array of types np.uint32 with 1 channel, which is the instance id of the entities.",
"colorize_instance_id_segmentation": "If True, instance id segmentation is converted to an image where instance ids are mapped to colors and saved as a uint8 4 channel PNG image.\nIf False, the output is saved as a uint32 PNG image.",
"instance_segmentation": "Outputs instance segmentation of each entity in the camera' viewport.\nThe main difference between instance id segmentation and instance segmentation are that instance segmentation annotator goes down the hierarchy to the lowest level prim which has semantic labels,\n whereas instance id segmentation always goes down to the leaf prim.\nIf colorize is set to True (mapping from color to usd prim path of that semantic entity), the image will be a 2d array of types np.uint8 with 4 channels.\nIf colorize is set to False (mapping from instance id to usd prim path of that semantic entity), the image will be a 2d array of types np.uint32 with 1 channel, which is the instance id of the semantic entities.",
"colorize_instance_segmentation": "If True, instance segmentation is converted to an image where instance are mapped to colors and saved as a uint8 4 channel PNG image.\nIf False, the output is saved as a uint32 PNG image.",
"distance_to_camera": "Outputs a depth map from objects to camera positions.\nProduces a 2d array of types np.float32 with 1 channel.",
"distance_to_image_plane": "Outputs a depth map from objects to image plane of the camera.\nProduces a 2d array of types np.float32 with 1 channel.",
"bounding_box_3d": "Outputs 3D bounding box of each entity with semantics in the camera's viewport, generated regardless of occlusion.",
"occlusion": "Outputs the occlusion of each entity in the camera's viewport.\nContains the instanceId, semanticId and the occlusionRatio.",
"normals": "Produces an array of type np.float32 with shape (height, width, 4).\nThe first three channels correspond to (x, y, z).\nThe fourth channel is unused.",
"motion_vectors": "Outputs a 2D array of motion vectors representing the relative motion of a pixel in the camera's viewport between frames.\nProduces a 2darray of types np.float32 with 4 channels.\nEach value is a normalized direction in 3D space.\nThe values represent motion relative to camera space.",
"camera_params": "Outputs the camera model (pinhole or fisheye models), view matrix, projection matrix, fisheye nominal width/height, fisheye optical centre, fisheye maximum field of view, fisheye polynomial, near/far clipping range.",
"pointcloud": "Outputs a 2D array of shape (N, 3) representing the points sampled on the surface of the prims in the viewport, where N is the number of point.\nPoint positions are in the world space.\nSample resolution is determined by the resolution of the render product.\nTo get the mapping from semantic id to semantic labels, pointcloud annotator is better used with semantic segmentation annotator, and users can extract the idToLabels data from the semantic segmentation annotator.",
"pointcloud_include_unlabelled": "If True, pointcloud annotator will capture any prim in the camera's perspective, not matter if it has semantics or not.\nIf False, only prims with semantics will be captured.",
"skeleton_data": "Retrieves skeleton data given skeleton prims and camera parameters",
"s3_bucket": "The S3 Bucket name to write to. If not provided, disk backend will be used instead.\nThis backend requires that AWS credentials are set up in ~/.aws/credentials.",
"s3_region": "If provided, this is the region the S3 bucket will be set to. Default: us-east-1",
"s3_endpoint": "Gateway endpoint for Amazon S3",
}
MAX_RESOLUTION = (7680, 4320) # 8K
WINDOW_NAME = "Synthetic Data Recorder"
MENU_PATH = f"Replicator/{WINDOW_NAME}"
class OutWriteType(Enum):
OVERWRITE = 0
INCREMENT = 1
TIMESTAMP = 2
@lru_cache()
def _ui_get_delete_glyph():
return omni.ui.get_custom_glyph_code("${glyphs}/menu_delete.svg")
@lru_cache()
def _ui_get_open_folder_glyph():
return omni.ui.get_custom_glyph_code("${glyphs}/folder_open.svg")
@lru_cache()
def _ui_get_reset_glyph():
return omni.ui.get_custom_glyph_code("${glyphs}/menu_refresh.svg")
class SyntheticRecorderExtension(omni.ext.IExt):
def on_startup(self, ext_id: str):
"""Caled to load the extension"""
self._ext_id = ext_id
self._window = ui.Window(WINDOW_NAME, dockPreference=ui.DockPreference.RIGHT_BOTTOM, visible=True)
self._window.deferred_dock_in("Property", omni.ui.DockPolicy.DO_NOTHING)
editor_menu = omni.kit.ui.get_editor_menu()
if editor_menu:
self._menu = editor_menu.add_item(MENU_PATH, self._menu_callback, toggle=True, value=True)
self._window.set_visibility_changed_fn(self._visibility_changed_fn)
self._writer_name = "BasicWriter"
self._custom_writer_name = "MyCustomWriter"
self._writer = None
self._num_frames = 0
self._rt_subframes = 0
self._control_timeline = False
self._orchestrator_status = rep.orchestrator.get_status()
self._in_running_state = False
# Orchestrator status update callback
self._orchestrator_status_cb = rep.orchestrator.register_status_callback(self._on_orchestrator_status_changed)
# Stage event callback
self._sub_stage_event = (
omni.usd.get_context()
.get_stage_event_stream()
.create_subscription_to_pop_by_type(int(omni.usd.StageEventType.CLOSING), self._on_stage_closing_event)
)
# Editor quit callback
self._sub_shutdown = (
omni.kit.app.get_app()
.get_shutdown_event_stream()
.create_subscription_to_pop_by_type(
omni.kit.app.POST_QUIT_EVENT_TYPE,
self._on_editor_quit_event,
name="omni.isaac.synthetic_recorder::shutdown_callback",
order=0,
)
)
self._config_dir = os.path.abspath(
os.path.join(omni.kit.app.get_app().get_extension_manager().get_extension_path(self._ext_id), "data", "")
)
self._last_config_path = os.path.join(self._config_dir, "last_config.json")
self._custom_params_path = ""
self._config_file = "custom_config.json"
self._out_working_dir = os.getcwd() + "/"
self._out_dir = "_out_sdrec"
self._out_write_type = OutWriteType.OVERWRITE
self._use_s3 = False
self._s3_params = {"s3_bucket": "", "s3_region": "", "s3_endpoint": ""}
self._basic_writer_params = {
"rgb": True,
"bounding_box_2d_tight": False,
"bounding_box_2d_loose": False,
"semantic_segmentation": False,
"colorize_semantic_segmentation": False,
"instance_id_segmentation": False,
"colorize_instance_id_segmentation": False,
"instance_segmentation": False,
"colorize_instance_segmentation": False,
"distance_to_camera": False,
"distance_to_image_plane": False,
"bounding_box_3d": False,
"occlusion": False,
"normals": False,
"motion_vectors": False,
"camera_params": False,
"pointcloud": False,
"pointcloud_include_unlabelled": False,
"skeleton_data": False,
}
self._render_products = []
self._rp_data = [["/OmniverseKit_Persp", 512, 512]]
# UI - frames collapsed state
self._writer_frame_collapsed = False
self._writer_params_frame_collapsed = True
self._rp_frame_collapsed = False
self._output_frame_collapsed = False
self._s3_params_frame_collapsed = True
self._config_frame_collapsed = True
self._control_frame_collapsed = False
self._control_params_frame_collapsed = False
# UI - Buttons
self._start_stop_button = None
self._pause_resume_button = None
# Load latest or default config values
if os.path.isfile(self._last_config_path):
self.load_config(self._last_config_path)
else:
self.load_config(os.path.join(self._config_dir, "default_config.json"))
# Build the window ui
self._build_window_ui()
def _menu_callback(self, menu, value):
self._window.visible = not self._window.visible
def _visibility_changed_fn(self, visible):
omni.kit.ui.get_editor_menu().set_value(MENU_PATH, visible)
def _on_orchestrator_status_changed(self, status):
new_status = status is not self._orchestrator_status
if new_status:
self._orchestrator_status = status
# Check if the recorder was running and it stopped because it reached the number of requested frames
has_finished_recording = self._in_running_state and status is rep.orchestrator.Status.STOPPED
if has_finished_recording:
asyncio.ensure_future(self._on_orchestrator_finish_async())
def _on_stage_closing_event(self, e: carb.events.IEvent):
self._disable_all_buttons()
if self._orchestrator_status is not orchestrator.Status.STOPPED:
rep.orchestrator.stop()
self._clear_recorder()
self._enable_buttons(case="reset")
def _on_editor_quit_event(self, e: carb.events.IEvent):
# Fast shutdown of the extension, stop recorder save config files
if self._orchestrator_status is not orchestrator.Status.STOPPED:
rep.orchestrator.stop()
self._clear_recorder()
self.save_config(self._last_config_path)
def on_shutdown(self):
# Clean shutdown of the extension, called when the extension is unloaded (not called when the editor is closed)
if self._orchestrator_status is not orchestrator.Status.STOPPED:
rep.orchestrator.stop()
self._clear_recorder()
self._orchestrator_status_cb.unregister()
self.save_config(self._last_config_path)
editor_menu = omni.kit.ui.get_editor_menu()
if editor_menu:
self._menu = editor_menu.remove_item(MENU_PATH)
self._menu = None
self._window = None
gc.collect()
def _open_dir(self, path):
if not os.path.isdir(path):
carb.log_warn(f"Could not open directory {path}.")
return
open_file_using_os_default(path)
def load_config(self, path):
if not os.path.isfile(path):
carb.log_warn(f"Could not find config file {path}.")
return
with open(path, "r") as f:
config = json.load(f)
if "writer_name" in config and config["writer_name"]:
self._writer_name = config["writer_name"]
if "custom_writer_name" in config and config["custom_writer_name"]:
self._custom_writer_name = config["custom_writer_name"]
if "num_frames" in config:
self._num_frames = config["num_frames"]
if "rt_subframes" in config:
self._rt_subframes = config["rt_subframes"]
if "control_timeline" in config:
self._control_timeline = config["control_timeline"]
if "config_file" in config and config["config_file"]:
self._config_file = config["config_file"]
if "custom_params_path" in config and config["custom_params_path"]:
self._custom_params_path = config["custom_params_path"]
if "out_working_dir" in config and config["out_working_dir"]:
self._out_working_dir = config["out_working_dir"]
if "out_dir" in config and config["out_dir"]:
self._out_dir = config["out_dir"]
if "out_write_type" in config:
self._out_write_type = OutWriteType[config["out_write_type"]]
if "use_s3" in config:
self._use_s3 = config["use_s3"]
if "s3_params" in config:
self._s3_params = config["s3_params"]
if "basic_writer_params" in config and isinstance(config["basic_writer_params"], dict):
for key, value in config["basic_writer_params"].items():
if key in self._basic_writer_params:
self._basic_writer_params[key] = value
if "rp_data" in config:
self._rp_data = config["rp_data"]
def _load_config_and_refresh_ui(self, directory, filename):
self.load_config(os.path.join(directory, filename))
self._build_window_ui()
def save_config(self, path):
os.makedirs(os.path.dirname(path), exist_ok=True)
if os.path.isfile(path):
carb.log_info(f"Overwriting config file {path}.")
with open(path, "w") as json_file:
config = {
"num_frames": self._num_frames,
"rt_subframes": self._rt_subframes,
"control_timeline": self._control_timeline,
"out_write_type": self._out_write_type.name,
"use_s3": self._use_s3,
"s3_params": self._s3_params,
"basic_writer_params": self._basic_writer_params,
"rp_data": self._rp_data,
}
# Only save string values if they are not empty
if self._writer_name:
config["writer_name"] = self._writer_name
if self._custom_writer_name:
config["custom_writer_name"] = self._custom_writer_name
if self._config_file:
config["config_file"] = self._config_file
if self._custom_params_path:
config["custom_params_path"] = self._custom_params_path
if self._out_working_dir:
config["out_working_dir"] = self._out_working_dir
if self._out_dir:
config["out_dir"] = self._out_dir
json.dump(config, json_file, indent=4)
def _get_custom_params(self, path):
custom_params = {}
if not os.path.isfile(path):
carb.log_warn(f"Could not find params file {path}.")
return custom_params
with open(path, "r") as f:
params = json.load(f)
for key in params:
custom_params[key] = params[key]
return custom_params
def _reset_config_dir(self):
self._config_dir = os.path.abspath(
os.path.join(omni.kit.app.get_app().get_extension_manager().get_extension_path(self._ext_id), "data", "")
)
self._build_window_ui()
def _reset_out_working_dir(self):
self._out_working_dir = os.getcwd() + "/"
self._build_window_ui()
def _get_dir_next_numerical_suffix(self, path, dir_name):
nums = [-1]
for file in os.listdir(path):
if file.startswith(dir_name) and os.path.isdir(os.path.join(path, file)):
file = file[len(dir_name) :]
file = file.replace("_", "")
if file.isdecimal():
nums.append(int(file))
suffix = "_" + str(max(nums) + 1)
return suffix
def _get_output_dir(self):
out_dir = self._out_dir
if self._out_write_type is OutWriteType.INCREMENT:
out_dir = out_dir + self._get_dir_next_numerical_suffix(self._out_working_dir, out_dir)
elif self._out_write_type is OutWriteType.TIMESTAMP:
out_dir = out_dir + time.strftime("_%Y-%m-%d-%H-%M-%S")
return os.path.join(self._out_working_dir, out_dir, "")
def _check_if_valid_camera(self, path):
context = omni.usd.get_context()
stage = context.get_stage()
prim = stage.GetPrimAtPath(path)
if not prim.IsValid():
carb.log_warn(f"{path} is not a valid prim path.")
return False
if prim.GetTypeName() == "Camera":
return True
else:
carb.log_warn(f"{prim} is not a 'Camera' type.")
return False
def _check_if_valid_resolution(self, width, height):
if 0 <= width <= MAX_RESOLUTION[0] and 0 <= height <= MAX_RESOLUTION[1]:
return True
else:
carb.log_warn(
f"Invalid resolution: {width}x{height}. Must be between 1x1 and {MAX_RESOLUTION[0]}x{MAX_RESOLUTION[1]}."
)
return False
def _check_if_valid_rp_entry(self, entry):
if (
len(entry) == 3
and self._check_if_valid_camera(entry[0])
and self._check_if_valid_resolution(entry[1], entry[2])
):
return True
else:
return False
def _check_if_stage_is_semantically_labeled(self):
stage = omni.usd.get_context().get_stage()
for prim in stage.Traverse():
if prim.HasAPI(Semantics.SemanticsAPI):
return True
carb.log_warn("Stage is not semantically labeled, semantics related annotators will not work.")
return False
def _check_if_stage_has_skeleton_prims(self):
stage = omni.usd.get_context().get_stage()
for prim in stage.Traverse():
if prim.GetTypeName() == "Skeleton":
return True
carb.log_warn("Stage does not have any skeleton prims, skeleton annotator will not work.")
return False
def _remove_semantics_annotators(self, writer_params):
disabled_annotators = []
semantics_annotators = [
"bounding_box_2d_tight",
"bounding_box_2d_loose",
"semantic_segmentation",
"instance_id_segmentation",
"instance_segmentation",
"bounding_box_3d",
"occlusion",
]
for annotator in semantics_annotators:
if annotator in writer_params and writer_params[annotator]:
writer_params[annotator] = False
disabled_annotators.append(annotator)
if disabled_annotators:
carb.log_warn(f"Disabled the following semantics related annotators: {disabled_annotators}.")
def _update_rp_entry(self, idx, field, value):
self._rp_data[idx][field] = value
def _remove_rp_entry(self, idx):
del self._rp_data[idx]
self._build_window_ui()
def _add_new_rp_field(self):
# If cameras are selected in the stage viewer use them default values
context = omni.usd.get_context()
stage = context.get_stage()
selected_prims = context.get_selection().get_selected_prim_paths()
selected_cameras = [path for path in selected_prims if stage.GetPrimAtPath(path).GetTypeName() == "Camera"]
if selected_cameras:
for path in selected_cameras:
self._rp_data.append([path, 512, 512])
else:
# Use selected viewport camera as default value
active_vp = get_active_viewport()
active_cam = active_vp.get_active_camera()
self._rp_data.append([str(active_cam), 512, 512])
self._build_window_ui()
def _clear_recorder(self):
if self._writer:
self._writer.detach()
self._writer = None
self._render_products.clear()
def _init_recorder(self) -> bool:
if self._writer is None:
try:
self._writer = rep.WriterRegistry.get(self._writer_name)
except Exception as e:
carb.log_warn(f"Could not create writer {self._writer_name}: {e}")
return False
# Set the number of subframes
if self._rt_subframes != carb.settings.get_settings().get("/omni/replicator/RTSubframes"):
rep.settings.carb_settings("/omni/replicator/RTSubframes", self._rt_subframes)
carb.log_info(f"Setting 'RTSubframes' to {self._rt_subframes}.")
# Init the default or custom writer with its parameters
writer_params = {}
if self._writer_name == "BasicWriter":
# In case S3 is selected, make sure the s3 parameters are valid
if self._use_s3:
# s3_bucket is a required parameter, if it is not set, do not initialize the writer
if not self._s3_params["s3_bucket"]:
carb.log_warn("Could not initialize writer, s3_bucket parameters is missing.")
return False
# Other S3 parameters are optional, set them to None in case of empty strings
for key, value in self._s3_params.items():
if value == "":
self._s3_params[key] = None
writer_params = {**self._basic_writer_params, **self._s3_params}
else:
writer_params = {**self._basic_writer_params}
# Disable semantics related annotators if the stage is not semantically labeled
stage_is_labeled = self._check_if_stage_is_semantically_labeled()
if not stage_is_labeled:
self._remove_semantics_annotators(writer_params)
# Disable skeleton annotator if the stage does not have any skeleton prims
if writer_params["skeleton_data"] and not self._check_if_stage_has_skeleton_prims():
carb.log_warn("Stage does not have any skeleton prims, disabling 'skeleton_data' annotator.")
writer_params["skeleton_data"] = False
else:
# Custom writers will not get any sanity cheks, it is up to the user to make sure the parameters are valid
custom_params = self._get_custom_params(self._custom_params_path)
writer_params = {**custom_params}
# Output path can suffixed with an increment or a timestamp if the user has enabled the option
output_dir = self._get_output_dir()
try:
self._writer.initialize(output_dir=output_dir, **writer_params)
except Exception as e:
carb.log_warn(f"Could not initialize writer {self._writer_name}: {e}")
return False
# Create the render products
for rp_entry in self._rp_data:
if self._check_if_valid_rp_entry(rp_entry):
rp = rep.create.render_product(rp_entry[0], (rp_entry[1], rp_entry[2]))
self._render_products.append(rp)
else:
carb.log_warn(f"Invalid render product entry {rp_entry}.")
if not self._render_products:
carb.log_warn("No valid render products found to initialize the writer.")
return False
try:
self._writer.attach(self._render_products)
except Exception as e:
carb.log_warn(f"Could not attach render products to writer: {e}")
return False
return True
async def _on_orchestrator_finish_async(self):
if self._control_timeline:
await self._set_timeline_state_async(case="reset")
await rep.orchestrator.wait_until_complete_async()
self._clear_recorder()
self._disable_all_buttons()
self._enable_buttons(case="stop")
self._in_running_state = False
async def _set_timeline_state_async(self, case="reset"):
timeline = omni.timeline.get_timeline_interface()
if case == "reset":
if timeline.is_playing():
timeline.stop()
timeline.set_current_time(0)
await omni.kit.app.get_app().next_update_async()
elif case == "pause":
if timeline.is_playing():
timeline.pause()
elif case == "resume":
if not timeline.is_playing():
timeline.play()
async def _start_stop_recorder_async(self):
if self._orchestrator_status is orchestrator.Status.STOPPED:
self._disable_all_buttons()
if self._init_recorder():
num_frames = None if self._num_frames <= 0 else self._num_frames
await rep.orchestrator.run_async(num_frames=num_frames, start_timeline=self._control_timeline)
self._in_running_state = True
self._enable_buttons(case="start")
else:
self._clear_recorder()
self._enable_buttons(case="reset")
elif self._orchestrator_status in [orchestrator.Status.STARTED, orchestrator.Status.PAUSED]:
self._disable_all_buttons()
await rep.orchestrator.stop_async()
if self._control_timeline:
await self._set_timeline_state_async(case="reset")
self._clear_recorder()
self._in_running_state = False
self._enable_buttons(case="stop")
else:
carb.log_warn(
f"Replicator's current state({self._orchestrator_status.name}) is different state than STOPPED, STARTED or PAUSED. Try again in a bit."
)
def _pause_resume_recorder(self):
self._pause_resume_button.enabled = False
if self._orchestrator_status is orchestrator.Status.STARTED:
rep.orchestrator.pause()
if self._control_timeline:
asyncio.ensure_future(self._set_timeline_state_async(case="pause"))
self._pause_resume_button.text = "Resume"
elif self._orchestrator_status is orchestrator.Status.PAUSED:
rep.orchestrator.resume()
if self._control_timeline:
asyncio.ensure_future(self._set_timeline_state_async(case="resume"))
self._pause_resume_button.text = "Pause"
else:
carb.log_warn(
f"Replicator's current state ({self._orchestrator_status.name}) is different state than STARTED or PAUSED. Try again in a bit."
)
self._pause_resume_button.enabled = True
def _disable_all_buttons(self):
self._start_stop_button.enabled = False
self._pause_resume_button.enabled = False
def _enable_buttons(self, case="reset"):
if case == "reset":
self._start_stop_button.text = "Start"
self._pause_resume_button.text = "Pause"
self._start_stop_button.enabled = True
elif case == "start":
self._start_stop_button.text = "Stop"
self._start_stop_button.enabled = True
self._pause_resume_button.enabled = True
elif case == "stop":
self._start_stop_button.text = "Start"
self._pause_resume_button.text = "Pause"
self._start_stop_button.enabled = True
def _build_config_ui(self):
with ui.VStack(spacing=5):
with ui.HStack():
ui.Spacer(width=10)
ui.Label("Config Directory", tooltip="Config files directory path")
with ui.HStack():
ui.Spacer(width=10)
config_dir_model = ui.StringField(read_only=False).model
config_dir_model.set_value(self._config_dir)
def config_dir_changed(model):
self._config_dir = model.as_string
config_dir_model.add_value_changed_fn(config_dir_changed)
ui.Spacer(width=5)
ui.Button(
f"{_ui_get_open_folder_glyph()}",
width=20,
clicked_fn=lambda: self._open_dir(self._config_dir),
tooltip="Open config directory",
)
ui.Button(
f"{_ui_get_reset_glyph()}",
width=20,
clicked_fn=lambda: self._reset_config_dir(),
tooltip="Reset config directory to default",
)
with ui.HStack(spacing=5):
ui.Spacer(width=5)
config_file_model = ui.StringField(tooltip="Config file name").model
config_file_model.set_value(self._config_file)
def config_file_changed(model):
self._config_file = model.as_string
config_file_model.add_value_changed_fn(config_file_changed)
ui.Button(
"Load",
clicked_fn=lambda: self._load_config_and_refresh_ui(self._config_dir, self._config_file),
tooltip="Load and apply selected config file",
)
ui.Button(
"Save",
clicked_fn=lambda: self.save_config(os.path.join(self._config_dir, self._config_file)),
tooltip="Save current config to selected file",
)
def _build_s3_ui(self):
with ui.VStack(spacing=5):
with ui.HStack():
ui.Spacer(width=10)
ui.Label("Use S3", alignment=ui.Alignment.LEFT, tooltip="Write data to S3 buckets")
s3_model = ui.CheckBox().model
s3_model.set_value(self._use_s3)
def value_changed(m):
self._use_s3 = m.as_bool
if self._use_s3 and self._out_write_type is OutWriteType.INCREMENT:
print(f"Incremental output is not supported for S3. Switching to Timestamp.")
self._out_write_type = OutWriteType.TIMESTAMP
# Rebuild ui to update radio buttons state to TIMESTAMP
self._build_window_ui()
s3_model.add_value_changed_fn(value_changed)
for key, val in self._s3_params.items():
with ui.HStack():
ui.Spacer(width=10)
ui.Label(key, alignment=ui.Alignment.LEFT, tooltip=PARAM_TOOLTIPS[key])
model = ui.StringField().model
if val:
model.set_value(val)
else:
model.set_value("")
def value_changed(m, k=key):
self._s3_params[k] = m.as_string
model.add_value_changed_fn(value_changed)
def _build_output_ui(self):
with ui.VStack(spacing=5):
with ui.HStack():
ui.Spacer(width=10)
ui.Label("Working Directory")
with ui.HStack():
ui.Spacer(width=10)
out_working_dir_model = ui.StringField().model
out_working_dir_model.set_value(self._out_working_dir)
def out_working_dir_changed(model):
self._out_working_dir = model.as_string
out_working_dir_model.add_value_changed_fn(out_working_dir_changed)
ui.Spacer(width=5)
ui.Button(
f"{_ui_get_open_folder_glyph()}",
width=20,
clicked_fn=lambda: self._open_dir(self._out_working_dir),
tooltip="Open working directory",
)
ui.Button(
f"{_ui_get_reset_glyph()}",
width=20,
clicked_fn=lambda: self._reset_out_working_dir(),
tooltip="Reset directory to default",
)
with ui.HStack(spacing=5):
ui.Spacer(width=5)
out_dir_model = ui.StringField().model
out_dir_model.set_value(self._out_dir)
def out_dir_changed(model):
self._out_dir = model.as_string
out_dir_model.add_value_changed_fn(out_dir_changed)
write_collection = ui.RadioCollection()
write_collection.model.set_value(self._out_write_type.value)
def write_collection_changed(model):
out_write_type = OutWriteType(model.as_int)
if self._use_s3 and out_write_type is OutWriteType.INCREMENT:
print(f"Incremental output is not supported for S3. Switching to Timestamp.")
self._out_write_type = OutWriteType.TIMESTAMP
# Rebuild ui to update radio buttons state to TIMESTAMP
self._build_window_ui()
else:
self._out_write_type = out_write_type
write_collection.model.add_value_changed_fn(write_collection_changed)
ui.RadioButton(
text="Overwrite",
radio_collection=write_collection,
tooltip="Overwrite data if output folder already exists",
)
ui.RadioButton(
text="Increment",
radio_collection=write_collection,
tooltip="Append numerical increments to output folder (e.g., _01, _02). NOTE: does not work with S3",
)
ui.RadioButton(
text="Timestamp",
radio_collection=write_collection,
tooltip="Append timestamp to output folder (e.g., _YYYY-mm-dd-HH-MM-SS)",
)
s3_frame = ui.CollapsableFrame("S3 Bucket", height=0, collapsed=self._s3_params_frame_collapsed)
with s3_frame:
def on_collapsed_changed(collapsed):
self._s3_params_frame_collapsed = collapsed
s3_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_s3_ui()
def _build_rp_ui(self):
with ui.VStack(spacing=5):
with ui.HStack(spacing=5):
ui.Spacer(width=15)
ui.Label("Camera Path", width=200, tooltip="Camera prim to be used as a render product")
ui.Spacer(width=15)
ui.Label("X", tooltip="X resolution of the render product")
ui.Spacer(width=15)
ui.Label("Y", tooltip="Y resolution of the render product")
for i, entry in enumerate(self._rp_data):
with ui.HStack(spacing=5):
ui.Spacer(width=10)
path_field_model = ui.StringField(width=200).model
path_field_model.set_value(entry[0])
path_field_model.add_value_changed_fn(lambda m, idx=i: self._update_rp_entry(idx, 0, m.as_string))
ui.Spacer(width=10)
x_field = ui.IntField()
x_field.model.set_value(entry[1])
x_field.model.add_value_changed_fn(lambda m, idx=i: self._update_rp_entry(idx, 1, m.as_int))
ui.Spacer(width=10)
y_field = ui.IntField()
y_field.model.set_value(entry[2])
y_field.model.add_value_changed_fn(lambda m, idx=i: self._update_rp_entry(idx, 2, m.as_int))
ui.Button(
f"{_ui_get_delete_glyph()}",
width=30,
clicked_fn=lambda idx=i: self._remove_rp_entry(idx),
tooltip="Remove entry",
)
with ui.HStack(spacing=5):
ui.Spacer(width=5)
ui.Button(
"Add New Render Product Entry", clicked_fn=self._add_new_rp_field, tooltip="Create a new entry"
)
def _build_params_ui(self):
with ui.VStack(spacing=5):
with ui.HStack():
ui.Spacer(width=10)
ui.Label("Writer")
writer_type_collection = ui.RadioCollection()
if self._writer_name == "BasicWriter":
writer_type_collection.model.set_value(0)
else:
writer_type_collection.model.set_value(1)
def writer_type_collection_changed(model):
if model.as_int == 0:
self._custom_writer_name = self._writer_name
self._writer_name = "BasicWriter"
else:
self._writer_name = self._custom_writer_name
# self._writer_name = "BasicWriter" if model.as_int == 0 else "CustomWriter"
self._build_window_ui()
writer_type_collection.model.add_value_changed_fn(writer_type_collection_changed)
ui.RadioButton(
text="Default", radio_collection=writer_type_collection, tooltip="Uses the default BasicWriter"
)
ui.RadioButton(
text="Custom", radio_collection=writer_type_collection, tooltip="Loads a custom writer by name"
)
if self._writer_name == "BasicWriter":
self._build_basic_writer_ui()
else:
self._build_custom_writer_ui()
def _build_basic_writer_ui(self):
for key, val in self._basic_writer_params.items():
with ui.HStack(spacing=5):
ui.Spacer(width=10)
ui.Label(key, alignment=ui.Alignment.LEFT, tooltip=PARAM_TOOLTIPS[key])
model = ui.CheckBox().model
model.set_value(val)
def value_changed(m, k=key):
self._basic_writer_params[k] = m.as_bool
model.add_value_changed_fn(value_changed)
def _build_custom_writer_ui(self):
with ui.HStack(spacing=5):
ui.Spacer(width=10)
ui.Label("Name", tooltip="The name of the custom writer from the registry")
writer_name_model = ui.StringField().model
writer_name_model.set_value(self._writer_name)
def writer_name_changed(m):
self._writer_name = m.as_string
writer_name_model.add_value_changed_fn(writer_name_changed)
with ui.HStack(spacing=5):
ui.Spacer(width=10)
ui.Label("Parameters Path", tooltip="Path to the json file storing the custom writer parameters")
path_model = ui.StringField().model
path_model.set_value(self._custom_params_path)
def path_changed(m):
self._custom_params_path = m.as_string
path_model.add_value_changed_fn(path_changed)
def _build_writer_ui(self):
with ui.VStack(spacing=5):
rp_frame = ui.CollapsableFrame("Render Products", height=0, collapsed=self._rp_frame_collapsed)
with rp_frame:
def on_collapsed_changed(collapsed):
self._rp_frame_collapsed = collapsed
rp_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_rp_ui()
params_frame = ui.CollapsableFrame("Parameters", height=0, collapsed=self._writer_params_frame_collapsed)
with params_frame:
def on_collapsed_changed(collapsed):
self._writer_params_frame_collapsed = collapsed
params_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_params_ui()
output_frame = ui.CollapsableFrame("Output", height=0, collapsed=self._output_frame_collapsed)
with output_frame:
def on_collapsed_changed(collapsed):
self._output_frame_collapsed = collapsed
output_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_output_ui()
config_frame = ui.CollapsableFrame("Config", height=0, collapsed=self._config_frame_collapsed)
with config_frame:
def on_collapsed_changed(collapsed):
self._config_frame_collapsed = collapsed
config_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_config_ui()
def _build_control_params_ui(self):
with ui.VStack(spacing=10):
with ui.HStack(spacing=5):
ui.Spacer(width=10)
ui.Label("Number of frames", tooltip="If set to 0, data acquisition will run indefinitely")
num_frames_model = ui.IntField().model
num_frames_model.set_value(self._num_frames)
def num_frames_changed(m):
self._num_frames = m.as_int
num_frames_model.add_value_changed_fn(num_frames_changed)
ui.Label("RTSubframes", tooltip="Render extra frames between captures to avoid rendering artifacts")
rt_subframes_model = ui.IntField().model
rt_subframes_model.set_value(self._rt_subframes)
def num_rt_subframes_changed(m):
self._rt_subframes = m.as_int
rt_subframes_model.add_value_changed_fn(num_rt_subframes_changed)
with ui.HStack(spacing=5):
ui.Spacer(width=10)
ui.Label(
"Control Timeline",
alignment=ui.Alignment.LEFT,
tooltip="Start/Stop/Pause/Reset the timeline with the recorder",
)
control_timeline_model = ui.CheckBox().model
control_timeline_model.set_value(self._control_timeline)
def value_changed(m):
self._control_timeline = m.as_bool
control_timeline_model.add_value_changed_fn(value_changed)
def _build_control_ui(self):
with ui.VStack(spacing=5):
control_params_frame = ui.CollapsableFrame(
"Parameters", height=0, collapsed=self._control_params_frame_collapsed
)
with control_params_frame:
def on_collapsed_changed(collapsed):
self._control_params_frame_collapsed = collapsed
control_params_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_control_params_ui()
with ui.HStack(spacing=5):
ui.Spacer(width=5)
self._start_stop_button = ui.Button(
"Start",
clicked_fn=lambda: asyncio.ensure_future(self._start_stop_recorder_async()),
enabled=True,
tooltip="Start/stop the recording",
)
self._pause_resume_button = ui.Button(
"Pause", clicked_fn=self._pause_resume_recorder, enabled=False, tooltip="Pause/resume recording"
)
def _build_window_ui(self):
with self._window.frame:
with ui.ScrollingFrame():
with ui.VStack(spacing=5):
writer_frame = ui.CollapsableFrame("Writer", height=0, collapsed=self._writer_frame_collapsed)
with writer_frame:
def on_collapsed_changed(collapsed):
self._writer_frame_collapsed = collapsed
writer_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_writer_ui()
control_frame = ui.CollapsableFrame("Control", height=0, collapsed=self._control_frame_collapsed)
with control_frame:
def on_collapsed_changed(collapsed):
self._control_frame_collapsed = collapsed
control_frame.set_collapsed_changed_fn(on_collapsed_changed)
self._build_control_ui()
| 46,149 | Python | 45.475327 | 736 | 0.587813 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/omni/isaac/synthetic_recorder/extension_custom.py | # Copyright (c) 2018-2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import carb
import omni
import omni.syntheticdata._syntheticdata as gt
import omni.ui as ui
from omni.kit.menu.utils import add_menu_items, remove_menu_items, MenuItemDescription
import asyncio
import atexit
import colorsys
import copy
import queue
import random
import os
import threading
import numpy as np
import weakref
from carb.settings import get_settings
from PIL import Image, ImageDraw
from omni.isaac.synthetic_utils import visualization as vis
from omni.isaac.synthetic_utils import SyntheticDataHelper, NumpyWriter
from omni.syntheticdata import sensors, visualize
EXTENSION_NAME = "Synthetic Data Recorder 2"
class MyRecorder():
def on_startup(self):
"""Called to load the extension"""
self._timeline = omni.timeline.get_timeline_interface()
self._display_paths = []
self._interface = gt.acquire_syntheticdata_interface()
self._enable_record = False
self._enable_timeline_record = False
self._counter = 0
# self.sub_update = omni.kit.app.get_app().get_update_event_stream().create_subscription_to_pop(self._update)
self._update_fps = omni.kit.app.get_app().get_update_event_stream().create_subscription_to_pop(
self._fps_info_update, name="omni.kit.debug.frame_info update"
)
self._current_fps = ""
self._settings = get_settings()
self._viewport = omni.kit.viewport.window
self._viewport_names = []
self._num_viewports = 0
self.data_writer = None
self.sd_helper = SyntheticDataHelper()
self.sensor_settings_default = {
"rgb": {"enabled": False},
"depth": {"enabled": False, "colorize": False, "npy": False},
"depthLinear": {"enabled": False, "colorize": False, "npy": False},
"instance": {"enabled": False, "colorize": False, "npy": False},
"semantic": {"enabled": False, "colorize": False, "npy": False},
"bbox_2d_tight": {"enabled": False, "colorize": False, "npy": False},
"bbox_2d_loose": {"enabled": False, "colorize": False, "npy": False},
"normals": {"enabled": False, "colorize": False, "npy": False},
"motion-vector": {"enabled": False, "colorize": False, "npy": False},
"bbox_3d": {"enabled": False, "colorize": False, "npy": False},
"camera": {"enabled": False, "colorize": False, "npy": False},
"poses": {"enabled": False, "colorize": False, "npy": False},
}
self._sensor_settings = {}
self._sensor_settings_single = {}
self.set_settings(self.sensor_settings_default)
self._viewport_names = []
self._dir_name = ''
self._num_threads = 10
self._max_queue_size = 500
self.verify = {}
self.skip_cameras = 0
def get_default_settings(self):
return self.sensor_settings_default
def set_single_settings(self, settings):
self._sensor_settings_single = copy.deepcopy(settings)
def set_settings(self, settings):
for index, viewport_name in enumerate(self._viewport_names):
if index >= self.skip_cameras:
viewport_name = viewport_name.split(" ")[0] + str(int(index - self.skip_cameras))
self._sensor_settings[viewport_name] = copy.deepcopy(settings)
else:
continue
# def _update(self, e: carb.events.IEvent):
def _update(self):
tmp = [x for x in self._viewport.get_viewport_window_instances()]
if len(tmp) != self._num_viewports:
self._num_viewports = len(tmp)
self._viewport_names = [x.name for x in tmp]
self._is_first_run = [True] * self._num_viewports
self.set_settings(self._sensor_settings_single)
self.verify[self._viewport_names[-1]] = True
if not self._timeline.is_playing():
print("Cannot Generate Data! Editor is not playing.")
self._enable_record = False
return
if self._dir_name == "":
print("Cannot generate data, empty dir")
return
data_dir = str(self._dir_name)
if self.data_writer is None:
self.data_writer = NumpyWriter(
data_dir,
self._num_threads,
self._max_queue_size,
self._sensor_settings,
)
self.data_writer.start_threads()
self._render_mode = str(self._settings.get("/rtx/rendermode"))
for index, viewport_name in enumerate(self._viewport_names):
if index < self.skip_cameras:
continue
real_viewport_name = viewport_name
viewport_name = viewport_name.split(" ")[0] + str(int(index - self.skip_cameras))
groundtruth = {
"METADATA": {
"image_id": str(self._counter),
"viewport_name": viewport_name,
"DEPTH": {},
"DEPTHLINEAR": {},
"INSTANCE": {},
"SEMANTIC": {},
"BBOX2DTIGHT": {},
"BBOX2DLOOSE": {},
"NORMALS": {},
"MOTIONVECTOR": {},
"BBOX3D": {},
"CAMERA": {},
"POSES": {},
},
"DATA": {},
}
gt_list = []
if self._sensor_settings[viewport_name]["rgb"]["enabled"]:
gt_list.append("rgb")
if self._sensor_settings[viewport_name]["depthLinear"]["enabled"]:
gt_list.append("depthLinear")
if self._sensor_settings[viewport_name]["depth"]["enabled"]:
gt_list.append("depth")
if self._sensor_settings[viewport_name]["bbox_2d_tight"]["enabled"]:
gt_list.append("boundingBox2DTight")
if self._sensor_settings[viewport_name]["bbox_2d_loose"]["enabled"]:
gt_list.append("boundingBox2DLoose")
if self._sensor_settings[viewport_name]["instance"]["enabled"]:
gt_list.append("instanceSegmentation")
if self._sensor_settings[viewport_name]["semantic"]["enabled"]:
gt_list.append("semanticSegmentation")
if self._sensor_settings[viewport_name]["motion-vector"]["enabled"]:
gt_list.append("motion-vector")
if self._sensor_settings[viewport_name]["normals"]["enabled"]:
gt_list.append("normals")
if self._sensor_settings[viewport_name]["bbox_3d"]["enabled"]:
gt_list.append("boundingBox3D")
if self._sensor_settings[viewport_name]["poses"]["enabled"]:
gt_list.append("pose")
if self._sensor_settings[viewport_name]["camera"]["enabled"]:
gt_list.append("camera")
for j in tmp:
if j.name == real_viewport_name:
viewport = j
break
try:
gt = self.sd_helper.get_groundtruth(gt_list, viewport.viewport_api,
verify_sensor_init=self.verify[real_viewport_name])
self.verify[real_viewport_name] = False
except:
self.verify[real_viewport_name] = True
gt = self.sd_helper.get_groundtruth(gt_list, viewport.viewport_api,
verify_sensor_init=self.verify[real_viewport_name])
self.verify[real_viewport_name] = False
if self._enable_record == False:
continue
mappings = []
# RGB
if self._sensor_settings[viewport_name]["rgb"]["enabled"] and gt["state"]["rgb"]:
groundtruth["DATA"]["RGB"] = gt["rgb"]
# Depth
if self._sensor_settings[viewport_name]["depth"]["enabled"] and gt["state"]["depth"]:
groundtruth["DATA"]["DEPTH"] = gt["depth"].squeeze()
groundtruth["METADATA"]["DEPTH"]["COLORIZE"] = self._sensor_settings[viewport_name]["depth"]["colorize"]
groundtruth["METADATA"]["DEPTH"]["NPY"] = self._sensor_settings[viewport_name]["depth"]["npy"]
# DepthLinear
if self._sensor_settings[viewport_name]["depthLinear"]["enabled"] and gt["state"]["depthLinear"]:
groundtruth["DATA"]["DEPTHLINEAR"] = gt["depthLinear"].squeeze()
groundtruth["METADATA"]["DEPTHLINEAR"]["COLORIZE"] = self._sensor_settings[viewport_name]["depthLinear"]["colorize"]
groundtruth["METADATA"]["DEPTHLINEAR"]["NPY"] = self._sensor_settings[viewport_name]["depthLinear"]["npy"]
# Instance Segmentation
if self._sensor_settings[viewport_name]["instance"]["enabled"] and gt["state"]["instanceSegmentation"]:
import ipdb;
ipdb.set_trace()
instance_data = gt["instanceSegmentation"]
groundtruth["DATA"]["INSTANCE"] = instance_data
try:
groundtruth["METADATA"]["INSTANCE"]["WIDTH"] = instance_data[0].shape[1]
groundtruth["METADATA"]["INSTANCE"]["HEIGHT"] = instance_data[0].shape[0]
mappings = instance_data[1]
except:
groundtruth["METADATA"]["INSTANCE"]["WIDTH"] = instance_data.shape[1]
groundtruth["METADATA"]["INSTANCE"]["HEIGHT"] = instance_data.shape[0]
mappings = []
groundtruth["METADATA"]["INSTANCE"]["MAPPINGS"] = self._sensor_settings[viewport_name]["instance"][
"mappings"
]
groundtruth["METADATA"]["INSTANCE"]["COLORIZE"] = self._sensor_settings[viewport_name]["instance"][
"colorize"
]
groundtruth["METADATA"]["INSTANCE"]["NPY"] = self._sensor_settings[viewport_name]["instance"]["npy"]
# Semantic Segmentation
if self._sensor_settings[viewport_name]["semantic"]["enabled"] and gt["state"]["semanticSegmentation"]:
semantic_data = gt["semanticSegmentation"]
semantic_data[semantic_data == 65535] = 0 # deals with invalid semantic id
groundtruth["DATA"]["SEMANTIC"] = (semantic_data, mappings)
groundtruth["METADATA"]["SEMANTIC"]["WIDTH"] = semantic_data.shape[1]
groundtruth["METADATA"]["SEMANTIC"]["HEIGHT"] = semantic_data.shape[0]
groundtruth["METADATA"]["SEMANTIC"]["MAPPINGS"] = self._sensor_settings[viewport_name]["instance"][
"mappings"
]
groundtruth["METADATA"]["SEMANTIC"]["COLORIZE"] = self._sensor_settings[viewport_name]["semantic"][
"colorize"
]
groundtruth["METADATA"]["SEMANTIC"]["NPY"] = self._sensor_settings[viewport_name]["semantic"]["npy"]
# 2D Tight BBox
if self._sensor_settings[viewport_name]["bbox_2d_tight"]["enabled"] and gt["state"]["boundingBox2DTight"]:
groundtruth["DATA"]["BBOX2DTIGHT"] = gt["boundingBox2DTight"]
groundtruth["METADATA"]["BBOX2DTIGHT"]["COLORIZE"] = self._sensor_settings[viewport_name][
"bbox_2d_tight"
]["colorize"]
groundtruth["METADATA"]["BBOX2DTIGHT"]["NPY"] = self._sensor_settings[viewport_name]["bbox_2d_tight"][
"npy"
]
# 2D Loose BBox
if self._sensor_settings[viewport_name]["bbox_2d_loose"]["enabled"] and gt["state"]["boundingBox2DLoose"]:
groundtruth["DATA"]["BBOX2DLOOSE"] = gt["boundingBox2DLoose"]
groundtruth["METADATA"]["BBOX2DLOOSE"]["COLORIZE"] = self._sensor_settings[viewport_name][
"bbox_2d_loose"
]["colorize"]
groundtruth["METADATA"]["BBOX2DLOOSE"]["NPY"] = self._sensor_settings[viewport_name]["bbox_2d_loose"][
"npy"
]
# 3D Bounding Box
if self._sensor_settings[viewport_name]["bbox_3d"]["enabled"] and gt["state"]["boundingBox3D"]:
groundtruth["DATA"]["BBOX3D"] = gt["boundingBox3D"].squeeze()
groundtruth["METADATA"]["BBOX3D"]["COLORIZE"] = self._sensor_settings[viewport_name]["bbox_3d"][
"colorize"]
groundtruth["METADATA"]["BBOX3D"]["NPY"] = self._sensor_settings[viewport_name]["bbox_3d"]["npy"]
groundtruth["METADATA"]["BBOX3D_IMAGE"] =visualize.get_bbox3d(viewport.viewport_api)
# Motion vector
if self._sensor_settings[viewport_name]["motion-vector"]["enabled"] and gt["state"]["motion-vector"]:
groundtruth["DATA"]["MOTIONVECTOR"] = gt["motion-vector"].squeeze()
groundtruth["METADATA"]["MOTIONVECTOR"]["COLORIZE"] = \
self._sensor_settings[viewport_name]["motion-vector"][
"colorize"]
groundtruth["METADATA"]["MOTIONVECTOR"]["NPY"] = self._sensor_settings[viewport_name]["motion-vector"][
"npy"]
# Poses
if self._sensor_settings[viewport_name]["poses"]["enabled"] and gt["pose"]:
groundtruth["DATA"]["POSES"] = gt["pose"]
groundtruth["METADATA"]["POSES"]["NPY"] = self._sensor_settings[viewport_name]["poses"]["npy"]
# Camera
if self._sensor_settings[viewport_name]["camera"]["enabled"] and gt["state"]["camera"]:
groundtruth["DATA"]["CAMERA"] = gt["camera"]
groundtruth["METADATA"]["CAMERA"]["NPY"] = self._sensor_settings[viewport_name]["camera"]["npy"]
# Normals
if self._sensor_settings[viewport_name]["normals"]["enabled"] and gt["state"]["normals"]:
groundtruth["DATA"]["NORMALS"] = gt["normals"].squeeze()
groundtruth["METADATA"]["NORMALS"]["NPY"] = self._sensor_settings[viewport_name]["normals"]["npy"]
self.data_writer.q.put(copy.deepcopy(groundtruth))
# self._counter = self._counter + 1
def _fps_info_update(self, event):
dt = event.payload["dt"] * 1000.0
self._current_fps = "%1.2fms [%1.2f]" % (dt, 1000.0 / dt)
| 14,898 | Python | 47.84918 | 132 | 0.558196 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/docs/CHANGELOG.md | # Changelog
## [1.5.0] - 2023-03-13
### Added
- pointcloud_include_unlabelled parameter for pointcloud data
## [1.4.2] - 2023-02-22
### Fixed
- added wait_until_complete for S3 bucket writing one frame less (OM-82465)
- S3 accepting None values for s3_region and s3_endpoint
## [1.4.1] - 2023-02-14
### Fixed
- Synthetic recorder should only subscribe to the type of stage event it needs
## [1.4.0] - 2023-02-07
### Added
- Timeline Control
### Fixed
- Incremental folder naming not supported with S3 (OM-80864)
## [1.3.0] - 2023-01-25
### Removed
- Manual Control UI
### Changed
- Switched to async functions from Replicator 1.7.1 API
## [1.2.2] - 2023-01-06
### Fixed
- onclick_fn warning when creating UI
## [1.2.1] - 2023-01-04
### Fixed
- clean-ups on on_shutdown
## [1.2.0] - 2022-12-09
### Fixed
- Empty strings are no loger saved to config files
### Added
- Refresh path strings to default
## [1.1.1] - 2022-12-06
### Fixed
- Menu toggle value when user closes the window
## [1.1.0] - 2022-11-30
### Added
- Support for loading custom writers
### Changed
- renamed extension.py to synthetic_recorder_extension.py
- renamed extension class from Extension to SyntheticRecorderExtension
### Fixed
- Annotators blocking other annotators of writing data if their requirements are not met
## [1.0.0] - 2022-11-14
### Added
- version using Replicator OV API
## [0.1.2] - 2022-09-07
### Fixed
- Fixes for kit 103.5
## [0.1.1] - 2022-08-02
### Fixed
- Error message when there was no instance data to write
## [0.1.0] - 2021-08-11
### Added
- Initial version of Isaac Sim Synthetic Data Recorder Extension
- Records RGB, Depth, Semantic and Instance segmentation, 2D Tight and Loose bounding box
- Supports multi-viewport recording
| 1,755 | Markdown | 20.679012 | 89 | 0.694587 |
eliabntt/GRADE-RR/isaac_internals/exts/omni.isaac.synthetic_recorder/docs/README.md | # Usage
To enable this extension, go to the Extension Manager menu and enable omni.isaac.synthetic_recorder extension.
Online documentation at:
* https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/tutorial_replicator_recorder.html#isaac-sim-app-tutorial-replicator-recorder
| 288 | Markdown | 31.111108 | 138 | 0.8125 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/PACKAGE-LICENSES/omni.syntheticdata-LICENSE.md | Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
NVIDIA CORPORATION and its licensors retain all intellectual property
and proprietary rights in and to this software, related documentation
and any modifications thereto. Any use, reproduction, disclosure or
distribution of this software and related documentation without an express
license agreement from NVIDIA CORPORATION is strictly prohibited. | 412 | Markdown | 57.999992 | 74 | 0.839806 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/include/omni/kit/syntheticdata/SyntheticData.h | // Copyright (c) 2020-2021, NVIDIA CORPORATION. All rights reserved.
//
// NVIDIA CORPORATION and its licensors retain all intellectual property
// and proprietary rights in and to this software, related documentation
// and any modifications thereto. Any use, reproduction, disclosure or
// distribution of this software and related documentation without an express
// license agreement from NVIDIA CORPORATION is strictly prohibited.
//
#pragma once
#include <carb/Interface.h>
#include <carb/sensors/SensorTypes.h>
#include <string>
namespace omni
{
// Forward declare deprecated viewport interface
namespace kit
{
class IViewportWindow;
};
namespace syntheticdata
{
/**
* Return code for functions that need to return information about a failure.
*/
enum class SyntheticDataResult : int32_t
{
eSuccess = 0, ///< Successful completion.
eFailure, ///< A general failure or error.
};
/**
* Structure which contains a list mapping instance Ids to prims with semantic labels that
* can be used to build bounding boxes for meshes with a common semantic class
*/
struct InstanceMapping
{
uint32_t uniqueId; ///< a unique ID for this instance mapping entry
std::string primPath; ///< the prim path for this instance mapping
uint16_t semanticId; ///< the semantic ID for this instance mapping
std::string semanticLabel; ///< the semantic class label for this mapping
std::vector<uint32_t> instanceIds; ///< a list of instance Ids that inherit this semantic label
void* metaData; ///< reserved for future use
};
struct SemanticInstanceMappingData
{
using TInstanceIndex = uint32_t;
using TInstanceToken = uint64_t;
static constexpr TInstanceToken invalidInstanceTypeToken = 0;
TInstanceIndex numInstances; ///< number of instances in the scene
TInstanceIndex minInstanceIndex; ///< minimum instance index
/// array containing the prim path token for every instances (from minInstanceIndex to minInstanceIndex + numInstances - 1)
TInstanceToken* instanceTokens;
using TSemanticIndex = uint16_t;
static constexpr TSemanticIndex invalidSemanticIndex = 0xFFFF;
using TSemanticToken = uint64_t;
static constexpr TSemanticToken invalidSemanticToken = 0;
using TSemanticTypeToken = uint64_t;
TSemanticIndex numSemantics; ///< number of semantic prim in the scene
TSemanticIndex minSemanticIndex; ///< minimum semantic index
/// array containing the prim path token for every semantic prim (from minSemanticIndex to minSemanticIndex + numSemantics
/// - 1)
TSemanticToken* semanticTokens;
using TTransform = float[4][4];
TTransform* semanticLocalTransforms; ///< transform from world to semantic prim local space
TTransform* semanticWorldTransforms; ///< transform from semantic prim local space to world
/// array of size numInstances containing the mapping from the instance index to its first semantic prim parent index
TSemanticIndex* instanceSemanticMap;
/// array of size numSemantics containing the mapping from the semantic index to its first semantic prim parent index
TSemanticIndex* semanticMap;
};
struct BoundingBox2DExtent
{
int32_t x_min; ///< left extent
int32_t y_min; ///< top extent
int32_t x_max; ///< right extent
int32_t y_max; ///< bottom extent
};
struct BoundingBox3DExtent
{
float x_min; ///< left extent (local coords)
float y_min; ///< top extent (local coords)
float z_min; ///< front extent (local coords)
float x_max; ///< right extent (local coords)
float y_max; ///< bottom extent (local coords)
float z_max; ///< back extent (local coords)
};
struct SyntheticData
{
CARB_PLUGIN_INTERFACE("omni::syntheticdata::SyntheticData", 0, 8)
/**
* Enable a specific sensor type on a viewport.
*
* @param type the type of sensor to enable
*
* @param viewportWindow the viewport to enable the sensor on
*
* @return false
*
* @deprecated removed since version 0.8
*/
bool(CARB_ABI* createSensor)(carb::sensors::SensorType type,
omni::kit::IViewportWindow* viewportWindow);
/**
* Disable a sensor on a viewport.
*
* @param type the type of sensor to disable
*
* @param viewportWindow the viewport to disable the sensor on
*
* @return false
*
* @deprecated removed since version 0.8
*/
bool(CARB_ABI* destroySensor)(carb::sensors::SensorType type,
omni::kit::IViewportWindow* viewportWindow);
/**
* Retrieve resource information on the sensor type of a specific viewport
*
* @param type the type of sensor to retrieve information from
*
* @param viewportWindow the viewport to retrieve information from
*
* @return dummy sensorInfo.
*
* @deprecated removed since version 0.8
*/
const carb::sensors::SensorInfo(CARB_ABI* getSensorInfo)(carb::sensors::SensorType type,
omni::kit::IViewportWindow* viewportWindow);
/**
* Get pointer the sensor data on the device
*
* @param type the type of sensor to retrieve data from
*
* @param viewportWindow the viewport you are retrieving data from
*
* @return nullptr
*
* @deprecated removed since version 0.8
*/
void*(CARB_ABI* getSensorDeviceData)(carb::sensors::SensorType type,
omni::kit::IViewportWindow* viewportWindow);
/**
* Get pointer the sensor data on the host
*
* @param type the type of sensor to retrieve data from
*
* @param viewportWindow the viewport you are retrieving data from
*
* @return nullptr
*
* @deprecated removed since version 0.8
*/
void*(CARB_ABI* getSensorHostData)(carb::sensors::SensorType type,
omni::kit::IViewportWindow* viewportWindow);
/**
* Get the number of sensors that are currently enabled on a viewport
*
* @param viewportWindow the viewport to return the count for
*
* @return 0
*
* @deprecated removed since version 0.8
*/
uint32_t(CARB_ABI* getSensorsCount)(omni::kit::IViewportWindow* viewportWindow);
/**
* Get a list of sensors bound to the viewport
*
* @param viewportWindow the viewport to retrieve sensors for
*
* @param sensorList an array of sensors in the viewport
*
* @param count number of sensors to retrieve for the given viewport
*
* @remarks It is up to the caller to allocate memory for the sensor
* list, using getSensorCount() to determind the list size.
* The call will fail if count is larger than the number of
* instance IDs at uri, or if instanceList is NULL.
*
* @return eFailure
*
* @deprecated removed since version 0.8
*/
SyntheticDataResult(CARB_ABI* getSensors)(omni::kit::IViewportWindow* viewportWindow,
carb::sensors::SensorType* sensorList,
uint32_t count);
/**
* Get instance ID count for an asset
*
* @param uri the object to retrieve the instance ID count for
*
* @return number of instance IDs listed at the uri
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
size_t(CARB_ABI* getInstanceIdsCount)(const char* uri);
/**
* Get instance IDs for an asset
*
* @param uri the object to retrieve the instance ID list for
*
* @param instanceList An array of instance IDs for the given uri
*
* @param count number of instance IDs to retrieve at the uri
*
* @remarks It is up to the caller to allocate memory for the instance
* list, using getInstanceIdsCount() to determind the list size.
* The call will fail if count is larger than the number of
* instance IDs at uri, or if instanceList is NULL.
*
* @return eSuccess if successful, eFailure otherwise
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
SyntheticDataResult(CARB_ABI* getInstanceIds)(const char* uri, uint32_t* instanceList, size_t count);
/**
* Get uri from an instance ID
*
* @param instanceId Instance ID to retrieve a uri for
*
* @return uri for the mesh specified by instanceId
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
const char*(CARB_ABI* getUriFromInstanceId)(uint32_t instanceId);
/**
* Get semantic ID for an asset
*
* @param type the semantic type to retrieve the semantic ID for
* @param data the semantic data to retrieve the semantic ID for
*
* @return semantic ID retrieved by the segmentation sensor
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
uint16_t(CARB_ABI* getSemanticIdFromData)(const char* type, const char* data);
/**
* Get semantic type for an asset
*
* @param semanticId the Id to retrieve the semantic type for
*
* @return semantic type retrieved by the segmentation sensor
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
const char*(CARB_ABI* getSemanticTypeFromId)(uint16_t semanticId);
/**
* Get semantic data for an asset
*
* @param semanticId the Id to retrieve the semantic class fors
*
* @return semantic data retrieved by the segmentation sensor
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
const char*(CARB_ABI* getSemanticDataFromId)(uint16_t semanticId);
/**
* Specify the semantic ID of bounding boxes to return
*
* @param semanticId only retreive bounding boxes with this id
*
* @remarks 0 is the default value and retrieves all bounding boxes
*
* @deprecated to be removed, will be replaced by OmniGraph node
*/
void(CARB_ABI* setBoundingBoxSemanticId)(uint16_t semanticId);
/**
* Specify the semantic type and data of bounding boxes to return
*
* @param type only retrieve bounding boxes with this semantic type
* @param data only retreive bounding boxes with this semantic data
*
* @remarks null string is the default value and retrieves all bounding boxes
*
* @deprecated to be removed, will be replaced by OmniGraph node
*/
void(CARB_ABI* setBoundingBoxSemantics)(const char* type, const char* data);
/**
* Build out a list that will containing mappings of instances and semantics
* to prims
*
* @param uri the root prim to derive instance mappings from
*
* @param instanceMappings a list to output instance mappings to
*
* @remarks It is expected that you will pass in an empty vector to be filled
* in with instance mappings. It is the caller's responsibility to make
* sure the vector is freed when it is no longer needed
*
* @deprecated to be removed, replaced by InstanceMapping AOVs
*/
size_t(CARB_ABI* getInstanceMappings)(const char* uri, std::vector<InstanceMapping>& instanceMappings);
/**
* Callback to update the pipeline internal data just before flushing the fabric
*
* @param stausdStageId id of the current USD stage for which the data has to be updated
*/
void(CARB_ABI* updatePipelineBeforeFabricFlush)(uint64_t usdStageId);
};
}
}
| 11,690 | C | 33.588757 | 127 | 0.661334 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/config/extension.toml | [package]
# Semantic Versioning is used: https://semver.org/
version = "0.2.4"
title = "Synthetic Data Sensors"
category = "Internal"
description="An extension for providing python access to the synthetic data sensors, useful helper functions and sensor visualization."
readme = "docs/README.md"
preview_image = "data/preview.png"
icon = "data/icon.png"
authors = ["NVIDIA"]
keywords = ["kit", "synthetic", "data", "visualization", "groundtruth", "sensor"]
changelog="docs/CHANGELOG.md"
[dependencies]
"omni.ui" = {}
"omni.kit.pip_archive" = {}
"omni.kit.commands" = {}
"omni.graph" = {}
"omni.graph.nodes" = {}
"omni.graph.action" = {}
"omni.usd" = {}
"omni.kit.async_engine" = {}
"omni.kit.viewport.utility" = {}
"omni.kit.viewport.menubar.core" = {optional = true}
[[python.module]]
name = "omni.syntheticdata"
# Watch the .ogn files for hot reloading (only for Python files)
[fswatcher.patterns]
include = ["*.ogn", "*.py"]
exclude = ["Ogn*Database.py"]
[[native.plugin]]
path = "bin/*.plugin"
recursive = false
[python.pipapi]
requirements = ["numpy", "Pillow"]
[[test]]
timeout = 1200
args = [
"--vulkan",
"--/app/content/emptyStageOnStart=true",
"--/app/asyncRendering=false",
"--/app/settings/flatCacheStageFrameHistoryCount=3",
"--/app/renderer/waitIdle=true",
"--/app/hydraEngine/waitIdle=true",
"--/rtx/post/aa/op=0",
"--/rtx-defaults/post/aa/op=0",
"--/rtx/hydra/enableSemanticSchema=true",
"--/rtx-defaults/hydra/enableSemanticSchema=true",
"--/rtx/raytracing/cached/enabled=false",
"--/rtx/raytracing/lightcache/spatialCache/enabled=false",
"--/syntheticdata/sensors/perSubsetSegmentation=true",
"--/renderer/debug/aftermath/enabled=false"
]
dependencies = [
"omni.kit.uiapp",
"omni.kit.window.extensions",
"omni.kit.commands",
"omni.hydra.rtx",
"omni.kit.hydra_texture",
"omni.kit.window.viewport"
]
stdoutFailPatterns.exclude = [
"*road_base_omniue4.mdl*",
"*DrivesimPBR.mdl*",
"*omni.graph.core*",
"*omni::graph::core*",
"*omni.kit.app.impl*",
"*__OgnSdgInstanceMappingCache__*",
"*Failed to delete file 'C:*",
"*ModuleNotFoundError: No module named 'omni.kit.material'*", # OM-55405
"*OgnSdOnNewFrame : frames * discarded*",
]
pythonTests.include = [
"omni.syntheticdata.tests.helpers.*",
"omni.syntheticdata.tests.sensors.*",
"omni.syntheticdata.tests.visualize.*"
]
pythonTests.exclude = [
"omni.syntheticdata.tests.sensors.test_stage_manipulation.*",
"omni.syntheticdata.tests.visualize.test_flattener*"
]
# pythonTests.unreliable = [
# "*test_cross_correspondence", # OM-55199
# "*test_swh_frame_number", # OM-55199
# "*test_reduce_occlusion", # OM-55199
# "*test_semantic_filter_world_and_sphere_test", # OM-55531
# "*test_sync_idle", # OM-58580
# "*test_golden_image", # OM-58580
# "*test_merge_sensors", # OM-58999
# ]
[[test]]
name="pipeline"
timeout = 1200
args = [
"--/app/content/emptyStageOnStart=true",
"--/app/asyncRendering=false",
"--/app/settings/flatCacheStageFrameHistoryCount=3",
"--no-window",
"--/rtx/post/aa/op=0",
"--/rtx-defaults/post/aa/op=0",
"--/rtx/raytracing/cached/enabled=false",
"--/rtx/raytracing/lightcache/spatialCache/enabled=false",
"--/rtx/pathtracing/cached/enabled=false",
"--/rtx/pathtracing/lightcache/spatialCache/enabled=false",
"--/renderer/debug/aftermath/enabled=false"
]
dependencies = [
"omni.hydra.rtx",
"omni.kit.hydra_texture"
]
stdoutFailPatterns.exclude = [
"*road_base_omniue4.mdl*",
"*DrivesimPBR.mdl*",
"*omni.graph.core*",
"*omni::graph::core*",
"*omni.kit.app.impl*",
"*__OgnSdgInstanceMappingCache__*",
"*Failed to delete file 'C:*",
"*ModuleNotFoundError: No module named 'omni.kit.material'*", # OM-55405
]
pythonTests.include = [
"omni.syntheticdata.tests.pipeline.*"
]
[[test]]
name="graph"
timeout = 1200
args = [
"--/app/content/emptyStageOnStart=true",
"--/app/asyncRendering=false",
"--/app/settings/flatCacheStageFrameHistoryCount=3",
"--no-window",
"--/rtx/post/aa/op=0",
"--/rtx-defaults/post/aa/op=0",
"--/rtx/raytracing/cached/enabled=false",
"--/rtx/raytracing/lightcache/spatialCache/enabled=false",
"--/rtx/pathtracing/cached/enabled=false",
"--/rtx/pathtracing/lightcache/spatialCache/enabled=false",
"--/renderer/debug/aftermath/enabled=false"
]
dependencies = [
"omni.hydra.rtx",
"omni.kit.hydra_texture"
]
stdoutFailPatterns.exclude = [
"*road_base_omniue4.mdl*",
"*DrivesimPBR.mdl*",
"*omni.graph.core*",
"*omni::graph::core*",
"*omni.kit.app.impl*",
"*__OgnSdgInstanceMappingCache__*",
"*Failed to delete file 'C:*",
"*ModuleNotFoundError: No module named 'omni.kit.material'*", # OM-55405
]
pythonTests.include = [
"omni.syntheticdata.tests.graph.*"
]
[[test]]
name="flattener"
timeout = 600
args = [
"--vulkan",
"--/app/content/emptyStageOnStart=true",
"--/app/asyncRendering=false",
"--/app/settings/flatCacheStageFrameHistoryCount=3",
"--/app/renderer/waitIdle=true",
"--/app/hydraEngine/waitIdle=true",
"--/renderer/multiGpu/enabled=false",
"--/renderer/multiGpu/maxGpuCount=1",
"--/rtx/post/aa/op=0",
"--/rtx-defaults/post/aa/op=0",
"--/rtx/hydra/enableSemanticSchema=true",
"--/rtx-defaults/hydra/enableSemanticSchema=true",
"--/rtx/materialflattener/disableTileBudget=true",
"--/rtx/materialflattener/enabled=true",
"--/rtx/materialflattener/numTexelsPerWorldUnit=32",
"--/rtx/materialflattener/enableSegmentation=true",
"--/rtx/virtualtexture/fixedMemoryPoolChunkSizeMB=32",
"--/rtx/raytracing/cached/enabled=false",
"--/rtx/raytracing/lightcache/spatialCache/enabled=false",
"--/syntheticdata/sensors/perSubsetSegmentation=true",
"--/renderer/debug/aftermath/enabled=false"
]
dependencies = [
"omni.kit.uiapp",
"omni.kit.window.extensions",
"omni.kit.commands",
"omni.hydra.rtx",
"omni.kit.hydra_texture",
"omni.kit.window.viewport"
]
stdoutFailPatterns.exclude = [
"*road_base_omniue4.mdl*",
"*DrivesimPBR.mdl*",
"*omni.graph.core*",
"*omni::graph::core*",
"*omni.kit.app.impl*",
"*__OgnSdgInstanceMappingCache__*",
"*Failed to delete file 'C:*",
"*ModuleNotFoundError: No module named 'omni.kit.material'*", # OM-55405
]
pythonTests.include = [
"omni.syntheticdata.tests.visualize.test_flattener*"
]
pythonTests.unreliable = [
"omni.syntheticdata.tests.visualize.test_flattener*" # OM-55405
]
| 6,615 | TOML | 28.801802 | 135 | 0.660317 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/__init__.py | from . import _syntheticdata
from .scripts.extension import *
from .ogn import *
| 81 | Python | 19.499995 | 32 | 0.765432 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdTestRenderProductCameraDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdTestRenderProductCamera
Synthetic Data node to test the renderProduct camera pipeline
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdTestRenderProductCameraDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdTestRenderProductCamera
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cameraApertureOffset
inputs.cameraApertureSize
inputs.cameraFStop
inputs.cameraFisheyeParams
inputs.cameraFocalLength
inputs.cameraFocusDistance
inputs.cameraModel
inputs.cameraNearFar
inputs.cameraProjection
inputs.cameraViewTransform
inputs.exec
inputs.height
inputs.metersPerSceneUnit
inputs.renderProductCameraPath
inputs.renderProductResolution
inputs.stage
inputs.swhFrameNumber
inputs.traceError
inputs.width
Outputs:
outputs.test
Predefined Tokens:
tokens.simulation
tokens.postRender
tokens.onDemand
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cameraApertureOffset', 'float2', 0, None, 'Camera horizontal and vertical aperture offset', {}, True, [0.0, 0.0], False, ''),
('inputs:cameraApertureSize', 'float2', 0, None, 'Camera horizontal and vertical aperture', {}, True, [0.0, 0.0], False, ''),
('inputs:cameraFStop', 'float', 0, None, 'Camera fStop', {}, True, 0.0, False, ''),
('inputs:cameraFisheyeParams', 'float[]', 0, None, 'Camera fisheye projection parameters', {}, True, [], False, ''),
('inputs:cameraFocalLength', 'float', 0, None, 'Camera focal length', {}, True, 0.0, False, ''),
('inputs:cameraFocusDistance', 'float', 0, None, 'Camera focus distance', {}, True, 0.0, False, ''),
('inputs:cameraModel', 'int', 0, None, 'Camera model (pinhole or fisheye models)', {}, True, 0, False, ''),
('inputs:cameraNearFar', 'float2', 0, None, 'Camera near/far clipping range', {}, True, [0.0, 0.0], False, ''),
('inputs:cameraProjection', 'matrix4d', 0, None, 'Camera projection matrix', {}, True, [[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]], False, ''),
('inputs:cameraViewTransform', 'matrix4d', 0, None, 'Camera view matrix', {}, True, [[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]], False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:height', 'uint', 0, None, 'Height of the frame', {}, True, 0, False, ''),
('inputs:metersPerSceneUnit', 'float', 0, None, 'Scene units to meters scale', {}, True, 0.0, False, ''),
('inputs:renderProductCameraPath', 'token', 0, None, 'RenderProduct camera prim path', {}, True, '', False, ''),
('inputs:renderProductResolution', 'int2', 0, None, 'RenderProduct resolution', {}, True, [0, 0], False, ''),
('inputs:stage', 'token', 0, None, 'Stage in {simulation, postrender, ondemand}', {}, True, '', False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('inputs:traceError', 'bool', 0, None, 'If true print an error message when the frame numbers are out-of-sync', {ogn.MetadataKeys.DEFAULT: 'false'}, True, False, False, ''),
('inputs:width', 'uint', 0, None, 'Width of the frame', {}, True, 0, False, ''),
('outputs:test', 'bool', 0, None, 'Test value : false if failed', {}, True, None, False, ''),
])
class tokens:
simulation = "simulation"
postRender = "postRender"
onDemand = "onDemand"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.cameraProjection = og.Database.ROLE_MATRIX
role_data.inputs.cameraViewTransform = og.Database.ROLE_MATRIX
role_data.inputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cameraApertureOffset", "cameraApertureSize", "cameraFStop", "cameraFocalLength", "cameraFocusDistance", "cameraModel", "cameraNearFar", "cameraProjection", "cameraViewTransform", "exec", "height", "metersPerSceneUnit", "renderProductCameraPath", "renderProductResolution", "stage", "swhFrameNumber", "traceError", "width", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cameraApertureOffset, self._attributes.cameraApertureSize, self._attributes.cameraFStop, self._attributes.cameraFocalLength, self._attributes.cameraFocusDistance, self._attributes.cameraModel, self._attributes.cameraNearFar, self._attributes.cameraProjection, self._attributes.cameraViewTransform, self._attributes.exec, self._attributes.height, self._attributes.metersPerSceneUnit, self._attributes.renderProductCameraPath, self._attributes.renderProductResolution, self._attributes.stage, self._attributes.swhFrameNumber, self._attributes.traceError, self._attributes.width]
self._batchedReadValues = [[0.0, 0.0], [0.0, 0.0], 0.0, 0.0, 0.0, 0, [0.0, 0.0], [1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0], [1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0], None, 0, 0.0, "", [0, 0], "", 0, False, 0]
@property
def cameraFisheyeParams(self):
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
return data_view.get()
@cameraFisheyeParams.setter
def cameraFisheyeParams(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.cameraFisheyeParams)
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
data_view.set(value)
self.cameraFisheyeParams_size = data_view.get_array_size()
@property
def cameraApertureOffset(self):
return self._batchedReadValues[0]
@cameraApertureOffset.setter
def cameraApertureOffset(self, value):
self._batchedReadValues[0] = value
@property
def cameraApertureSize(self):
return self._batchedReadValues[1]
@cameraApertureSize.setter
def cameraApertureSize(self, value):
self._batchedReadValues[1] = value
@property
def cameraFStop(self):
return self._batchedReadValues[2]
@cameraFStop.setter
def cameraFStop(self, value):
self._batchedReadValues[2] = value
@property
def cameraFocalLength(self):
return self._batchedReadValues[3]
@cameraFocalLength.setter
def cameraFocalLength(self, value):
self._batchedReadValues[3] = value
@property
def cameraFocusDistance(self):
return self._batchedReadValues[4]
@cameraFocusDistance.setter
def cameraFocusDistance(self, value):
self._batchedReadValues[4] = value
@property
def cameraModel(self):
return self._batchedReadValues[5]
@cameraModel.setter
def cameraModel(self, value):
self._batchedReadValues[5] = value
@property
def cameraNearFar(self):
return self._batchedReadValues[6]
@cameraNearFar.setter
def cameraNearFar(self, value):
self._batchedReadValues[6] = value
@property
def cameraProjection(self):
return self._batchedReadValues[7]
@cameraProjection.setter
def cameraProjection(self, value):
self._batchedReadValues[7] = value
@property
def cameraViewTransform(self):
return self._batchedReadValues[8]
@cameraViewTransform.setter
def cameraViewTransform(self, value):
self._batchedReadValues[8] = value
@property
def exec(self):
return self._batchedReadValues[9]
@exec.setter
def exec(self, value):
self._batchedReadValues[9] = value
@property
def height(self):
return self._batchedReadValues[10]
@height.setter
def height(self, value):
self._batchedReadValues[10] = value
@property
def metersPerSceneUnit(self):
return self._batchedReadValues[11]
@metersPerSceneUnit.setter
def metersPerSceneUnit(self, value):
self._batchedReadValues[11] = value
@property
def renderProductCameraPath(self):
return self._batchedReadValues[12]
@renderProductCameraPath.setter
def renderProductCameraPath(self, value):
self._batchedReadValues[12] = value
@property
def renderProductResolution(self):
return self._batchedReadValues[13]
@renderProductResolution.setter
def renderProductResolution(self, value):
self._batchedReadValues[13] = value
@property
def stage(self):
return self._batchedReadValues[14]
@stage.setter
def stage(self, value):
self._batchedReadValues[14] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[15]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[15] = value
@property
def traceError(self):
return self._batchedReadValues[16]
@traceError.setter
def traceError(self, value):
self._batchedReadValues[16] = value
@property
def width(self):
return self._batchedReadValues[17]
@width.setter
def width(self, value):
self._batchedReadValues[17] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"test", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def test(self):
value = self._batchedWriteValues.get(self._attributes.test)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.test)
return data_view.get()
@test.setter
def test(self, value):
self._batchedWriteValues[self._attributes.test] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdTestRenderProductCameraDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdTestRenderProductCameraDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdTestRenderProductCameraDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 14,809 | Python | 45.137072 | 636 | 0.628672 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostSemantic3dBoundingBoxFilterDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostSemantic3dBoundingBoxFilter
Synthetic Data node to cull the semantic 3d bounding boxes.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdPostSemantic3dBoundingBoxFilterDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostSemantic3dBoundingBoxFilter
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.gpu
inputs.instanceMappingInfoSDPtr
inputs.metersPerSceneUnit
inputs.rp
inputs.sdSemBBox3dCamCornersCudaPtr
inputs.sdSemBBoxInfosCudaPtr
inputs.viewportNearFar
Outputs:
outputs.exec
outputs.sdSemBBoxInfosCudaPtr
Predefined Tokens:
tokens.SemanticBoundingBox3DInfosSD
tokens.SemanticBoundingBox3DFilterInfosSD
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:instanceMappingInfoSDPtr', 'uint64', 0, None, 'uint buffer pointer containing the following information : [numInstances, minInstanceId, numSemantics, minSemanticId, numProtoSemantic]', {}, True, 0, False, ''),
('inputs:metersPerSceneUnit', 'float', 0, None, 'Scene units to meters scale', {ogn.MetadataKeys.DEFAULT: '0.01'}, True, 0.01, False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'Pointer to render product for this view', {}, True, 0, False, ''),
('inputs:sdSemBBox3dCamCornersCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the projection of the 3d bounding boxes on the camera plane represented as a float3=(u,v,z,a) for each bounding box corners', {}, True, 0, False, ''),
('inputs:sdSemBBoxInfosCudaPtr', 'uint64', 0, None, 'Cuda buffer containing valid bounding boxes infos', {}, True, 0, False, ''),
('inputs:viewportNearFar', 'float2', 0, None, 'near and far plane (in scene units) used to clip the 3d bounding boxes.', {ogn.MetadataKeys.DEFAULT: '[0.0, -1.0]'}, True, [0.0, -1.0], False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:sdSemBBoxInfosCudaPtr', 'uint64', 0, None, 'Cuda buffer containing valid bounding boxes infos', {}, True, None, False, ''),
])
class tokens:
SemanticBoundingBox3DInfosSD = "SemanticBoundingBox3DInfosSD"
SemanticBoundingBox3DFilterInfosSD = "SemanticBoundingBox3DFilterInfosSD"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "gpu", "instanceMappingInfoSDPtr", "metersPerSceneUnit", "rp", "sdSemBBox3dCamCornersCudaPtr", "sdSemBBoxInfosCudaPtr", "viewportNearFar", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.gpu, self._attributes.instanceMappingInfoSDPtr, self._attributes.metersPerSceneUnit, self._attributes.rp, self._attributes.sdSemBBox3dCamCornersCudaPtr, self._attributes.sdSemBBoxInfosCudaPtr, self._attributes.viewportNearFar]
self._batchedReadValues = [None, 0, 0, 0.01, 0, 0, 0, [0.0, -1.0]]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def gpu(self):
return self._batchedReadValues[1]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[1] = value
@property
def instanceMappingInfoSDPtr(self):
return self._batchedReadValues[2]
@instanceMappingInfoSDPtr.setter
def instanceMappingInfoSDPtr(self, value):
self._batchedReadValues[2] = value
@property
def metersPerSceneUnit(self):
return self._batchedReadValues[3]
@metersPerSceneUnit.setter
def metersPerSceneUnit(self, value):
self._batchedReadValues[3] = value
@property
def rp(self):
return self._batchedReadValues[4]
@rp.setter
def rp(self, value):
self._batchedReadValues[4] = value
@property
def sdSemBBox3dCamCornersCudaPtr(self):
return self._batchedReadValues[5]
@sdSemBBox3dCamCornersCudaPtr.setter
def sdSemBBox3dCamCornersCudaPtr(self, value):
self._batchedReadValues[5] = value
@property
def sdSemBBoxInfosCudaPtr(self):
return self._batchedReadValues[6]
@sdSemBBoxInfosCudaPtr.setter
def sdSemBBoxInfosCudaPtr(self, value):
self._batchedReadValues[6] = value
@property
def viewportNearFar(self):
return self._batchedReadValues[7]
@viewportNearFar.setter
def viewportNearFar(self, value):
self._batchedReadValues[7] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "sdSemBBoxInfosCudaPtr", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def sdSemBBoxInfosCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.sdSemBBoxInfosCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdSemBBoxInfosCudaPtr)
return data_view.get()
@sdSemBBoxInfosCudaPtr.setter
def sdSemBBoxInfosCudaPtr(self, value):
self._batchedWriteValues[self._attributes.sdSemBBoxInfosCudaPtr] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostSemantic3dBoundingBoxFilterDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostSemantic3dBoundingBoxFilterDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostSemantic3dBoundingBoxFilterDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 10,643 | Python | 47.825688 | 309 | 0.653575 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdTestStageManipulationScenariiDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdTestStageManipulationScenarii
Synthetic Data test node applying randomly some predefined stage manipulation scenarii
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import traceback
import sys
class OgnSdTestStageManipulationScenariiDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdTestStageManipulationScenarii
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.randomSeed
inputs.worldPrimPath
State:
state.frameNumber
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:randomSeed', 'int', 0, None, 'Random seed', {}, True, 0, False, ''),
('inputs:worldPrimPath', 'token', 0, None, 'Path of the world prim : contains every modifiable prim, cannot be modified', {}, True, '', False, ''),
('state:frameNumber', 'uint64', 0, None, 'Current frameNumber (number of invocations)', {ogn.MetadataKeys.DEFAULT: '0'}, True, 0, False, ''),
])
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"randomSeed", "worldPrimPath", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.randomSeed, self._attributes.worldPrimPath]
self._batchedReadValues = [0, ""]
@property
def randomSeed(self):
return self._batchedReadValues[0]
@randomSeed.setter
def randomSeed(self, value):
self._batchedReadValues[0] = value
@property
def worldPrimPath(self):
return self._batchedReadValues[1]
@worldPrimPath.setter
def worldPrimPath(self, value):
self._batchedReadValues[1] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = { }
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
@property
def frameNumber(self):
data_view = og.AttributeValueHelper(self._attributes.frameNumber)
return data_view.get()
@frameNumber.setter
def frameNumber(self, value):
data_view = og.AttributeValueHelper(self._attributes.frameNumber)
data_view.set(value)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdTestStageManipulationScenariiDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdTestStageManipulationScenariiDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdTestStageManipulationScenariiDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
class abi:
"""Class defining the ABI interface for the node type"""
@staticmethod
def get_node_type():
get_node_type_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'get_node_type', None)
if callable(get_node_type_function):
return get_node_type_function()
return 'omni.syntheticdata.SdTestStageManipulationScenarii'
@staticmethod
def compute(context, node):
try:
per_node_data = OgnSdTestStageManipulationScenariiDatabase.PER_NODE_DATA[node.node_id()]
db = per_node_data.get('_db')
if db is None:
db = OgnSdTestStageManipulationScenariiDatabase(node)
per_node_data['_db'] = db
except:
db = OgnSdTestStageManipulationScenariiDatabase(node)
try:
compute_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'compute', None)
if callable(compute_function) and compute_function.__code__.co_argcount > 1:
return compute_function(context, node)
db.inputs._prefetch()
db.inputs._setting_locked = True
with og.in_compute():
return OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS.compute(db)
except Exception as error:
stack_trace = "".join(traceback.format_tb(sys.exc_info()[2].tb_next))
db.log_error(f'Assertion raised in compute - {error}\n{stack_trace}', add_context=False)
finally:
db.inputs._setting_locked = False
db.outputs._commit()
return False
@staticmethod
def initialize(context, node):
OgnSdTestStageManipulationScenariiDatabase._initialize_per_node_data(node)
initialize_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'initialize', None)
if callable(initialize_function):
initialize_function(context, node)
@staticmethod
def release(node):
release_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'release', None)
if callable(release_function):
release_function(node)
OgnSdTestStageManipulationScenariiDatabase._release_per_node_data(node)
@staticmethod
def update_node_version(context, node, old_version, new_version):
update_node_version_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'update_node_version', None)
if callable(update_node_version_function):
return update_node_version_function(context, node, old_version, new_version)
return False
@staticmethod
def initialize_type(node_type):
initialize_type_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'initialize_type', None)
needs_initializing = True
if callable(initialize_type_function):
needs_initializing = initialize_type_function(node_type)
if needs_initializing:
node_type.set_metadata(ogn.MetadataKeys.EXTENSION, "omni.syntheticdata")
node_type.set_metadata(ogn.MetadataKeys.CATEGORIES, "graph:simulation,internal:test")
node_type.set_metadata(ogn.MetadataKeys.DESCRIPTION, "Synthetic Data test node applying randomly some predefined stage manipulation scenarii")
node_type.set_metadata(ogn.MetadataKeys.EXCLUSIONS, "tests")
node_type.set_metadata(ogn.MetadataKeys.LANGUAGE, "Python")
OgnSdTestStageManipulationScenariiDatabase.INTERFACE.add_to_node_type(node_type)
node_type.set_has_state(True)
@staticmethod
def on_connection_type_resolve(node):
on_connection_type_resolve_function = getattr(OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS, 'on_connection_type_resolve', None)
if callable(on_connection_type_resolve_function):
on_connection_type_resolve_function(node)
NODE_TYPE_CLASS = None
GENERATOR_VERSION = (1, 17, 2)
TARGET_VERSION = (2, 65, 4)
@staticmethod
def register(node_type_class):
OgnSdTestStageManipulationScenariiDatabase.NODE_TYPE_CLASS = node_type_class
og.register_node_type(OgnSdTestStageManipulationScenariiDatabase.abi, 1)
@staticmethod
def deregister():
og.deregister_node_type("omni.syntheticdata.SdTestStageManipulationScenarii")
| 10,571 | Python | 52.664974 | 158 | 0.660865 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdInstanceMappingDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdInstanceMapping
Synthetic Data node to expose the scene instances semantic hierarchy information
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdInstanceMappingDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdInstanceMapping
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.lazy
inputs.renderResults
inputs.swhFrameNumber
Outputs:
outputs.exec
outputs.sdIMInstanceSemanticMap
outputs.sdIMInstanceTokens
outputs.sdIMMaxSemanticHierarchyDepth
outputs.sdIMMinInstanceIndex
outputs.sdIMMinSemanticIndex
outputs.sdIMNumInstances
outputs.sdIMNumSemanticTokens
outputs.sdIMNumSemantics
outputs.sdIMSemanticLocalTransform
outputs.sdIMSemanticTokenMap
outputs.sdIMSemanticWorldTransform
outputs.swhFrameNumber
Predefined Tokens:
tokens.InstanceMappingInfoSDhost
tokens.InstanceMapSDhost
tokens.SemanticLabelTokenSDhost
tokens.InstancePrimTokenSDhost
tokens.SemanticLocalTransformSDhost
tokens.SemanticWorldTransformSDhost
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:lazy', 'bool', 0, None, 'Compute outputs only when connected to a downstream node', {ogn.MetadataKeys.DEFAULT: 'true'}, True, True, False, ''),
('inputs:renderResults', 'uint64', 0, None, 'Render results pointer', {}, True, 0, False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:sdIMInstanceSemanticMap', 'uchar[]', 0, None, 'Raw array of uint16_t of size sdIMNumInstances*sdIMMaxSemanticHierarchyDepth containing the mapping from the instances index to their inherited semantic entities', {}, True, None, False, ''),
('outputs:sdIMInstanceTokens', 'token[]', 0, None, 'Instance array containing the token for every instances', {}, True, None, False, ''),
('outputs:sdIMMaxSemanticHierarchyDepth', 'uint', 0, None, 'Maximal number of semantic entities inherited by an instance', {}, True, None, False, ''),
('outputs:sdIMMinInstanceIndex', 'uint', 0, None, 'Instance id of the first instance in the instance arrays', {}, True, None, False, ''),
('outputs:sdIMMinSemanticIndex', 'uint', 0, None, 'Semantic id of the first semantic entity in the semantic arrays', {}, True, None, False, ''),
('outputs:sdIMNumInstances', 'uint', 0, None, 'Number of instances in the instance arrays', {}, True, None, False, ''),
('outputs:sdIMNumSemanticTokens', 'uint', 0, None, 'Number of semantics token including the semantic entity path, the semantic entity types and if the number of semantic types is greater than one a ', {}, True, None, False, ''),
('outputs:sdIMNumSemantics', 'uint', 0, None, 'Number of semantic entities in the semantic arrays', {}, True, None, False, ''),
('outputs:sdIMSemanticLocalTransform', 'float[]', 0, None, 'Semantic array of 4x4 float matrices containing the transform from world to local space for every semantic entity', {}, True, None, False, ''),
('outputs:sdIMSemanticTokenMap', 'token[]', 0, None, 'Semantic array of token of size numSemantics * numSemanticTypes containing the mapping from the semantic entities to the semantic entity path and semantic types', {}, True, None, False, ''),
('outputs:sdIMSemanticWorldTransform', 'float[]', 0, None, 'Semantic array of 4x4 float matrices containing the transform from local to world space for every semantic entity', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
class tokens:
InstanceMappingInfoSDhost = "InstanceMappingInfoSDhost"
InstanceMapSDhost = "InstanceMapSDhost"
SemanticLabelTokenSDhost = "SemanticLabelTokenSDhost"
InstancePrimTokenSDhost = "InstancePrimTokenSDhost"
SemanticLocalTransformSDhost = "SemanticLocalTransformSDhost"
SemanticWorldTransformSDhost = "SemanticWorldTransformSDhost"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "lazy", "renderResults", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.lazy, self._attributes.renderResults, self._attributes.swhFrameNumber]
self._batchedReadValues = [None, True, 0, 0]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def lazy(self):
return self._batchedReadValues[1]
@lazy.setter
def lazy(self, value):
self._batchedReadValues[1] = value
@property
def renderResults(self):
return self._batchedReadValues[2]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[2] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[3]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "sdIMMaxSemanticHierarchyDepth", "sdIMMinInstanceIndex", "sdIMMinSemanticIndex", "sdIMNumInstances", "sdIMNumSemanticTokens", "sdIMNumSemantics", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self.sdIMInstanceSemanticMap_size = None
self.sdIMInstanceTokens_size = None
self.sdIMSemanticLocalTransform_size = None
self.sdIMSemanticTokenMap_size = None
self.sdIMSemanticWorldTransform_size = None
self._batchedWriteValues = { }
@property
def sdIMInstanceSemanticMap(self):
data_view = og.AttributeValueHelper(self._attributes.sdIMInstanceSemanticMap)
return data_view.get(reserved_element_count=self.sdIMInstanceSemanticMap_size)
@sdIMInstanceSemanticMap.setter
def sdIMInstanceSemanticMap(self, value):
data_view = og.AttributeValueHelper(self._attributes.sdIMInstanceSemanticMap)
data_view.set(value)
self.sdIMInstanceSemanticMap_size = data_view.get_array_size()
@property
def sdIMInstanceTokens(self):
data_view = og.AttributeValueHelper(self._attributes.sdIMInstanceTokens)
return data_view.get(reserved_element_count=self.sdIMInstanceTokens_size)
@sdIMInstanceTokens.setter
def sdIMInstanceTokens(self, value):
data_view = og.AttributeValueHelper(self._attributes.sdIMInstanceTokens)
data_view.set(value)
self.sdIMInstanceTokens_size = data_view.get_array_size()
@property
def sdIMSemanticLocalTransform(self):
data_view = og.AttributeValueHelper(self._attributes.sdIMSemanticLocalTransform)
return data_view.get(reserved_element_count=self.sdIMSemanticLocalTransform_size)
@sdIMSemanticLocalTransform.setter
def sdIMSemanticLocalTransform(self, value):
data_view = og.AttributeValueHelper(self._attributes.sdIMSemanticLocalTransform)
data_view.set(value)
self.sdIMSemanticLocalTransform_size = data_view.get_array_size()
@property
def sdIMSemanticTokenMap(self):
data_view = og.AttributeValueHelper(self._attributes.sdIMSemanticTokenMap)
return data_view.get(reserved_element_count=self.sdIMSemanticTokenMap_size)
@sdIMSemanticTokenMap.setter
def sdIMSemanticTokenMap(self, value):
data_view = og.AttributeValueHelper(self._attributes.sdIMSemanticTokenMap)
data_view.set(value)
self.sdIMSemanticTokenMap_size = data_view.get_array_size()
@property
def sdIMSemanticWorldTransform(self):
data_view = og.AttributeValueHelper(self._attributes.sdIMSemanticWorldTransform)
return data_view.get(reserved_element_count=self.sdIMSemanticWorldTransform_size)
@sdIMSemanticWorldTransform.setter
def sdIMSemanticWorldTransform(self, value):
data_view = og.AttributeValueHelper(self._attributes.sdIMSemanticWorldTransform)
data_view.set(value)
self.sdIMSemanticWorldTransform_size = data_view.get_array_size()
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def sdIMMaxSemanticHierarchyDepth(self):
value = self._batchedWriteValues.get(self._attributes.sdIMMaxSemanticHierarchyDepth)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdIMMaxSemanticHierarchyDepth)
return data_view.get()
@sdIMMaxSemanticHierarchyDepth.setter
def sdIMMaxSemanticHierarchyDepth(self, value):
self._batchedWriteValues[self._attributes.sdIMMaxSemanticHierarchyDepth] = value
@property
def sdIMMinInstanceIndex(self):
value = self._batchedWriteValues.get(self._attributes.sdIMMinInstanceIndex)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdIMMinInstanceIndex)
return data_view.get()
@sdIMMinInstanceIndex.setter
def sdIMMinInstanceIndex(self, value):
self._batchedWriteValues[self._attributes.sdIMMinInstanceIndex] = value
@property
def sdIMMinSemanticIndex(self):
value = self._batchedWriteValues.get(self._attributes.sdIMMinSemanticIndex)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdIMMinSemanticIndex)
return data_view.get()
@sdIMMinSemanticIndex.setter
def sdIMMinSemanticIndex(self, value):
self._batchedWriteValues[self._attributes.sdIMMinSemanticIndex] = value
@property
def sdIMNumInstances(self):
value = self._batchedWriteValues.get(self._attributes.sdIMNumInstances)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdIMNumInstances)
return data_view.get()
@sdIMNumInstances.setter
def sdIMNumInstances(self, value):
self._batchedWriteValues[self._attributes.sdIMNumInstances] = value
@property
def sdIMNumSemanticTokens(self):
value = self._batchedWriteValues.get(self._attributes.sdIMNumSemanticTokens)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdIMNumSemanticTokens)
return data_view.get()
@sdIMNumSemanticTokens.setter
def sdIMNumSemanticTokens(self, value):
self._batchedWriteValues[self._attributes.sdIMNumSemanticTokens] = value
@property
def sdIMNumSemantics(self):
value = self._batchedWriteValues.get(self._attributes.sdIMNumSemantics)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdIMNumSemantics)
return data_view.get()
@sdIMNumSemantics.setter
def sdIMNumSemantics(self, value):
self._batchedWriteValues[self._attributes.sdIMNumSemantics] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdInstanceMappingDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdInstanceMappingDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdInstanceMappingDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 17,311 | Python | 49.034682 | 256 | 0.658714 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostRenderVarDisplayTextureDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostRenderVarDisplayTexture
Synthetic Data node to copy the input aov texture into the corresponding visualization texture
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdPostRenderVarDisplayTextureDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostRenderVarDisplayTexture
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cameraFisheyeParams
inputs.cameraModel
inputs.cameraNearFar
inputs.exec
inputs.gpu
inputs.instanceMapSDCudaPtr
inputs.instanceMappingInfoSDPtr
inputs.metersPerSceneUnit
inputs.mode
inputs.parameters
inputs.renderVar
inputs.renderVarDisplay
inputs.rp
inputs.sdDisplayHeight
inputs.sdDisplayWidth
inputs.sdSemBBox3dCamCornersCudaPtr
inputs.sdSemBBox3dCamExtentCudaPtr
inputs.sdSemBBoxExtentCudaPtr
inputs.sdSemBBoxInfosCudaPtr
inputs.semanticLabelTokenSDCudaPtr
inputs.semanticMapSDCudaPtr
inputs.semanticPrimTokenSDCudaPtr
inputs.semanticWorldTransformSDCudaPtr
inputs.swhFrameNumber
Outputs:
outputs.cudaPtr
outputs.exec
outputs.format
outputs.height
outputs.renderVarDisplay
outputs.width
Predefined Tokens:
tokens.LdrColorSD
tokens.Camera3dPositionSD
tokens.DistanceToImagePlaneSD
tokens.DistanceToCameraSD
tokens.InstanceSegmentationSD
tokens.SemanticSegmentationSD
tokens.NormalSD
tokens.TargetMotionSD
tokens.BoundingBox2DTightSD
tokens.BoundingBox2DLooseSD
tokens.BoundingBox3DSD
tokens.OcclusionSD
tokens.TruncationSD
tokens.CrossCorrespondenceSD
tokens.SemanticBoundingBox2DExtentTightSD
tokens.SemanticBoundingBox2DInfosTightSD
tokens.SemanticBoundingBox2DExtentLooseSD
tokens.SemanticBoundingBox2DInfosLooseSD
tokens.SemanticBoundingBox3DExtentSD
tokens.SemanticBoundingBox3DInfosSD
tokens.SemanticBoundingBox3DCamCornersSD
tokens.SemanticBoundingBox3DDisplayAxesSD
tokens.autoMode
tokens.colorMode
tokens.scaled3dVectorMode
tokens.clippedValueMode
tokens.normalized3dVectorMode
tokens.segmentationMapMode
tokens.instanceMapMode
tokens.semanticPathMode
tokens.semanticLabelMode
tokens.semanticBoundingBox2dMode
tokens.rawBoundingBox2dMode
tokens.semanticProjBoundingBox3dMode
tokens.semanticBoundingBox3dMode
tokens.rawBoundingBox3dMode
tokens.pinhole
tokens.perspective
tokens.orthographic
tokens.fisheyePolynomial
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cameraFisheyeParams', 'float[]', 0, None, 'Camera fisheye projection parameters', {}, True, [], False, ''),
('inputs:cameraModel', 'int', 0, None, 'Camera model (pinhole or fisheye models)', {}, True, 0, False, ''),
('inputs:cameraNearFar', 'float2', 0, None, 'Camera near/far clipping range', {}, True, [0.0, 0.0], False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:instanceMapSDCudaPtr', 'uint64', 0, None, 'cuda uint16_t buffer pointer of size numInstances containing the instance parent semantic index', {}, True, 0, False, ''),
('inputs:instanceMappingInfoSDPtr', 'uint64', 0, None, 'uint buffer pointer containing the following information : [numInstances, minInstanceId, numSemantics, minSemanticId, numProtoSemantic]', {}, True, 0, False, ''),
('inputs:metersPerSceneUnit', 'float', 0, None, 'Scene units to meters scale', {}, True, 0.0, False, ''),
('inputs:mode', 'token', 0, None, 'Display mode', {ogn.MetadataKeys.DEFAULT: '"autoMode"'}, True, 'autoMode', False, ''),
('inputs:parameters', 'float4', 0, None, 'Display parameters', {ogn.MetadataKeys.DEFAULT: '[0.0, 5.0, 0.33, 0.27]'}, True, [0.0, 5.0, 0.33, 0.27], False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the input RenderVar to display', {}, True, '', False, ''),
('inputs:renderVarDisplay', 'token', 0, None, 'Name of the output display RenderVar', {}, True, '', False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'Pointer to render product for this view', {}, True, 0, False, ''),
('inputs:sdDisplayHeight', 'uint', 0, None, 'Visualization texture Height', {}, True, 0, False, ''),
('inputs:sdDisplayWidth', 'uint', 0, None, 'Visualization texture width', {}, True, 0, False, ''),
('inputs:sdSemBBox3dCamCornersCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the projection of the 3d bounding boxes on the camera plane represented as a float3=(u,v,z,a) for each bounding box corners', {}, True, 0, False, ''),
('inputs:sdSemBBox3dCamExtentCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the 2d extent of the 3d bounding boxes on the camera plane represented as a float6=(u_min,u_max,v_min,v_max,z_min,z_max)', {}, True, 0, False, ''),
('inputs:sdSemBBoxExtentCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the extent of the bounding boxes as a float4=(u_min,v_min,u_max,v_max) for 2D or a float6=(xmin,ymin,zmin,xmax,ymax,zmax) in object space for 3D', {}, True, 0, False, ''),
('inputs:sdSemBBoxInfosCudaPtr', 'uint64', 0, None, 'Cuda buffer containing valid bounding boxes infos', {}, True, 0, False, ''),
('inputs:semanticLabelTokenSDCudaPtr', 'uint64', 0, None, 'cuda uint64_t buffer pointer of size numSemantics containing the semantic label token', {}, True, 0, False, ''),
('inputs:semanticMapSDCudaPtr', 'uint64', 0, None, 'cuda uint16_t buffer pointer of size numSemantics containing the semantic parent semantic index', {}, True, 0, False, ''),
('inputs:semanticPrimTokenSDCudaPtr', 'uint64', 0, None, 'cuda uint64_t buffer pointer of size numSemantics containing the semantic path token', {}, True, 0, False, ''),
('inputs:semanticWorldTransformSDCudaPtr', 'uint64', 0, None, 'cuda float44 buffer pointer of size numSemantics containing the world semantic transform', {}, True, 0, False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:cudaPtr', 'uint64', 0, None, 'Display texture CUDA pointer', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:format', 'uint64', 0, None, 'Display texture format', {}, True, None, False, ''),
('outputs:height', 'uint', 0, None, 'Display texture height', {}, True, None, False, ''),
('outputs:renderVarDisplay', 'token', 0, None, 'Name of the output display RenderVar', {}, True, None, False, ''),
('outputs:width', 'uint', 0, None, 'Display texture width', {}, True, None, False, ''),
])
class tokens:
LdrColorSD = "LdrColorSD"
Camera3dPositionSD = "Camera3dPositionSD"
DistanceToImagePlaneSD = "DistanceToImagePlaneSD"
DistanceToCameraSD = "DistanceToCameraSD"
InstanceSegmentationSD = "InstanceSegmentationSD"
SemanticSegmentationSD = "SemanticSegmentationSD"
NormalSD = "NormalSD"
TargetMotionSD = "TargetMotionSD"
BoundingBox2DTightSD = "BoundingBox2DTightSD"
BoundingBox2DLooseSD = "BoundingBox2DLooseSD"
BoundingBox3DSD = "BoundingBox3DSD"
OcclusionSD = "OcclusionSD"
TruncationSD = "TruncationSD"
CrossCorrespondenceSD = "CrossCorrespondenceSD"
SemanticBoundingBox2DExtentTightSD = "SemanticBoundingBox2DExtentTightSD"
SemanticBoundingBox2DInfosTightSD = "SemanticBoundingBox2DInfosTightSD"
SemanticBoundingBox2DExtentLooseSD = "SemanticBoundingBox2DExtentLooseSD"
SemanticBoundingBox2DInfosLooseSD = "SemanticBoundingBox2DInfosLooseSD"
SemanticBoundingBox3DExtentSD = "SemanticBoundingBox3DExtentSD"
SemanticBoundingBox3DInfosSD = "SemanticBoundingBox3DInfosSD"
SemanticBoundingBox3DCamCornersSD = "SemanticBoundingBox3DCamCornersSD"
SemanticBoundingBox3DDisplayAxesSD = "SemanticBoundingBox3DDisplayAxesSD"
autoMode = "autoMode"
colorMode = "colorMode"
scaled3dVectorMode = "scaled3dVectorMode"
clippedValueMode = "clippedValueMode"
normalized3dVectorMode = "normalized3dVectorMode"
segmentationMapMode = "segmentationMapMode"
instanceMapMode = "instanceMapMode"
semanticPathMode = "semanticPathMode"
semanticLabelMode = "semanticLabelMode"
semanticBoundingBox2dMode = "semanticBoundingBox2dMode"
rawBoundingBox2dMode = "rawBoundingBox2dMode"
semanticProjBoundingBox3dMode = "semanticProjBoundingBox3dMode"
semanticBoundingBox3dMode = "semanticBoundingBox3dMode"
rawBoundingBox3dMode = "rawBoundingBox3dMode"
pinhole = "pinhole"
perspective = "perspective"
orthographic = "orthographic"
fisheyePolynomial = "fisheyePolynomial"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cameraModel", "cameraNearFar", "exec", "gpu", "instanceMapSDCudaPtr", "instanceMappingInfoSDPtr", "metersPerSceneUnit", "mode", "parameters", "renderVar", "renderVarDisplay", "rp", "sdDisplayHeight", "sdDisplayWidth", "sdSemBBox3dCamCornersCudaPtr", "sdSemBBox3dCamExtentCudaPtr", "sdSemBBoxExtentCudaPtr", "sdSemBBoxInfosCudaPtr", "semanticLabelTokenSDCudaPtr", "semanticMapSDCudaPtr", "semanticPrimTokenSDCudaPtr", "semanticWorldTransformSDCudaPtr", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cameraModel, self._attributes.cameraNearFar, self._attributes.exec, self._attributes.gpu, self._attributes.instanceMapSDCudaPtr, self._attributes.instanceMappingInfoSDPtr, self._attributes.metersPerSceneUnit, self._attributes.mode, self._attributes.parameters, self._attributes.renderVar, self._attributes.renderVarDisplay, self._attributes.rp, self._attributes.sdDisplayHeight, self._attributes.sdDisplayWidth, self._attributes.sdSemBBox3dCamCornersCudaPtr, self._attributes.sdSemBBox3dCamExtentCudaPtr, self._attributes.sdSemBBoxExtentCudaPtr, self._attributes.sdSemBBoxInfosCudaPtr, self._attributes.semanticLabelTokenSDCudaPtr, self._attributes.semanticMapSDCudaPtr, self._attributes.semanticPrimTokenSDCudaPtr, self._attributes.semanticWorldTransformSDCudaPtr, self._attributes.swhFrameNumber]
self._batchedReadValues = [0, [0.0, 0.0], None, 0, 0, 0, 0.0, "autoMode", [0.0, 5.0, 0.33, 0.27], "", "", 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
@property
def cameraFisheyeParams(self):
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
return data_view.get()
@cameraFisheyeParams.setter
def cameraFisheyeParams(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.cameraFisheyeParams)
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
data_view.set(value)
self.cameraFisheyeParams_size = data_view.get_array_size()
@property
def cameraModel(self):
return self._batchedReadValues[0]
@cameraModel.setter
def cameraModel(self, value):
self._batchedReadValues[0] = value
@property
def cameraNearFar(self):
return self._batchedReadValues[1]
@cameraNearFar.setter
def cameraNearFar(self, value):
self._batchedReadValues[1] = value
@property
def exec(self):
return self._batchedReadValues[2]
@exec.setter
def exec(self, value):
self._batchedReadValues[2] = value
@property
def gpu(self):
return self._batchedReadValues[3]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[3] = value
@property
def instanceMapSDCudaPtr(self):
return self._batchedReadValues[4]
@instanceMapSDCudaPtr.setter
def instanceMapSDCudaPtr(self, value):
self._batchedReadValues[4] = value
@property
def instanceMappingInfoSDPtr(self):
return self._batchedReadValues[5]
@instanceMappingInfoSDPtr.setter
def instanceMappingInfoSDPtr(self, value):
self._batchedReadValues[5] = value
@property
def metersPerSceneUnit(self):
return self._batchedReadValues[6]
@metersPerSceneUnit.setter
def metersPerSceneUnit(self, value):
self._batchedReadValues[6] = value
@property
def mode(self):
return self._batchedReadValues[7]
@mode.setter
def mode(self, value):
self._batchedReadValues[7] = value
@property
def parameters(self):
return self._batchedReadValues[8]
@parameters.setter
def parameters(self, value):
self._batchedReadValues[8] = value
@property
def renderVar(self):
return self._batchedReadValues[9]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[9] = value
@property
def renderVarDisplay(self):
return self._batchedReadValues[10]
@renderVarDisplay.setter
def renderVarDisplay(self, value):
self._batchedReadValues[10] = value
@property
def rp(self):
return self._batchedReadValues[11]
@rp.setter
def rp(self, value):
self._batchedReadValues[11] = value
@property
def sdDisplayHeight(self):
return self._batchedReadValues[12]
@sdDisplayHeight.setter
def sdDisplayHeight(self, value):
self._batchedReadValues[12] = value
@property
def sdDisplayWidth(self):
return self._batchedReadValues[13]
@sdDisplayWidth.setter
def sdDisplayWidth(self, value):
self._batchedReadValues[13] = value
@property
def sdSemBBox3dCamCornersCudaPtr(self):
return self._batchedReadValues[14]
@sdSemBBox3dCamCornersCudaPtr.setter
def sdSemBBox3dCamCornersCudaPtr(self, value):
self._batchedReadValues[14] = value
@property
def sdSemBBox3dCamExtentCudaPtr(self):
return self._batchedReadValues[15]
@sdSemBBox3dCamExtentCudaPtr.setter
def sdSemBBox3dCamExtentCudaPtr(self, value):
self._batchedReadValues[15] = value
@property
def sdSemBBoxExtentCudaPtr(self):
return self._batchedReadValues[16]
@sdSemBBoxExtentCudaPtr.setter
def sdSemBBoxExtentCudaPtr(self, value):
self._batchedReadValues[16] = value
@property
def sdSemBBoxInfosCudaPtr(self):
return self._batchedReadValues[17]
@sdSemBBoxInfosCudaPtr.setter
def sdSemBBoxInfosCudaPtr(self, value):
self._batchedReadValues[17] = value
@property
def semanticLabelTokenSDCudaPtr(self):
return self._batchedReadValues[18]
@semanticLabelTokenSDCudaPtr.setter
def semanticLabelTokenSDCudaPtr(self, value):
self._batchedReadValues[18] = value
@property
def semanticMapSDCudaPtr(self):
return self._batchedReadValues[19]
@semanticMapSDCudaPtr.setter
def semanticMapSDCudaPtr(self, value):
self._batchedReadValues[19] = value
@property
def semanticPrimTokenSDCudaPtr(self):
return self._batchedReadValues[20]
@semanticPrimTokenSDCudaPtr.setter
def semanticPrimTokenSDCudaPtr(self, value):
self._batchedReadValues[20] = value
@property
def semanticWorldTransformSDCudaPtr(self):
return self._batchedReadValues[21]
@semanticWorldTransformSDCudaPtr.setter
def semanticWorldTransformSDCudaPtr(self, value):
self._batchedReadValues[21] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[22]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[22] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaPtr", "exec", "format", "height", "renderVarDisplay", "width", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def cudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.cudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaPtr)
return data_view.get()
@cudaPtr.setter
def cudaPtr(self, value):
self._batchedWriteValues[self._attributes.cudaPtr] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def format(self):
value = self._batchedWriteValues.get(self._attributes.format)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.format)
return data_view.get()
@format.setter
def format(self, value):
self._batchedWriteValues[self._attributes.format] = value
@property
def height(self):
value = self._batchedWriteValues.get(self._attributes.height)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.height)
return data_view.get()
@height.setter
def height(self, value):
self._batchedWriteValues[self._attributes.height] = value
@property
def renderVarDisplay(self):
value = self._batchedWriteValues.get(self._attributes.renderVarDisplay)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.renderVarDisplay)
return data_view.get()
@renderVarDisplay.setter
def renderVarDisplay(self, value):
self._batchedWriteValues[self._attributes.renderVarDisplay] = value
@property
def width(self):
value = self._batchedWriteValues.get(self._attributes.width)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.width)
return data_view.get()
@width.setter
def width(self, value):
self._batchedWriteValues[self._attributes.width] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostRenderVarDisplayTextureDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostRenderVarDisplayTextureDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostRenderVarDisplayTextureDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 24,183 | Python | 45.597302 | 858 | 0.652938 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdTestStageSynchronizationDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdTestStageSynchronization
Synthetic Data node to test the pipeline stage synchronization
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdTestStageSynchronizationDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdTestStageSynchronization
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.gpu
inputs.randomMaxProcessingTimeUs
inputs.randomSeed
inputs.renderResults
inputs.rp
inputs.swhFrameNumber
inputs.tag
inputs.traceError
Outputs:
outputs.exec
outputs.fabricSWHFrameNumber
outputs.swhFrameNumber
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'OnDemand connection : trigger', {}, True, None, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'PostRender connection : pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:randomMaxProcessingTimeUs', 'uint', 0, None, 'Maximum number of micro-seconds to randomly (uniformely) wait for in order to simulate varying workload', {ogn.MetadataKeys.DEFAULT: '0'}, True, 0, False, ''),
('inputs:randomSeed', 'uint', 0, None, 'Random seed for the randomization', {ogn.MetadataKeys.DEFAULT: '0'}, True, 0, False, ''),
('inputs:renderResults', 'uint64', 0, None, 'OnDemand connection : pointer to render product results', {}, True, 0, False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'PostRender connection : pointer to render product for this view', {}, True, 0, False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('inputs:tag', 'token', 0, None, 'A tag to identify the node', {}, True, '', False, ''),
('inputs:traceError', 'bool', 0, None, 'If true print an error message when the frame numbers are out-of-sync', {ogn.MetadataKeys.DEFAULT: 'false'}, True, False, False, ''),
('outputs:exec', 'execution', 0, None, 'OnDemand connection : trigger', {}, True, None, False, ''),
('outputs:fabricSWHFrameNumber', 'uint64', 0, None, 'Fabric frame number from the fabric', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "gpu", "randomMaxProcessingTimeUs", "randomSeed", "renderResults", "rp", "swhFrameNumber", "tag", "traceError", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.gpu, self._attributes.randomMaxProcessingTimeUs, self._attributes.randomSeed, self._attributes.renderResults, self._attributes.rp, self._attributes.swhFrameNumber, self._attributes.tag, self._attributes.traceError]
self._batchedReadValues = [None, 0, 0, 0, 0, 0, 0, "", False]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def gpu(self):
return self._batchedReadValues[1]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[1] = value
@property
def randomMaxProcessingTimeUs(self):
return self._batchedReadValues[2]
@randomMaxProcessingTimeUs.setter
def randomMaxProcessingTimeUs(self, value):
self._batchedReadValues[2] = value
@property
def randomSeed(self):
return self._batchedReadValues[3]
@randomSeed.setter
def randomSeed(self, value):
self._batchedReadValues[3] = value
@property
def renderResults(self):
return self._batchedReadValues[4]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[4] = value
@property
def rp(self):
return self._batchedReadValues[5]
@rp.setter
def rp(self, value):
self._batchedReadValues[5] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[6]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[6] = value
@property
def tag(self):
return self._batchedReadValues[7]
@tag.setter
def tag(self, value):
self._batchedReadValues[7] = value
@property
def traceError(self):
return self._batchedReadValues[8]
@traceError.setter
def traceError(self, value):
self._batchedReadValues[8] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "fabricSWHFrameNumber", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def fabricSWHFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.fabricSWHFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.fabricSWHFrameNumber)
return data_view.get()
@fabricSWHFrameNumber.setter
def fabricSWHFrameNumber(self, value):
self._batchedWriteValues[self._attributes.fabricSWHFrameNumber] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdTestStageSynchronizationDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdTestStageSynchronizationDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdTestStageSynchronizationDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 10,958 | Python | 45.634042 | 297 | 0.634331 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdRenderVarDisplayTextureDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdRenderVarDisplayTexture
Synthetic Data node to expose texture handle of a visualization AOV
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdRenderVarDisplayTextureDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdRenderVarDisplayTexture
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.renderResults
inputs.renderVarDisplay
inputs.swhFrameNumber
Outputs:
outputs.cudaPtr
outputs.exec
outputs.format
outputs.handlePtr
outputs.height
outputs.swhFrameNumber
outputs.width
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:renderResults', 'uint64', 0, None, 'Render results pointer', {}, True, 0, False, ''),
('inputs:renderVarDisplay', 'token', 0, None, 'Name of the renderVar', {}, True, '', False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:cudaPtr', 'uint64', 0, None, 'Display texture CUDA pointer', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:format', 'uint64', 0, None, 'Display texture format', {}, True, None, False, ''),
('outputs:handlePtr', 'uint64', 0, None, 'Display texture handle reference', {}, True, None, False, ''),
('outputs:height', 'uint', 0, None, 'Display texture height', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
('outputs:width', 'uint', 0, None, 'Display texture width', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "renderResults", "renderVarDisplay", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.renderResults, self._attributes.renderVarDisplay, self._attributes.swhFrameNumber]
self._batchedReadValues = [None, 0, "", 0]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def renderResults(self):
return self._batchedReadValues[1]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[1] = value
@property
def renderVarDisplay(self):
return self._batchedReadValues[2]
@renderVarDisplay.setter
def renderVarDisplay(self, value):
self._batchedReadValues[2] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[3]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaPtr", "exec", "format", "handlePtr", "height", "swhFrameNumber", "width", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def cudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.cudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaPtr)
return data_view.get()
@cudaPtr.setter
def cudaPtr(self, value):
self._batchedWriteValues[self._attributes.cudaPtr] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def format(self):
value = self._batchedWriteValues.get(self._attributes.format)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.format)
return data_view.get()
@format.setter
def format(self, value):
self._batchedWriteValues[self._attributes.format] = value
@property
def handlePtr(self):
value = self._batchedWriteValues.get(self._attributes.handlePtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.handlePtr)
return data_view.get()
@handlePtr.setter
def handlePtr(self, value):
self._batchedWriteValues[self._attributes.handlePtr] = value
@property
def height(self):
value = self._batchedWriteValues.get(self._attributes.height)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.height)
return data_view.get()
@height.setter
def height(self, value):
self._batchedWriteValues[self._attributes.height] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
@property
def width(self):
value = self._batchedWriteValues.get(self._attributes.width)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.width)
return data_view.get()
@width.setter
def width(self, value):
self._batchedWriteValues[self._attributes.width] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdRenderVarDisplayTextureDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdRenderVarDisplayTextureDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdRenderVarDisplayTextureDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 10,872 | Python | 43.379592 | 165 | 0.617274 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostRenderVarTextureToBufferDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostRenderVarTextureToBuffer
Expose a device renderVar buffer a texture one.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdPostRenderVarTextureToBufferDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostRenderVarTextureToBuffer
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.gpu
inputs.renderVar
inputs.renderVarBufferSuffix
inputs.rp
Outputs:
outputs.renderVar
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:gpu', 'uint64', 0, None, 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the device renderVar to expose on the host', {}, True, '', False, ''),
('inputs:renderVarBufferSuffix', 'string', 0, None, 'Suffix appended to the renderVar name', {ogn.MetadataKeys.DEFAULT: '"buffer"'}, True, 'buffer', False, ''),
('inputs:rp', 'uint64', 0, None, 'Pointer to render product for this view', {}, True, 0, False, ''),
('outputs:renderVar', 'token', 0, None, 'Name of the resulting renderVar on the host', {}, True, None, False, ''),
])
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"gpu", "renderVar", "renderVarBufferSuffix", "rp", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.gpu, self._attributes.renderVar, self._attributes.renderVarBufferSuffix, self._attributes.rp]
self._batchedReadValues = [0, "", "buffer", 0]
@property
def gpu(self):
return self._batchedReadValues[0]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[0] = value
@property
def renderVar(self):
return self._batchedReadValues[1]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[1] = value
@property
def renderVarBufferSuffix(self):
return self._batchedReadValues[2]
@renderVarBufferSuffix.setter
def renderVarBufferSuffix(self, value):
self._batchedReadValues[2] = value
@property
def rp(self):
return self._batchedReadValues[3]
@rp.setter
def rp(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"renderVar", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def renderVar(self):
value = self._batchedWriteValues.get(self._attributes.renderVar)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.renderVar)
return data_view.get()
@renderVar.setter
def renderVar(self, value):
self._batchedWriteValues[self._attributes.renderVar] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostRenderVarTextureToBufferDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostRenderVarTextureToBufferDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostRenderVarTextureToBufferDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 7,180 | Python | 47.52027 | 168 | 0.644568 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdRenderProductCameraDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdRenderProductCamera
Synthetic Data node to expose the camera data
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdRenderProductCameraDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdRenderProductCamera
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.renderProductPath
inputs.renderResults
inputs.swhFrameNumber
Outputs:
outputs.cameraApertureOffset
outputs.cameraApertureSize
outputs.cameraFStop
outputs.cameraFisheyeParams
outputs.cameraFocalLength
outputs.cameraFocusDistance
outputs.cameraModel
outputs.cameraNearFar
outputs.cameraProjection
outputs.cameraViewTransform
outputs.exec
outputs.metersPerSceneUnit
outputs.renderProductResolution
outputs.swhFrameNumber
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:renderProductPath', 'token', 0, None, 'RenderProduct prim path', {}, True, '', False, ''),
('inputs:renderResults', 'uint64', 0, None, 'Render results', {}, True, 0, False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:cameraApertureOffset', 'float2', 0, None, 'Camera horizontal and vertical aperture offset', {}, True, None, False, ''),
('outputs:cameraApertureSize', 'float2', 0, None, 'Camera horizontal and vertical aperture', {}, True, None, False, ''),
('outputs:cameraFStop', 'float', 0, None, 'Camera fStop', {}, True, None, False, ''),
('outputs:cameraFisheyeParams', 'float[]', 0, None, 'Camera fisheye projection parameters', {}, True, None, False, ''),
('outputs:cameraFocalLength', 'float', 0, None, 'Camera focal length', {}, True, None, False, ''),
('outputs:cameraFocusDistance', 'float', 0, None, 'Camera focus distance', {}, True, None, False, ''),
('outputs:cameraModel', 'int', 0, None, 'Camera model (pinhole or fisheye models)', {}, True, None, False, ''),
('outputs:cameraNearFar', 'float2', 0, None, 'Camera near/far clipping range', {}, True, None, False, ''),
('outputs:cameraProjection', 'matrix4d', 0, None, 'Camera projection matrix', {}, True, None, False, ''),
('outputs:cameraViewTransform', 'matrix4d', 0, None, 'Camera view matrix', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes for each newFrame event received', {}, True, None, False, ''),
('outputs:metersPerSceneUnit', 'float', 0, None, 'Scene units to meters scale', {}, True, None, False, ''),
('outputs:renderProductResolution', 'int2', 0, None, 'RenderProduct resolution', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.cameraProjection = og.Database.ROLE_MATRIX
role_data.outputs.cameraViewTransform = og.Database.ROLE_MATRIX
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "renderProductPath", "renderResults", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.renderProductPath, self._attributes.renderResults, self._attributes.swhFrameNumber]
self._batchedReadValues = [None, "", 0, 0]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def renderProductPath(self):
return self._batchedReadValues[1]
@renderProductPath.setter
def renderProductPath(self, value):
self._batchedReadValues[1] = value
@property
def renderResults(self):
return self._batchedReadValues[2]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[2] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[3]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cameraApertureOffset", "cameraApertureSize", "cameraFStop", "cameraFocalLength", "cameraFocusDistance", "cameraModel", "cameraNearFar", "cameraProjection", "cameraViewTransform", "exec", "metersPerSceneUnit", "renderProductResolution", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self.cameraFisheyeParams_size = None
self._batchedWriteValues = { }
@property
def cameraFisheyeParams(self):
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
return data_view.get(reserved_element_count=self.cameraFisheyeParams_size)
@cameraFisheyeParams.setter
def cameraFisheyeParams(self, value):
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
data_view.set(value)
self.cameraFisheyeParams_size = data_view.get_array_size()
@property
def cameraApertureOffset(self):
value = self._batchedWriteValues.get(self._attributes.cameraApertureOffset)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraApertureOffset)
return data_view.get()
@cameraApertureOffset.setter
def cameraApertureOffset(self, value):
self._batchedWriteValues[self._attributes.cameraApertureOffset] = value
@property
def cameraApertureSize(self):
value = self._batchedWriteValues.get(self._attributes.cameraApertureSize)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraApertureSize)
return data_view.get()
@cameraApertureSize.setter
def cameraApertureSize(self, value):
self._batchedWriteValues[self._attributes.cameraApertureSize] = value
@property
def cameraFStop(self):
value = self._batchedWriteValues.get(self._attributes.cameraFStop)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraFStop)
return data_view.get()
@cameraFStop.setter
def cameraFStop(self, value):
self._batchedWriteValues[self._attributes.cameraFStop] = value
@property
def cameraFocalLength(self):
value = self._batchedWriteValues.get(self._attributes.cameraFocalLength)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraFocalLength)
return data_view.get()
@cameraFocalLength.setter
def cameraFocalLength(self, value):
self._batchedWriteValues[self._attributes.cameraFocalLength] = value
@property
def cameraFocusDistance(self):
value = self._batchedWriteValues.get(self._attributes.cameraFocusDistance)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraFocusDistance)
return data_view.get()
@cameraFocusDistance.setter
def cameraFocusDistance(self, value):
self._batchedWriteValues[self._attributes.cameraFocusDistance] = value
@property
def cameraModel(self):
value = self._batchedWriteValues.get(self._attributes.cameraModel)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraModel)
return data_view.get()
@cameraModel.setter
def cameraModel(self, value):
self._batchedWriteValues[self._attributes.cameraModel] = value
@property
def cameraNearFar(self):
value = self._batchedWriteValues.get(self._attributes.cameraNearFar)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraNearFar)
return data_view.get()
@cameraNearFar.setter
def cameraNearFar(self, value):
self._batchedWriteValues[self._attributes.cameraNearFar] = value
@property
def cameraProjection(self):
value = self._batchedWriteValues.get(self._attributes.cameraProjection)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraProjection)
return data_view.get()
@cameraProjection.setter
def cameraProjection(self, value):
self._batchedWriteValues[self._attributes.cameraProjection] = value
@property
def cameraViewTransform(self):
value = self._batchedWriteValues.get(self._attributes.cameraViewTransform)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cameraViewTransform)
return data_view.get()
@cameraViewTransform.setter
def cameraViewTransform(self, value):
self._batchedWriteValues[self._attributes.cameraViewTransform] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def metersPerSceneUnit(self):
value = self._batchedWriteValues.get(self._attributes.metersPerSceneUnit)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.metersPerSceneUnit)
return data_view.get()
@metersPerSceneUnit.setter
def metersPerSceneUnit(self, value):
self._batchedWriteValues[self._attributes.metersPerSceneUnit] = value
@property
def renderProductResolution(self):
value = self._batchedWriteValues.get(self._attributes.renderProductResolution)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.renderProductResolution)
return data_view.get()
@renderProductResolution.setter
def renderProductResolution(self, value):
self._batchedWriteValues[self._attributes.renderProductResolution] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdRenderProductCameraDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdRenderProductCameraDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdRenderProductCameraDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 16,236 | Python | 45.127841 | 309 | 0.631683 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostCompRenderVarTexturesDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostCompRenderVarTextures
Synthetic Data node to compose a front renderVar texture into a back renderVar texture
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdPostCompRenderVarTexturesDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostCompRenderVarTextures
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cudaPtr
inputs.format
inputs.gpu
inputs.height
inputs.mode
inputs.parameters
inputs.renderVar
inputs.rp
inputs.width
Predefined Tokens:
tokens.line
tokens.grid
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cudaPtr', 'uint64', 0, None, 'Front texture CUDA pointer', {}, True, 0, False, ''),
('inputs:format', 'uint64', 0, None, 'Front texture format', {}, True, 0, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:height', 'uint', 0, None, 'Front texture height', {}, True, 0, False, ''),
('inputs:mode', 'token', 0, None, 'Mode : grid, line', {ogn.MetadataKeys.DEFAULT: '"line"'}, True, 'line', False, ''),
('inputs:parameters', 'float3', 0, None, 'Parameters', {ogn.MetadataKeys.DEFAULT: '[0, 0, 0]'}, True, [0, 0, 0], False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the back RenderVar', {ogn.MetadataKeys.DEFAULT: '"LdrColor"'}, True, 'LdrColor', False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'Pointer to render product for this view', {}, True, 0, False, ''),
('inputs:width', 'uint', 0, None, 'Front texture width', {}, True, 0, False, ''),
])
class tokens:
line = "line"
grid = "grid"
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaPtr", "format", "gpu", "height", "mode", "parameters", "renderVar", "rp", "width", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cudaPtr, self._attributes.format, self._attributes.gpu, self._attributes.height, self._attributes.mode, self._attributes.parameters, self._attributes.renderVar, self._attributes.rp, self._attributes.width]
self._batchedReadValues = [0, 0, 0, 0, "line", [0, 0, 0], "LdrColor", 0, 0]
@property
def cudaPtr(self):
return self._batchedReadValues[0]
@cudaPtr.setter
def cudaPtr(self, value):
self._batchedReadValues[0] = value
@property
def format(self):
return self._batchedReadValues[1]
@format.setter
def format(self, value):
self._batchedReadValues[1] = value
@property
def gpu(self):
return self._batchedReadValues[2]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[2] = value
@property
def height(self):
return self._batchedReadValues[3]
@height.setter
def height(self, value):
self._batchedReadValues[3] = value
@property
def mode(self):
return self._batchedReadValues[4]
@mode.setter
def mode(self, value):
self._batchedReadValues[4] = value
@property
def parameters(self):
return self._batchedReadValues[5]
@parameters.setter
def parameters(self, value):
self._batchedReadValues[5] = value
@property
def renderVar(self):
return self._batchedReadValues[6]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[6] = value
@property
def rp(self):
return self._batchedReadValues[7]
@rp.setter
def rp(self, value):
self._batchedReadValues[7] = value
@property
def width(self):
return self._batchedReadValues[8]
@width.setter
def width(self, value):
self._batchedReadValues[8] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = { }
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostCompRenderVarTexturesDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostCompRenderVarTexturesDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostCompRenderVarTexturesDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 7,980 | Python | 43.837078 | 265 | 0.63183 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdOnNewRenderProductFrameDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdOnNewRenderProductFrame
Synthetic Data postprocess node to execute pipeline after the NewFrame event has been received on the given renderProduct
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdOnNewRenderProductFrameDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdOnNewRenderProductFrame
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.renderProductDataPtrs
inputs.renderProductPath
inputs.renderProductPaths
inputs.swhFrameNumber
Outputs:
outputs.cudaStream
outputs.exec
outputs.renderProductPath
outputs.renderResults
outputs.swhFrameNumber
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, 'Received', 'Executes for each newFrame event received', {}, True, None, False, ''),
('inputs:renderProductDataPtrs', 'uint64[]', 0, None, 'HydraRenderProduct data pointers.', {}, True, [], False, ''),
('inputs:renderProductPath', 'token', 0, None, 'Path of the renderProduct to wait for being rendered', {}, True, '', False, ''),
('inputs:renderProductPaths', 'token[]', 0, None, 'Render product path tokens.', {}, True, [], False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:cudaStream', 'uint64', 0, None, 'Cuda stream', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes for each newFrame event received', {}, True, None, False, ''),
('outputs:renderProductPath', 'token', 0, None, 'Path of the renderProduct to wait for being rendered', {}, True, None, False, ''),
('outputs:renderResults', 'uint64', 0, None, 'Render results', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "renderProductPath", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.renderProductPath, self._attributes.swhFrameNumber]
self._batchedReadValues = [None, "", 0]
@property
def renderProductDataPtrs(self):
data_view = og.AttributeValueHelper(self._attributes.renderProductDataPtrs)
return data_view.get()
@renderProductDataPtrs.setter
def renderProductDataPtrs(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.renderProductDataPtrs)
data_view = og.AttributeValueHelper(self._attributes.renderProductDataPtrs)
data_view.set(value)
self.renderProductDataPtrs_size = data_view.get_array_size()
@property
def renderProductPaths(self):
data_view = og.AttributeValueHelper(self._attributes.renderProductPaths)
return data_view.get()
@renderProductPaths.setter
def renderProductPaths(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.renderProductPaths)
data_view = og.AttributeValueHelper(self._attributes.renderProductPaths)
data_view.set(value)
self.renderProductPaths_size = data_view.get_array_size()
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def renderProductPath(self):
return self._batchedReadValues[1]
@renderProductPath.setter
def renderProductPath(self, value):
self._batchedReadValues[1] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[2]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[2] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaStream", "exec", "renderProductPath", "renderResults", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def cudaStream(self):
value = self._batchedWriteValues.get(self._attributes.cudaStream)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaStream)
return data_view.get()
@cudaStream.setter
def cudaStream(self, value):
self._batchedWriteValues[self._attributes.cudaStream] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def renderProductPath(self):
value = self._batchedWriteValues.get(self._attributes.renderProductPath)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.renderProductPath)
return data_view.get()
@renderProductPath.setter
def renderProductPath(self, value):
self._batchedWriteValues[self._attributes.renderProductPath] = value
@property
def renderResults(self):
value = self._batchedWriteValues.get(self._attributes.renderResults)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.renderResults)
return data_view.get()
@renderResults.setter
def renderResults(self, value):
self._batchedWriteValues[self._attributes.renderResults] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdOnNewRenderProductFrameDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdOnNewRenderProductFrameDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdOnNewRenderProductFrameDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 11,145 | Python | 46.228813 | 145 | 0.637057 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdTestPrintRawArrayDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdTestPrintRawArray
Synthetic Data test node printing the input linear array
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
import sys
import traceback
class OgnSdTestPrintRawArrayDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdTestPrintRawArray
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.bufferSize
inputs.data
inputs.elementCount
inputs.elementType
inputs.exec
inputs.height
inputs.mode
inputs.randomSeed
inputs.referenceNumUniqueRandomValues
inputs.referenceSWHFrameNumbers
inputs.referenceTolerance
inputs.referenceValues
inputs.swhFrameNumber
inputs.width
Outputs:
outputs.exec
outputs.swhFrameNumber
State:
state.initialSWHFrameNumber
Predefined Tokens:
tokens.uint16
tokens.int16
tokens.uint32
tokens.int32
tokens.float32
tokens.token
tokens.printFormatted
tokens.printReferences
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:bufferSize', 'uint', 0, None, 'Size (in bytes) of the buffer (0 if the input is a texture)', {}, True, 0, False, ''),
('inputs:data', 'uchar[]', 0, None, 'Buffer array data', {ogn.MetadataKeys.DEFAULT: '[]'}, True, [], False, ''),
('inputs:elementCount', 'int', 0, None, 'Number of array element', {ogn.MetadataKeys.DEFAULT: '1'}, True, 1, False, ''),
('inputs:elementType', 'token', 0, None, 'Type of the array element', {ogn.MetadataKeys.DEFAULT: '"uint8"'}, True, 'uint8', False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:height', 'uint', 0, None, 'Height (0 if the input is a buffer)', {}, True, 0, False, ''),
('inputs:mode', 'token', 0, None, 'Mode in [printFormatted, printReferences, testReferences]', {ogn.MetadataKeys.DEFAULT: '"printFormatted"'}, True, 'printFormatted', False, ''),
('inputs:randomSeed', 'int', 0, None, 'Random seed', {}, True, 0, False, ''),
('inputs:referenceNumUniqueRandomValues', 'int', 0, None, 'Number of reference unique random values to compare', {ogn.MetadataKeys.DEFAULT: '7'}, True, 7, False, ''),
('inputs:referenceSWHFrameNumbers', 'uint[]', 0, None, 'Reference swhFrameNumbers relative to the first one', {ogn.MetadataKeys.DEFAULT: '[11, 17, 29]'}, True, [11, 17, 29], False, ''),
('inputs:referenceTolerance', 'float', 0, None, 'Reference tolerance', {ogn.MetadataKeys.DEFAULT: '0.1'}, True, 0.1, False, ''),
('inputs:referenceValues', 'float[]', 0, None, 'Reference data point values', {}, True, [], False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Frame number', {}, True, 0, False, ''),
('inputs:width', 'uint', 0, None, 'Width (0 if the input is a buffer)', {}, True, 0, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'FrameNumber just rendered', {}, True, None, False, ''),
('state:initialSWHFrameNumber', 'int64', 0, None, 'Initial swhFrameNumber', {ogn.MetadataKeys.DEFAULT: '-1'}, True, -1, False, ''),
])
class tokens:
uint16 = "uint16"
int16 = "int16"
uint32 = "uint32"
int32 = "int32"
float32 = "float32"
token = "token"
printFormatted = "printFormatted"
printReferences = "printReferences"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"bufferSize", "elementCount", "elementType", "exec", "height", "mode", "randomSeed", "referenceNumUniqueRandomValues", "referenceTolerance", "swhFrameNumber", "width", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.bufferSize, self._attributes.elementCount, self._attributes.elementType, self._attributes.exec, self._attributes.height, self._attributes.mode, self._attributes.randomSeed, self._attributes.referenceNumUniqueRandomValues, self._attributes.referenceTolerance, self._attributes.swhFrameNumber, self._attributes.width]
self._batchedReadValues = [0, 1, "uint8", None, 0, "printFormatted", 0, 7, 0.1, 0, 0]
@property
def data(self):
data_view = og.AttributeValueHelper(self._attributes.data)
return data_view.get()
@data.setter
def data(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.data)
data_view = og.AttributeValueHelper(self._attributes.data)
data_view.set(value)
self.data_size = data_view.get_array_size()
@property
def referenceSWHFrameNumbers(self):
data_view = og.AttributeValueHelper(self._attributes.referenceSWHFrameNumbers)
return data_view.get()
@referenceSWHFrameNumbers.setter
def referenceSWHFrameNumbers(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.referenceSWHFrameNumbers)
data_view = og.AttributeValueHelper(self._attributes.referenceSWHFrameNumbers)
data_view.set(value)
self.referenceSWHFrameNumbers_size = data_view.get_array_size()
@property
def referenceValues(self):
data_view = og.AttributeValueHelper(self._attributes.referenceValues)
return data_view.get()
@referenceValues.setter
def referenceValues(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.referenceValues)
data_view = og.AttributeValueHelper(self._attributes.referenceValues)
data_view.set(value)
self.referenceValues_size = data_view.get_array_size()
@property
def bufferSize(self):
return self._batchedReadValues[0]
@bufferSize.setter
def bufferSize(self, value):
self._batchedReadValues[0] = value
@property
def elementCount(self):
return self._batchedReadValues[1]
@elementCount.setter
def elementCount(self, value):
self._batchedReadValues[1] = value
@property
def elementType(self):
return self._batchedReadValues[2]
@elementType.setter
def elementType(self, value):
self._batchedReadValues[2] = value
@property
def exec(self):
return self._batchedReadValues[3]
@exec.setter
def exec(self, value):
self._batchedReadValues[3] = value
@property
def height(self):
return self._batchedReadValues[4]
@height.setter
def height(self, value):
self._batchedReadValues[4] = value
@property
def mode(self):
return self._batchedReadValues[5]
@mode.setter
def mode(self, value):
self._batchedReadValues[5] = value
@property
def randomSeed(self):
return self._batchedReadValues[6]
@randomSeed.setter
def randomSeed(self, value):
self._batchedReadValues[6] = value
@property
def referenceNumUniqueRandomValues(self):
return self._batchedReadValues[7]
@referenceNumUniqueRandomValues.setter
def referenceNumUniqueRandomValues(self, value):
self._batchedReadValues[7] = value
@property
def referenceTolerance(self):
return self._batchedReadValues[8]
@referenceTolerance.setter
def referenceTolerance(self, value):
self._batchedReadValues[8] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[9]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[9] = value
@property
def width(self):
return self._batchedReadValues[10]
@width.setter
def width(self, value):
self._batchedReadValues[10] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
@property
def initialSWHFrameNumber(self):
data_view = og.AttributeValueHelper(self._attributes.initialSWHFrameNumber)
return data_view.get()
@initialSWHFrameNumber.setter
def initialSWHFrameNumber(self, value):
data_view = og.AttributeValueHelper(self._attributes.initialSWHFrameNumber)
data_view.set(value)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdTestPrintRawArrayDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdTestPrintRawArrayDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdTestPrintRawArrayDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
class abi:
"""Class defining the ABI interface for the node type"""
@staticmethod
def get_node_type():
get_node_type_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'get_node_type', None)
if callable(get_node_type_function):
return get_node_type_function()
return 'omni.syntheticdata.SdTestPrintRawArray'
@staticmethod
def compute(context, node):
try:
per_node_data = OgnSdTestPrintRawArrayDatabase.PER_NODE_DATA[node.node_id()]
db = per_node_data.get('_db')
if db is None:
db = OgnSdTestPrintRawArrayDatabase(node)
per_node_data['_db'] = db
except:
db = OgnSdTestPrintRawArrayDatabase(node)
try:
compute_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'compute', None)
if callable(compute_function) and compute_function.__code__.co_argcount > 1:
return compute_function(context, node)
db.inputs._prefetch()
db.inputs._setting_locked = True
with og.in_compute():
return OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS.compute(db)
except Exception as error:
stack_trace = "".join(traceback.format_tb(sys.exc_info()[2].tb_next))
db.log_error(f'Assertion raised in compute - {error}\n{stack_trace}', add_context=False)
finally:
db.inputs._setting_locked = False
db.outputs._commit()
return False
@staticmethod
def initialize(context, node):
OgnSdTestPrintRawArrayDatabase._initialize_per_node_data(node)
initialize_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'initialize', None)
if callable(initialize_function):
initialize_function(context, node)
@staticmethod
def release(node):
release_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'release', None)
if callable(release_function):
release_function(node)
OgnSdTestPrintRawArrayDatabase._release_per_node_data(node)
@staticmethod
def update_node_version(context, node, old_version, new_version):
update_node_version_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'update_node_version', None)
if callable(update_node_version_function):
return update_node_version_function(context, node, old_version, new_version)
return False
@staticmethod
def initialize_type(node_type):
initialize_type_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'initialize_type', None)
needs_initializing = True
if callable(initialize_type_function):
needs_initializing = initialize_type_function(node_type)
if needs_initializing:
node_type.set_metadata(ogn.MetadataKeys.EXTENSION, "omni.syntheticdata")
node_type.set_metadata(ogn.MetadataKeys.TOKENS, "[\"uint16\", \"int16\", \"uint32\", \"int32\", \"float32\", \"token\", \"printFormatted\", \"printReferences\"]")
node_type.set_metadata(ogn.MetadataKeys.CATEGORIES, "graph:action,internal:test")
node_type.set_metadata(ogn.MetadataKeys.DESCRIPTION, "Synthetic Data test node printing the input linear array")
node_type.set_metadata(ogn.MetadataKeys.EXCLUSIONS, "tests")
node_type.set_metadata(ogn.MetadataKeys.LANGUAGE, "Python")
OgnSdTestPrintRawArrayDatabase.INTERFACE.add_to_node_type(node_type)
node_type.set_has_state(True)
@staticmethod
def on_connection_type_resolve(node):
on_connection_type_resolve_function = getattr(OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS, 'on_connection_type_resolve', None)
if callable(on_connection_type_resolve_function):
on_connection_type_resolve_function(node)
NODE_TYPE_CLASS = None
GENERATOR_VERSION = (1, 17, 2)
TARGET_VERSION = (2, 65, 4)
@staticmethod
def register(node_type_class):
OgnSdTestPrintRawArrayDatabase.NODE_TYPE_CLASS = node_type_class
og.register_node_type(OgnSdTestPrintRawArrayDatabase.abi, 1)
@staticmethod
def deregister():
og.deregister_node_type("omni.syntheticdata.SdTestPrintRawArray")
| 18,880 | Python | 45.851117 | 375 | 0.628284 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdSimRenderProductCameraDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdSimRenderProductCamera
Synthetic Data node to expose the renderProduct camera in the fabric
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdSimRenderProductCameraDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdSimRenderProductCamera
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.renderProductPath
Outputs:
outputs.exec
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:renderProductPath', 'token', 0, None, 'renderProduct prim path', {}, True, '', False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"renderProductPath", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.renderProductPath]
self._batchedReadValues = [""]
@property
def renderProductPath(self):
return self._batchedReadValues[0]
@renderProductPath.setter
def renderProductPath(self, value):
self._batchedReadValues[0] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdSimRenderProductCameraDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdSimRenderProductCameraDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdSimRenderProductCameraDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 6,155 | Python | 48.645161 | 126 | 0.652153 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdUpdateSwhFrameNumberDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdUpdateSwFrameNumber
Synthetic Data node to return the current update swhFrameNumber
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdUpdateSwhFrameNumberDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdUpdateSwFrameNumber
Class Members:
node: Node being evaluated
Attribute Value Properties:
Outputs:
outputs.exec
outputs.swhFrameNumber
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = { }
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = []
self._batchedReadValues = []
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdUpdateSwhFrameNumberDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdUpdateSwhFrameNumberDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdUpdateSwhFrameNumberDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 5,845 | Python | 49.396551 | 124 | 0.658854 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdTextureToLinearArrayDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdTextureToLinearArray
SyntheticData node to copy the input texture into a linear array buffer
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdTextureToLinearArrayDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdTextureToLinearArray
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cudaMipmappedArray
inputs.format
inputs.height
inputs.hydraTime
inputs.mipCount
inputs.outputHeight
inputs.outputWidth
inputs.simTime
inputs.stream
inputs.width
Outputs:
outputs.data
outputs.height
outputs.hydraTime
outputs.simTime
outputs.stream
outputs.width
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cudaMipmappedArray', 'uint64', 0, None, 'Pointer to the CUDA Mipmapped Array', {}, True, 0, False, ''),
('inputs:format', 'uint64', 0, None, 'Format', {}, True, 0, False, ''),
('inputs:height', 'uint', 0, None, 'Height', {}, True, 0, False, ''),
('inputs:hydraTime', 'double', 0, None, 'Hydra time in stage', {}, True, 0.0, False, ''),
('inputs:mipCount', 'uint', 0, None, 'Mip Count', {}, True, 0, False, ''),
('inputs:outputHeight', 'uint', 0, None, 'Requested output height', {ogn.MetadataKeys.DEFAULT: '0'}, True, 0, False, ''),
('inputs:outputWidth', 'uint', 0, None, 'Requested output width', {ogn.MetadataKeys.DEFAULT: '0'}, True, 0, False, ''),
('inputs:simTime', 'double', 0, None, 'Simulation time', {}, True, 0.0, False, ''),
('inputs:stream', 'uint64', 0, None, 'Pointer to the CUDA Stream', {}, True, 0, False, ''),
('inputs:width', 'uint', 0, None, 'Width', {}, True, 0, False, ''),
('outputs:data', 'float4[]', 0, None, 'Buffer array data', {ogn.MetadataKeys.MEMORY_TYPE: 'cuda', ogn.MetadataKeys.DEFAULT: '[]'}, True, [], False, ''),
('outputs:height', 'uint', 0, None, 'Buffer array height', {}, True, None, False, ''),
('outputs:hydraTime', 'double', 0, None, 'Hydra time in stage', {}, True, None, False, ''),
('outputs:simTime', 'double', 0, None, 'Simulation time', {}, True, None, False, ''),
('outputs:stream', 'uint64', 0, None, 'Pointer to the CUDA Stream', {}, True, None, False, ''),
('outputs:width', 'uint', 0, None, 'Buffer array width', {}, True, None, False, ''),
])
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaMipmappedArray", "format", "height", "hydraTime", "mipCount", "outputHeight", "outputWidth", "simTime", "stream", "width", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cudaMipmappedArray, self._attributes.format, self._attributes.height, self._attributes.hydraTime, self._attributes.mipCount, self._attributes.outputHeight, self._attributes.outputWidth, self._attributes.simTime, self._attributes.stream, self._attributes.width]
self._batchedReadValues = [0, 0, 0, 0.0, 0, 0, 0, 0.0, 0, 0]
@property
def cudaMipmappedArray(self):
return self._batchedReadValues[0]
@cudaMipmappedArray.setter
def cudaMipmappedArray(self, value):
self._batchedReadValues[0] = value
@property
def format(self):
return self._batchedReadValues[1]
@format.setter
def format(self, value):
self._batchedReadValues[1] = value
@property
def height(self):
return self._batchedReadValues[2]
@height.setter
def height(self, value):
self._batchedReadValues[2] = value
@property
def hydraTime(self):
return self._batchedReadValues[3]
@hydraTime.setter
def hydraTime(self, value):
self._batchedReadValues[3] = value
@property
def mipCount(self):
return self._batchedReadValues[4]
@mipCount.setter
def mipCount(self, value):
self._batchedReadValues[4] = value
@property
def outputHeight(self):
return self._batchedReadValues[5]
@outputHeight.setter
def outputHeight(self, value):
self._batchedReadValues[5] = value
@property
def outputWidth(self):
return self._batchedReadValues[6]
@outputWidth.setter
def outputWidth(self, value):
self._batchedReadValues[6] = value
@property
def simTime(self):
return self._batchedReadValues[7]
@simTime.setter
def simTime(self, value):
self._batchedReadValues[7] = value
@property
def stream(self):
return self._batchedReadValues[8]
@stream.setter
def stream(self, value):
self._batchedReadValues[8] = value
@property
def width(self):
return self._batchedReadValues[9]
@width.setter
def width(self, value):
self._batchedReadValues[9] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"height", "hydraTime", "simTime", "stream", "width", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self.data_size = 0
self._batchedWriteValues = { }
@property
def data(self):
data_view = og.AttributeValueHelper(self._attributes.data)
return data_view.get(reserved_element_count=self.data_size, on_gpu=True)
@data.setter
def data(self, value):
data_view = og.AttributeValueHelper(self._attributes.data)
data_view.set(value, on_gpu=True)
self.data_size = data_view.get_array_size()
@property
def height(self):
value = self._batchedWriteValues.get(self._attributes.height)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.height)
return data_view.get()
@height.setter
def height(self, value):
self._batchedWriteValues[self._attributes.height] = value
@property
def hydraTime(self):
value = self._batchedWriteValues.get(self._attributes.hydraTime)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.hydraTime)
return data_view.get()
@hydraTime.setter
def hydraTime(self, value):
self._batchedWriteValues[self._attributes.hydraTime] = value
@property
def simTime(self):
value = self._batchedWriteValues.get(self._attributes.simTime)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.simTime)
return data_view.get()
@simTime.setter
def simTime(self, value):
self._batchedWriteValues[self._attributes.simTime] = value
@property
def stream(self):
value = self._batchedWriteValues.get(self._attributes.stream)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.stream)
return data_view.get()
@stream.setter
def stream(self, value):
self._batchedWriteValues[self._attributes.stream] = value
@property
def width(self):
value = self._batchedWriteValues.get(self._attributes.width)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.width)
return data_view.get()
@width.setter
def width(self, value):
self._batchedWriteValues[self._attributes.width] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdTextureToLinearArrayDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdTextureToLinearArrayDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdTextureToLinearArrayDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 12,156 | Python | 41.957597 | 320 | 0.608342 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdNoOpDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdNoOp
Synthetic Data pass through node
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdNoOpDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdNoOp
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
Outputs:
outputs.exec
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec]
self._batchedReadValues = [None]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdNoOpDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdNoOpDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdNoOpDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 5,971 | Python | 46.776 | 111 | 0.640429 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdTestInstanceMappingDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdTestInstanceMapping
Synthetic Data node to test the instance mapping pipeline
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdTestInstanceMappingDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdTestInstanceMapping
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.instanceMapPtr
inputs.instancePrimPathPtr
inputs.minInstanceIndex
inputs.minSemanticIndex
inputs.numInstances
inputs.numSemantics
inputs.semanticLabelTokenPtrs
inputs.semanticLocalTransformPtr
inputs.semanticMapPtr
inputs.semanticPrimPathPtr
inputs.semanticWorldTransformPtr
inputs.stage
inputs.swhFrameNumber
inputs.testCaseIndex
Outputs:
outputs.exec
outputs.semanticFilterPredicate
outputs.success
Predefined Tokens:
tokens.simulation
tokens.postRender
tokens.onDemand
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:instanceMapPtr', 'uint64', 0, None, 'Array pointer of numInstances uint16_t containing the semantic index of the instance prim first semantic prim parent', {}, True, 0, False, ''),
('inputs:instancePrimPathPtr', 'uint64', 0, None, 'Array pointer of numInstances uint64_t containing the prim path tokens for every instance prims', {}, True, 0, False, ''),
('inputs:minInstanceIndex', 'uint', 0, None, 'Instance index of the first instance prim in the instance arrays', {}, True, 0, False, ''),
('inputs:minSemanticIndex', 'uint', 0, None, 'Semantic index of the first semantic prim in the semantic arrays', {}, True, 0, False, ''),
('inputs:numInstances', 'uint', 0, None, 'Number of instances prim in the instance arrays', {}, True, 0, False, ''),
('inputs:numSemantics', 'uint', 0, None, 'Number of semantic prim in the semantic arrays', {}, True, 0, False, ''),
('inputs:semanticLabelTokenPtrs', 'uint64[]', 0, None, 'Array containing for every input semantic filters the corresponding array pointer of numSemantics uint64_t representing the semantic label of the semantic prim', {}, True, [], False, ''),
('inputs:semanticLocalTransformPtr', 'uint64', 0, None, 'Array pointer of numSemantics 4x4 float matrices containing the transform from world to object space for every semantic prims', {}, True, 0, False, ''),
('inputs:semanticMapPtr', 'uint64', 0, None, 'Array pointer of numSemantics uint16_t containing the semantic index of the semantic prim first semantic prim parent', {}, True, 0, False, ''),
('inputs:semanticPrimPathPtr', 'uint64', 0, None, 'Array pointer of numSemantics uint32_t containing the prim part of the prim path tokens for every semantic prims', {}, True, 0, False, ''),
('inputs:semanticWorldTransformPtr', 'uint64', 0, None, 'Array pointer of numSemantics 4x4 float matrices containing the transform from local to world space for every semantic entity', {}, True, 0, False, ''),
('inputs:stage', 'token', 0, None, 'Stage in {simulation, postrender, ondemand}', {}, True, '', False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('inputs:testCaseIndex', 'int', 0, None, 'Test case index', {ogn.MetadataKeys.DEFAULT: '-1'}, True, -1, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:semanticFilterPredicate', 'token', 0, None, 'The semantic filter predicate : a disjunctive normal form of semantic type and label', {}, True, None, False, ''),
('outputs:success', 'bool', 0, None, 'Test value : false if failed', {}, True, None, False, ''),
])
class tokens:
simulation = "simulation"
postRender = "postRender"
onDemand = "onDemand"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "instanceMapPtr", "instancePrimPathPtr", "minInstanceIndex", "minSemanticIndex", "numInstances", "numSemantics", "semanticLocalTransformPtr", "semanticMapPtr", "semanticPrimPathPtr", "semanticWorldTransformPtr", "stage", "swhFrameNumber", "testCaseIndex", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.instanceMapPtr, self._attributes.instancePrimPathPtr, self._attributes.minInstanceIndex, self._attributes.minSemanticIndex, self._attributes.numInstances, self._attributes.numSemantics, self._attributes.semanticLocalTransformPtr, self._attributes.semanticMapPtr, self._attributes.semanticPrimPathPtr, self._attributes.semanticWorldTransformPtr, self._attributes.stage, self._attributes.swhFrameNumber, self._attributes.testCaseIndex]
self._batchedReadValues = [None, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, "", 0, -1]
@property
def semanticLabelTokenPtrs(self):
data_view = og.AttributeValueHelper(self._attributes.semanticLabelTokenPtrs)
return data_view.get()
@semanticLabelTokenPtrs.setter
def semanticLabelTokenPtrs(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.semanticLabelTokenPtrs)
data_view = og.AttributeValueHelper(self._attributes.semanticLabelTokenPtrs)
data_view.set(value)
self.semanticLabelTokenPtrs_size = data_view.get_array_size()
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def instanceMapPtr(self):
return self._batchedReadValues[1]
@instanceMapPtr.setter
def instanceMapPtr(self, value):
self._batchedReadValues[1] = value
@property
def instancePrimPathPtr(self):
return self._batchedReadValues[2]
@instancePrimPathPtr.setter
def instancePrimPathPtr(self, value):
self._batchedReadValues[2] = value
@property
def minInstanceIndex(self):
return self._batchedReadValues[3]
@minInstanceIndex.setter
def minInstanceIndex(self, value):
self._batchedReadValues[3] = value
@property
def minSemanticIndex(self):
return self._batchedReadValues[4]
@minSemanticIndex.setter
def minSemanticIndex(self, value):
self._batchedReadValues[4] = value
@property
def numInstances(self):
return self._batchedReadValues[5]
@numInstances.setter
def numInstances(self, value):
self._batchedReadValues[5] = value
@property
def numSemantics(self):
return self._batchedReadValues[6]
@numSemantics.setter
def numSemantics(self, value):
self._batchedReadValues[6] = value
@property
def semanticLocalTransformPtr(self):
return self._batchedReadValues[7]
@semanticLocalTransformPtr.setter
def semanticLocalTransformPtr(self, value):
self._batchedReadValues[7] = value
@property
def semanticMapPtr(self):
return self._batchedReadValues[8]
@semanticMapPtr.setter
def semanticMapPtr(self, value):
self._batchedReadValues[8] = value
@property
def semanticPrimPathPtr(self):
return self._batchedReadValues[9]
@semanticPrimPathPtr.setter
def semanticPrimPathPtr(self, value):
self._batchedReadValues[9] = value
@property
def semanticWorldTransformPtr(self):
return self._batchedReadValues[10]
@semanticWorldTransformPtr.setter
def semanticWorldTransformPtr(self, value):
self._batchedReadValues[10] = value
@property
def stage(self):
return self._batchedReadValues[11]
@stage.setter
def stage(self, value):
self._batchedReadValues[11] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[12]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[12] = value
@property
def testCaseIndex(self):
return self._batchedReadValues[13]
@testCaseIndex.setter
def testCaseIndex(self, value):
self._batchedReadValues[13] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "semanticFilterPredicate", "success", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def semanticFilterPredicate(self):
value = self._batchedWriteValues.get(self._attributes.semanticFilterPredicate)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticFilterPredicate)
return data_view.get()
@semanticFilterPredicate.setter
def semanticFilterPredicate(self, value):
self._batchedWriteValues[self._attributes.semanticFilterPredicate] = value
@property
def success(self):
value = self._batchedWriteValues.get(self._attributes.success)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.success)
return data_view.get()
@success.setter
def success(self, value):
self._batchedWriteValues[self._attributes.success] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdTestInstanceMappingDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdTestInstanceMappingDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdTestInstanceMappingDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 14,821 | Python | 46.812903 | 516 | 0.647257 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostSemantic3dBoundingBoxCameraProjection
Synthetic Data node to project 3d bounding boxes data in camera space.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostSemantic3dBoundingBoxCameraProjection
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cameraFisheyeParams
inputs.cameraModel
inputs.cameraNearFar
inputs.exec
inputs.gpu
inputs.instanceMappingInfoSDPtr
inputs.metersPerSceneUnit
inputs.renderProductResolution
inputs.rp
inputs.sdSemBBoxExtentCudaPtr
inputs.sdSemBBoxInfosCudaPtr
inputs.semanticWorldTransformSDCudaPtr
inputs.viewportNearFar
inputs.viewportResolution
Outputs:
outputs.exec
outputs.sdSemBBox3dCamCornersCudaPtr
outputs.sdSemBBox3dCamExtentCudaPtr
Predefined Tokens:
tokens.SemanticBoundingBox3DInfosSD
tokens.SemanticBoundingBox3DCamCornersSD
tokens.SemanticBoundingBox3DCamExtentSD
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cameraFisheyeParams', 'float[]', 0, None, 'Camera fisheye projection parameters', {}, True, [], False, ''),
('inputs:cameraModel', 'int', 0, None, 'Camera model (pinhole or fisheye models)', {}, True, 0, False, ''),
('inputs:cameraNearFar', 'float2', 0, None, 'Camera near/far clipping range', {}, True, [0.0, 0.0], False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:instanceMappingInfoSDPtr', 'uint64', 0, None, 'uint buffer pointer containing the following information : [numInstances, minInstanceId, numSemantics, minSemanticId, numProtoSemantic]', {}, True, 0, False, ''),
('inputs:metersPerSceneUnit', 'float', 0, None, 'Scene units to meters scale', {ogn.MetadataKeys.DEFAULT: '0.01'}, True, 0.01, False, ''),
('inputs:renderProductResolution', 'int2', 0, None, 'RenderProduct resolution', {}, True, [0, 0], False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'Pointer to render product for this view', {}, True, 0, False, ''),
('inputs:sdSemBBoxExtentCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the extent of the bounding boxes as a float4=(u_min,v_min,u_max,v_max) for 2D or a float6=(xmin,ymin,zmin,xmax,ymax,zmax) in object space for 3D', {}, True, 0, False, ''),
('inputs:sdSemBBoxInfosCudaPtr', 'uint64', 0, None, 'Cuda buffer containing valid bounding boxes infos', {}, True, 0, False, ''),
('inputs:semanticWorldTransformSDCudaPtr', 'uint64', 0, None, 'cuda float44 buffer pointer of size numSemantics containing the world semantic transform', {}, True, 0, False, ''),
('inputs:viewportNearFar', 'float2', 0, None, 'near and far plane (in scene units) used to clip the 3d bounding boxes.', {ogn.MetadataKeys.DEFAULT: '[1.0, 10000000.0]'}, True, [1.0, 10000000.0], False, ''),
('inputs:viewportResolution', 'int2', 0, None, 'viewport width and height (in pixels) used to clip the 3d bounding boxes.', {ogn.MetadataKeys.DEFAULT: '[65536, 65536]'}, True, [65536, 65536], False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:sdSemBBox3dCamCornersCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the projection of the 3d bounding boxes on the camera plane represented as a float4=(u,v,z,a) for each bounding box corners', {}, True, None, False, ''),
('outputs:sdSemBBox3dCamExtentCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the 2d extent of the 3d bounding boxes on the camera plane represented as a float6=(u_min,u_max,v_min,v_max,z_min,z_max)', {}, True, None, False, ''),
])
class tokens:
SemanticBoundingBox3DInfosSD = "SemanticBoundingBox3DInfosSD"
SemanticBoundingBox3DCamCornersSD = "SemanticBoundingBox3DCamCornersSD"
SemanticBoundingBox3DCamExtentSD = "SemanticBoundingBox3DCamExtentSD"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cameraModel", "cameraNearFar", "exec", "gpu", "instanceMappingInfoSDPtr", "metersPerSceneUnit", "renderProductResolution", "rp", "sdSemBBoxExtentCudaPtr", "sdSemBBoxInfosCudaPtr", "semanticWorldTransformSDCudaPtr", "viewportNearFar", "viewportResolution", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cameraModel, self._attributes.cameraNearFar, self._attributes.exec, self._attributes.gpu, self._attributes.instanceMappingInfoSDPtr, self._attributes.metersPerSceneUnit, self._attributes.renderProductResolution, self._attributes.rp, self._attributes.sdSemBBoxExtentCudaPtr, self._attributes.sdSemBBoxInfosCudaPtr, self._attributes.semanticWorldTransformSDCudaPtr, self._attributes.viewportNearFar, self._attributes.viewportResolution]
self._batchedReadValues = [0, [0.0, 0.0], None, 0, 0, 0.01, [0, 0], 0, 0, 0, 0, [1.0, 10000000.0], [65536, 65536]]
@property
def cameraFisheyeParams(self):
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
return data_view.get()
@cameraFisheyeParams.setter
def cameraFisheyeParams(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.cameraFisheyeParams)
data_view = og.AttributeValueHelper(self._attributes.cameraFisheyeParams)
data_view.set(value)
self.cameraFisheyeParams_size = data_view.get_array_size()
@property
def cameraModel(self):
return self._batchedReadValues[0]
@cameraModel.setter
def cameraModel(self, value):
self._batchedReadValues[0] = value
@property
def cameraNearFar(self):
return self._batchedReadValues[1]
@cameraNearFar.setter
def cameraNearFar(self, value):
self._batchedReadValues[1] = value
@property
def exec(self):
return self._batchedReadValues[2]
@exec.setter
def exec(self, value):
self._batchedReadValues[2] = value
@property
def gpu(self):
return self._batchedReadValues[3]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[3] = value
@property
def instanceMappingInfoSDPtr(self):
return self._batchedReadValues[4]
@instanceMappingInfoSDPtr.setter
def instanceMappingInfoSDPtr(self, value):
self._batchedReadValues[4] = value
@property
def metersPerSceneUnit(self):
return self._batchedReadValues[5]
@metersPerSceneUnit.setter
def metersPerSceneUnit(self, value):
self._batchedReadValues[5] = value
@property
def renderProductResolution(self):
return self._batchedReadValues[6]
@renderProductResolution.setter
def renderProductResolution(self, value):
self._batchedReadValues[6] = value
@property
def rp(self):
return self._batchedReadValues[7]
@rp.setter
def rp(self, value):
self._batchedReadValues[7] = value
@property
def sdSemBBoxExtentCudaPtr(self):
return self._batchedReadValues[8]
@sdSemBBoxExtentCudaPtr.setter
def sdSemBBoxExtentCudaPtr(self, value):
self._batchedReadValues[8] = value
@property
def sdSemBBoxInfosCudaPtr(self):
return self._batchedReadValues[9]
@sdSemBBoxInfosCudaPtr.setter
def sdSemBBoxInfosCudaPtr(self, value):
self._batchedReadValues[9] = value
@property
def semanticWorldTransformSDCudaPtr(self):
return self._batchedReadValues[10]
@semanticWorldTransformSDCudaPtr.setter
def semanticWorldTransformSDCudaPtr(self, value):
self._batchedReadValues[10] = value
@property
def viewportNearFar(self):
return self._batchedReadValues[11]
@viewportNearFar.setter
def viewportNearFar(self, value):
self._batchedReadValues[11] = value
@property
def viewportResolution(self):
return self._batchedReadValues[12]
@viewportResolution.setter
def viewportResolution(self, value):
self._batchedReadValues[12] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "sdSemBBox3dCamCornersCudaPtr", "sdSemBBox3dCamExtentCudaPtr", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def sdSemBBox3dCamCornersCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.sdSemBBox3dCamCornersCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdSemBBox3dCamCornersCudaPtr)
return data_view.get()
@sdSemBBox3dCamCornersCudaPtr.setter
def sdSemBBox3dCamCornersCudaPtr(self, value):
self._batchedWriteValues[self._attributes.sdSemBBox3dCamCornersCudaPtr] = value
@property
def sdSemBBox3dCamExtentCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.sdSemBBox3dCamExtentCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdSemBBox3dCamExtentCudaPtr)
return data_view.get()
@sdSemBBox3dCamExtentCudaPtr.setter
def sdSemBBox3dCamExtentCudaPtr(self, value):
self._batchedWriteValues[self._attributes.sdSemBBox3dCamExtentCudaPtr] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 15,079 | Python | 49.266667 | 494 | 0.659195 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdSimInstanceMappingDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdSimInstanceMapping
Synthetic Data node to update and cache the instance mapping data
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdSimInstanceMappingDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdSimInstanceMapping
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.needTransform
inputs.semanticFilterPredicate
Outputs:
outputs.exec
outputs.semanticFilterPredicate
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:needTransform', 'bool', 0, None, 'If true compute the semantic entities world and object transforms', {ogn.MetadataKeys.DEFAULT: 'true'}, True, True, False, ''),
('inputs:semanticFilterPredicate', 'token', 0, None, 'The semantic filter predicate : a disjunctive normal form of semantic type and label', {ogn.MetadataKeys.DEFAULT: '"*:*"'}, True, '*:*', False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:semanticFilterPredicate', 'token', 0, None, 'The semantic filter predicate in normalized form', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"needTransform", "semanticFilterPredicate", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.needTransform, self._attributes.semanticFilterPredicate]
self._batchedReadValues = [True, "*:*"]
@property
def needTransform(self):
return self._batchedReadValues[0]
@needTransform.setter
def needTransform(self, value):
self._batchedReadValues[0] = value
@property
def semanticFilterPredicate(self):
return self._batchedReadValues[1]
@semanticFilterPredicate.setter
def semanticFilterPredicate(self, value):
self._batchedReadValues[1] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "semanticFilterPredicate", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def semanticFilterPredicate(self):
value = self._batchedWriteValues.get(self._attributes.semanticFilterPredicate)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticFilterPredicate)
return data_view.get()
@semanticFilterPredicate.setter
def semanticFilterPredicate(self, value):
self._batchedWriteValues[self._attributes.semanticFilterPredicate] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdSimInstanceMappingDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdSimInstanceMappingDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdSimInstanceMappingDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 7,499 | Python | 49.33557 | 210 | 0.65342 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdRenderVarToRawArrayDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdRenderVarToRawArray
Synthetic Data action node to copy the input rendervar into an output raw array
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdRenderVarToRawArrayDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdRenderVarToRawArray
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cudaStream
inputs.exec
inputs.renderResults
inputs.renderVar
inputs.swhFrameNumber
Outputs:
outputs.bufferSize
outputs.cudaStream
outputs.data
outputs.exec
outputs.format
outputs.height
outputs.swhFrameNumber
outputs.width
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cudaStream', 'uint64', 0, None, 'Pointer to the CUDA stream', {}, True, 0, False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:renderResults', 'uint64', 0, None, 'Render results pointer', {}, True, 0, False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the renderVar', {}, True, '', False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:bufferSize', 'uint64', 0, None, 'Size (in bytes) of the buffer (0 if the input is a texture)', {}, True, None, False, ''),
('outputs:cudaStream', 'uint64', 0, None, 'Pointer to the CUDA stream', {}, True, None, False, ''),
('outputs:data', 'uchar[]', 0, None, 'Buffer array data', {ogn.MetadataKeys.MEMORY_TYPE: 'any', ogn.MetadataKeys.DEFAULT: '[]'}, True, [], False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:format', 'uint64', 0, None, 'Format', {}, True, None, False, ''),
('outputs:height', 'uint', 0, None, 'Height (0 if the input is a buffer)', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Frame number', {}, True, None, False, ''),
('outputs:width', 'uint', 0, None, 'Width (0 if the input is a buffer)', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaStream", "exec", "renderResults", "renderVar", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cudaStream, self._attributes.exec, self._attributes.renderResults, self._attributes.renderVar, self._attributes.swhFrameNumber]
self._batchedReadValues = [0, None, 0, "", 0]
@property
def cudaStream(self):
return self._batchedReadValues[0]
@cudaStream.setter
def cudaStream(self, value):
self._batchedReadValues[0] = value
@property
def exec(self):
return self._batchedReadValues[1]
@exec.setter
def exec(self, value):
self._batchedReadValues[1] = value
@property
def renderResults(self):
return self._batchedReadValues[2]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[2] = value
@property
def renderVar(self):
return self._batchedReadValues[3]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[3] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[4]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[4] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"bufferSize", "cudaStream", "exec", "format", "height", "swhFrameNumber", "width", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self.data_size = 0
self._batchedWriteValues = { }
class __data:
def __init__(self, parent):
self._parent = parent
@property
def cpu(self):
data_view = og.AttributeValueHelper(self._parent._attributes.data)
return data_view.get(reserved_element_count=self._parent.data_size)
@cpu.setter
def cpu(self, value):
data_view = og.AttributeValueHelper(self._parent._attributes.cpu)
data_view.set(value)
self._parent.cpu_size = data_view.get_array_size()
@property
def gpu(self):
data_view = og.AttributeValueHelper(self._parent._attributes.data)
data_view.gpu_ptr_kind = og.PtrToPtrKind.CPU
return data_view.get(reserved_element_count=self._parent.data_size, on_gpu=True)
@gpu.setter
def gpu(self, value):
data_view = og.AttributeValueHelper(self._parent._attributes.gpu)
data_view.set(value)
self._parent.gpu_size = data_view.get_array_size()
@property
def data(self):
return self.__class__.__data(self)
@property
def bufferSize(self):
value = self._batchedWriteValues.get(self._attributes.bufferSize)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.bufferSize)
return data_view.get()
@bufferSize.setter
def bufferSize(self, value):
self._batchedWriteValues[self._attributes.bufferSize] = value
@property
def cudaStream(self):
value = self._batchedWriteValues.get(self._attributes.cudaStream)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaStream)
return data_view.get()
@cudaStream.setter
def cudaStream(self, value):
self._batchedWriteValues[self._attributes.cudaStream] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def format(self):
value = self._batchedWriteValues.get(self._attributes.format)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.format)
return data_view.get()
@format.setter
def format(self, value):
self._batchedWriteValues[self._attributes.format] = value
@property
def height(self):
value = self._batchedWriteValues.get(self._attributes.height)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.height)
return data_view.get()
@height.setter
def height(self, value):
self._batchedWriteValues[self._attributes.height] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
@property
def width(self):
value = self._batchedWriteValues.get(self._attributes.width)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.width)
return data_view.get()
@width.setter
def width(self, value):
self._batchedWriteValues[self._attributes.width] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdRenderVarToRawArrayDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdRenderVarToRawArrayDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdRenderVarToRawArrayDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 12,715 | Python | 42.848276 | 187 | 0.606606 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdOnNewFrameDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdOnNewFrame
Synthetic Data postprocess node to execute pipeline after the NewFrame event has been received
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdOnNewFrameDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdOnNewFrame
Class Members:
node: Node being evaluated
Attribute Value Properties:
Outputs:
outputs.cudaStream
outputs.exec
outputs.renderProductDataPtrs
outputs.renderProductPaths
outputs.swhFrameNumber
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('outputs:cudaStream', 'uint64', 0, None, 'Cuda stream', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, None, 'Executes for each newFrame event received', {}, True, None, False, ''),
('outputs:renderProductDataPtrs', 'uint64[]', 0, None, 'HydraRenderProduct data pointer.', {}, True, None, False, ''),
('outputs:renderProductPaths', 'token[]', 0, None, 'Render product path tokens.', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = { }
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = []
self._batchedReadValues = []
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaStream", "exec", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self.renderProductDataPtrs_size = None
self.renderProductPaths_size = None
self._batchedWriteValues = { }
@property
def renderProductDataPtrs(self):
data_view = og.AttributeValueHelper(self._attributes.renderProductDataPtrs)
return data_view.get(reserved_element_count=self.renderProductDataPtrs_size)
@renderProductDataPtrs.setter
def renderProductDataPtrs(self, value):
data_view = og.AttributeValueHelper(self._attributes.renderProductDataPtrs)
data_view.set(value)
self.renderProductDataPtrs_size = data_view.get_array_size()
@property
def renderProductPaths(self):
data_view = og.AttributeValueHelper(self._attributes.renderProductPaths)
return data_view.get(reserved_element_count=self.renderProductPaths_size)
@renderProductPaths.setter
def renderProductPaths(self, value):
data_view = og.AttributeValueHelper(self._attributes.renderProductPaths)
data_view.set(value)
self.renderProductPaths_size = data_view.get_array_size()
@property
def cudaStream(self):
value = self._batchedWriteValues.get(self._attributes.cudaStream)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaStream)
return data_view.get()
@cudaStream.setter
def cudaStream(self, value):
self._batchedWriteValues[self._attributes.cudaStream] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdOnNewFrameDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdOnNewFrameDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdOnNewFrameDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 7,864 | Python | 48.15625 | 126 | 0.652594 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostInstanceMappingDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostInstanceMapping
Synthetic Data node to compute and store scene instances semantic hierarchy information
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdPostInstanceMappingDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostInstanceMapping
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.gpu
inputs.rp
inputs.semanticFilterName
inputs.swhFrameNumber
Outputs:
outputs.exec
outputs.instanceMapSDCudaPtr
outputs.instanceMappingInfoSDPtr
outputs.instancePrimTokenSDCudaPtr
outputs.semanticLabelTokenSDCudaPtr
outputs.semanticLocalTransformSDCudaPtr
outputs.semanticMapSDCudaPtr
outputs.semanticPrimTokenSDCudaPtr
outputs.semanticWorldTransformSDCudaPtr
Predefined Tokens:
tokens.InstanceMappingInfoSDhost
tokens.SemanticMapSD
tokens.SemanticMapSDhost
tokens.SemanticPrimTokenSD
tokens.SemanticPrimTokenSDhost
tokens.InstanceMapSD
tokens.InstanceMapSDhost
tokens.InstancePrimTokenSD
tokens.InstancePrimTokenSDhost
tokens.SemanticLabelTokenSD
tokens.SemanticLabelTokenSDhost
tokens.SemanticLocalTransformSD
tokens.SemanticLocalTransformSDhost
tokens.SemanticWorldTransformSD
tokens.SemanticWorldTransformSDhost
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'Pointer to render product for this view', {}, True, 0, False, ''),
('inputs:semanticFilterName', 'token', 0, None, 'Name of the semantic filter to apply to the semanticLabelToken', {ogn.MetadataKeys.DEFAULT: '"default"'}, True, 'default', False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:instanceMapSDCudaPtr', 'uint64', 0, None, 'cuda uint16_t buffer pointer of size numInstances containing the instance parent semantic index', {}, True, None, False, ''),
('outputs:instanceMappingInfoSDPtr', 'uint64', 0, None, 'uint buffer pointer containing the following information : [numInstances, minInstanceId, numSemantics, minSemanticId, numProtoSemantic]', {}, True, None, False, ''),
('outputs:instancePrimTokenSDCudaPtr', 'uint64', 0, None, 'cuda uint64_t buffer pointer of size numInstances containing the instance path token', {}, True, None, False, ''),
('outputs:semanticLabelTokenSDCudaPtr', 'uint64', 0, None, 'cuda uint64_t buffer pointer of size numSemantics containing the semantic label token', {}, True, None, False, ''),
('outputs:semanticLocalTransformSDCudaPtr', 'uint64', 0, None, 'cuda float44 buffer pointer of size numSemantics containing the local semantic transform', {}, True, None, False, ''),
('outputs:semanticMapSDCudaPtr', 'uint64', 0, None, 'cuda uint16_t buffer pointer of size numSemantics containing the semantic parent semantic index', {}, True, None, False, ''),
('outputs:semanticPrimTokenSDCudaPtr', 'uint64', 0, None, 'cuda uint32_t buffer pointer of size numSemantics containing the prim part of the semantic path token', {}, True, None, False, ''),
('outputs:semanticWorldTransformSDCudaPtr', 'uint64', 0, None, 'cuda float44 buffer pointer of size numSemantics containing the world semantic transform', {}, True, None, False, ''),
])
class tokens:
InstanceMappingInfoSDhost = "InstanceMappingInfoSDhost"
SemanticMapSD = "SemanticMapSD"
SemanticMapSDhost = "SemanticMapSDhost"
SemanticPrimTokenSD = "SemanticPrimTokenSD"
SemanticPrimTokenSDhost = "SemanticPrimTokenSDhost"
InstanceMapSD = "InstanceMapSD"
InstanceMapSDhost = "InstanceMapSDhost"
InstancePrimTokenSD = "InstancePrimTokenSD"
InstancePrimTokenSDhost = "InstancePrimTokenSDhost"
SemanticLabelTokenSD = "SemanticLabelTokenSD"
SemanticLabelTokenSDhost = "SemanticLabelTokenSDhost"
SemanticLocalTransformSD = "SemanticLocalTransformSD"
SemanticLocalTransformSDhost = "SemanticLocalTransformSDhost"
SemanticWorldTransformSD = "SemanticWorldTransformSD"
SemanticWorldTransformSDhost = "SemanticWorldTransformSDhost"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "gpu", "rp", "semanticFilterName", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.gpu, self._attributes.rp, self._attributes.semanticFilterName, self._attributes.swhFrameNumber]
self._batchedReadValues = [None, 0, 0, "default", 0]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def gpu(self):
return self._batchedReadValues[1]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[1] = value
@property
def rp(self):
return self._batchedReadValues[2]
@rp.setter
def rp(self, value):
self._batchedReadValues[2] = value
@property
def semanticFilterName(self):
return self._batchedReadValues[3]
@semanticFilterName.setter
def semanticFilterName(self, value):
self._batchedReadValues[3] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[4]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[4] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "instanceMapSDCudaPtr", "instanceMappingInfoSDPtr", "instancePrimTokenSDCudaPtr", "semanticLabelTokenSDCudaPtr", "semanticLocalTransformSDCudaPtr", "semanticMapSDCudaPtr", "semanticPrimTokenSDCudaPtr", "semanticWorldTransformSDCudaPtr", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def instanceMapSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.instanceMapSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.instanceMapSDCudaPtr)
return data_view.get()
@instanceMapSDCudaPtr.setter
def instanceMapSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.instanceMapSDCudaPtr] = value
@property
def instanceMappingInfoSDPtr(self):
value = self._batchedWriteValues.get(self._attributes.instanceMappingInfoSDPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.instanceMappingInfoSDPtr)
return data_view.get()
@instanceMappingInfoSDPtr.setter
def instanceMappingInfoSDPtr(self, value):
self._batchedWriteValues[self._attributes.instanceMappingInfoSDPtr] = value
@property
def instancePrimTokenSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.instancePrimTokenSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.instancePrimTokenSDCudaPtr)
return data_view.get()
@instancePrimTokenSDCudaPtr.setter
def instancePrimTokenSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.instancePrimTokenSDCudaPtr] = value
@property
def semanticLabelTokenSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticLabelTokenSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticLabelTokenSDCudaPtr)
return data_view.get()
@semanticLabelTokenSDCudaPtr.setter
def semanticLabelTokenSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.semanticLabelTokenSDCudaPtr] = value
@property
def semanticLocalTransformSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticLocalTransformSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticLocalTransformSDCudaPtr)
return data_view.get()
@semanticLocalTransformSDCudaPtr.setter
def semanticLocalTransformSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.semanticLocalTransformSDCudaPtr] = value
@property
def semanticMapSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticMapSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticMapSDCudaPtr)
return data_view.get()
@semanticMapSDCudaPtr.setter
def semanticMapSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.semanticMapSDCudaPtr] = value
@property
def semanticPrimTokenSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticPrimTokenSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticPrimTokenSDCudaPtr)
return data_view.get()
@semanticPrimTokenSDCudaPtr.setter
def semanticPrimTokenSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.semanticPrimTokenSDCudaPtr] = value
@property
def semanticWorldTransformSDCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticWorldTransformSDCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticWorldTransformSDCudaPtr)
return data_view.get()
@semanticWorldTransformSDCudaPtr.setter
def semanticWorldTransformSDCudaPtr(self, value):
self._batchedWriteValues[self._attributes.semanticWorldTransformSDCudaPtr] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostInstanceMappingDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostInstanceMappingDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostInstanceMappingDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 15,781 | Python | 48.628931 | 299 | 0.662949 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdLinearArrayToTextureDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdLinearArrayToTexture
Synthetic Data node to copy the input buffer array into a texture for visualization
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdLinearArrayToTextureDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdLinearArrayToTexture
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.data
inputs.exec
inputs.height
inputs.sdDisplayCudaMipmappedArray
inputs.sdDisplayFormat
inputs.sdDisplayHeight
inputs.sdDisplayStream
inputs.sdDisplayWidth
inputs.stream
inputs.width
Outputs:
outputs.cudaPtr
outputs.exec
outputs.format
outputs.handlePtr
outputs.height
outputs.stream
outputs.width
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:data', 'float4[]', 0, None, 'Buffer array data', {ogn.MetadataKeys.MEMORY_TYPE: 'cuda'}, True, [], False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:height', 'uint', 0, None, 'Buffer array height', {}, True, 0, False, ''),
('inputs:sdDisplayCudaMipmappedArray', 'uint64', 0, None, 'Visualization texture CUDA mipmapped array pointer', {}, True, 0, False, ''),
('inputs:sdDisplayFormat', 'uint64', 0, None, 'Visualization texture format', {}, True, 0, False, ''),
('inputs:sdDisplayHeight', 'uint', 0, None, 'Visualization texture Height', {}, True, 0, False, ''),
('inputs:sdDisplayStream', 'uint64', 0, None, 'Visualization texture CUDA stream pointer', {}, True, 0, False, ''),
('inputs:sdDisplayWidth', 'uint', 0, None, 'Visualization texture width', {}, True, 0, False, ''),
('inputs:stream', 'uint64', 0, None, 'Pointer to the CUDA Stream', {}, True, 0, False, ''),
('inputs:width', 'uint', 0, None, 'Buffer array width', {}, True, 0, False, ''),
('outputs:cudaPtr', 'uint64', 0, None, 'Display texture CUDA pointer', {}, True, None, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:format', 'uint64', 0, None, 'Display texture format', {}, True, None, False, ''),
('outputs:handlePtr', 'uint64', 0, None, 'Display texture handle reference', {}, True, None, False, ''),
('outputs:height', 'uint', 0, None, 'Display texture height', {}, True, None, False, ''),
('outputs:stream', 'uint64', 0, None, 'Output texture CUDA stream pointer', {}, True, None, False, ''),
('outputs:width', 'uint', 0, None, 'Display texture width', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "height", "sdDisplayCudaMipmappedArray", "sdDisplayFormat", "sdDisplayHeight", "sdDisplayStream", "sdDisplayWidth", "stream", "width", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.height, self._attributes.sdDisplayCudaMipmappedArray, self._attributes.sdDisplayFormat, self._attributes.sdDisplayHeight, self._attributes.sdDisplayStream, self._attributes.sdDisplayWidth, self._attributes.stream, self._attributes.width]
self._batchedReadValues = [None, 0, 0, 0, 0, 0, 0, 0, 0]
@property
def data(self):
data_view = og.AttributeValueHelper(self._attributes.data)
return data_view.get(on_gpu=True)
@data.setter
def data(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.data)
data_view = og.AttributeValueHelper(self._attributes.data)
data_view.set(value, on_gpu=True)
self.data_size = data_view.get_array_size()
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def height(self):
return self._batchedReadValues[1]
@height.setter
def height(self, value):
self._batchedReadValues[1] = value
@property
def sdDisplayCudaMipmappedArray(self):
return self._batchedReadValues[2]
@sdDisplayCudaMipmappedArray.setter
def sdDisplayCudaMipmappedArray(self, value):
self._batchedReadValues[2] = value
@property
def sdDisplayFormat(self):
return self._batchedReadValues[3]
@sdDisplayFormat.setter
def sdDisplayFormat(self, value):
self._batchedReadValues[3] = value
@property
def sdDisplayHeight(self):
return self._batchedReadValues[4]
@sdDisplayHeight.setter
def sdDisplayHeight(self, value):
self._batchedReadValues[4] = value
@property
def sdDisplayStream(self):
return self._batchedReadValues[5]
@sdDisplayStream.setter
def sdDisplayStream(self, value):
self._batchedReadValues[5] = value
@property
def sdDisplayWidth(self):
return self._batchedReadValues[6]
@sdDisplayWidth.setter
def sdDisplayWidth(self, value):
self._batchedReadValues[6] = value
@property
def stream(self):
return self._batchedReadValues[7]
@stream.setter
def stream(self, value):
self._batchedReadValues[7] = value
@property
def width(self):
return self._batchedReadValues[8]
@width.setter
def width(self, value):
self._batchedReadValues[8] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaPtr", "exec", "format", "handlePtr", "height", "stream", "width", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def cudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.cudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaPtr)
return data_view.get()
@cudaPtr.setter
def cudaPtr(self, value):
self._batchedWriteValues[self._attributes.cudaPtr] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def format(self):
value = self._batchedWriteValues.get(self._attributes.format)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.format)
return data_view.get()
@format.setter
def format(self, value):
self._batchedWriteValues[self._attributes.format] = value
@property
def handlePtr(self):
value = self._batchedWriteValues.get(self._attributes.handlePtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.handlePtr)
return data_view.get()
@handlePtr.setter
def handlePtr(self, value):
self._batchedWriteValues[self._attributes.handlePtr] = value
@property
def height(self):
value = self._batchedWriteValues.get(self._attributes.height)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.height)
return data_view.get()
@height.setter
def height(self, value):
self._batchedWriteValues[self._attributes.height] = value
@property
def stream(self):
value = self._batchedWriteValues.get(self._attributes.stream)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.stream)
return data_view.get()
@stream.setter
def stream(self, value):
self._batchedWriteValues[self._attributes.stream] = value
@property
def width(self):
value = self._batchedWriteValues.get(self._attributes.width)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.width)
return data_view.get()
@width.setter
def width(self, value):
self._batchedWriteValues[self._attributes.width] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdLinearArrayToTextureDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdLinearArrayToTextureDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdLinearArrayToTextureDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 13,538 | Python | 42.533762 | 320 | 0.613385 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostSemanticBoundingBoxDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostSemanticBoundingBox
Synthetic Data node to compute the bounding boxes of the scene semantic entities.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdPostSemanticBoundingBoxDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostSemanticBoundingBox
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.gpu
inputs.instanceMapSDCudaPtr
inputs.instanceMappingInfoSDPtr
inputs.renderProductResolution
inputs.renderVar
inputs.rp
inputs.semanticLocalTransformSDCudaPtr
inputs.semanticMapSDCudaPtr
Outputs:
outputs.exec
outputs.sdSemBBoxExtentCudaPtr
outputs.sdSemBBoxInfosCudaPtr
Predefined Tokens:
tokens.BoundingBox2DLooseSD
tokens.BoundingBox2DTightSD
tokens.SemanticBoundingBox2DExtentLooseSD
tokens.SemanticBoundingBox2DInfosLooseSD
tokens.SemanticBoundingBox2DExtentTightSD
tokens.SemanticBoundingBox2DInfosTightSD
tokens.BoundingBox3DSD
tokens.SemanticBoundingBox3DExtentSD
tokens.SemanticBoundingBox3DInfosSD
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:gpu', 'uint64', 0, 'gpuFoundations', 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:instanceMapSDCudaPtr', 'uint64', 0, None, 'cuda uint16_t buffer pointer of size numInstances containing the instance parent semantic index', {}, True, 0, False, ''),
('inputs:instanceMappingInfoSDPtr', 'uint64', 0, None, 'uint buffer pointer containing the following information : [numInstances, minInstanceId, numSemantics, minSemanticId, numProtoSemantic]', {}, True, 0, False, ''),
('inputs:renderProductResolution', 'int2', 0, None, 'RenderProduct resolution', {}, True, [0, 0], False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the BoundingBox RenderVar to process', {}, True, '', False, ''),
('inputs:rp', 'uint64', 0, 'renderProduct', 'Pointer to render product for this view', {}, True, 0, False, ''),
('inputs:semanticLocalTransformSDCudaPtr', 'uint64', 0, None, 'cuda float44 buffer pointer of size numSemantics containing the local semantic transform', {}, True, 0, False, ''),
('inputs:semanticMapSDCudaPtr', 'uint64', 0, None, 'cuda uint16_t buffer pointer of size numSemantics containing the semantic parent semantic index', {}, True, 0, False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:sdSemBBoxExtentCudaPtr', 'uint64', 0, None, 'Cuda buffer containing the extent of the bounding boxes as a float4=(u_min,v_min,u_max,v_max) for 2D or a float6=(xmin,ymin,zmin,xmax,ymax,zmax) in object space for 3D', {}, True, None, False, ''),
('outputs:sdSemBBoxInfosCudaPtr', 'uint64', 0, None, 'Cuda buffer containing valid bounding boxes infos', {}, True, None, False, ''),
])
class tokens:
BoundingBox2DLooseSD = "BoundingBox2DLooseSD"
BoundingBox2DTightSD = "BoundingBox2DTightSD"
SemanticBoundingBox2DExtentLooseSD = "SemanticBoundingBox2DExtentLooseSD"
SemanticBoundingBox2DInfosLooseSD = "SemanticBoundingBox2DInfosLooseSD"
SemanticBoundingBox2DExtentTightSD = "SemanticBoundingBox2DExtentTightSD"
SemanticBoundingBox2DInfosTightSD = "SemanticBoundingBox2DInfosTightSD"
BoundingBox3DSD = "BoundingBox3DSD"
SemanticBoundingBox3DExtentSD = "SemanticBoundingBox3DExtentSD"
SemanticBoundingBox3DInfosSD = "SemanticBoundingBox3DInfosSD"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "gpu", "instanceMapSDCudaPtr", "instanceMappingInfoSDPtr", "renderProductResolution", "renderVar", "rp", "semanticLocalTransformSDCudaPtr", "semanticMapSDCudaPtr", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.gpu, self._attributes.instanceMapSDCudaPtr, self._attributes.instanceMappingInfoSDPtr, self._attributes.renderProductResolution, self._attributes.renderVar, self._attributes.rp, self._attributes.semanticLocalTransformSDCudaPtr, self._attributes.semanticMapSDCudaPtr]
self._batchedReadValues = [None, 0, 0, 0, [0, 0], "", 0, 0, 0]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def gpu(self):
return self._batchedReadValues[1]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[1] = value
@property
def instanceMapSDCudaPtr(self):
return self._batchedReadValues[2]
@instanceMapSDCudaPtr.setter
def instanceMapSDCudaPtr(self, value):
self._batchedReadValues[2] = value
@property
def instanceMappingInfoSDPtr(self):
return self._batchedReadValues[3]
@instanceMappingInfoSDPtr.setter
def instanceMappingInfoSDPtr(self, value):
self._batchedReadValues[3] = value
@property
def renderProductResolution(self):
return self._batchedReadValues[4]
@renderProductResolution.setter
def renderProductResolution(self, value):
self._batchedReadValues[4] = value
@property
def renderVar(self):
return self._batchedReadValues[5]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[5] = value
@property
def rp(self):
return self._batchedReadValues[6]
@rp.setter
def rp(self, value):
self._batchedReadValues[6] = value
@property
def semanticLocalTransformSDCudaPtr(self):
return self._batchedReadValues[7]
@semanticLocalTransformSDCudaPtr.setter
def semanticLocalTransformSDCudaPtr(self, value):
self._batchedReadValues[7] = value
@property
def semanticMapSDCudaPtr(self):
return self._batchedReadValues[8]
@semanticMapSDCudaPtr.setter
def semanticMapSDCudaPtr(self, value):
self._batchedReadValues[8] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "sdSemBBoxExtentCudaPtr", "sdSemBBoxInfosCudaPtr", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def sdSemBBoxExtentCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.sdSemBBoxExtentCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdSemBBoxExtentCudaPtr)
return data_view.get()
@sdSemBBoxExtentCudaPtr.setter
def sdSemBBoxExtentCudaPtr(self, value):
self._batchedWriteValues[self._attributes.sdSemBBoxExtentCudaPtr] = value
@property
def sdSemBBoxInfosCudaPtr(self):
value = self._batchedWriteValues.get(self._attributes.sdSemBBoxInfosCudaPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.sdSemBBoxInfosCudaPtr)
return data_view.get()
@sdSemBBoxInfosCudaPtr.setter
def sdSemBBoxInfosCudaPtr(self, value):
self._batchedWriteValues[self._attributes.sdSemBBoxInfosCudaPtr] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostSemanticBoundingBoxDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostSemanticBoundingBoxDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostSemanticBoundingBoxDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 12,640 | Python | 48.18677 | 349 | 0.662104 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdInstanceMappingPtrDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdInstanceMappingPtr
Synthetic Data node to expose the scene instances semantic hierarchy information
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
import numpy
class OgnSdInstanceMappingPtrDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdInstanceMappingPtr
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.cudaPtr
inputs.exec
inputs.renderResults
inputs.semanticFilerTokens
inputs.swhFrameNumber
Outputs:
outputs.exec
outputs.instanceMapPtr
outputs.instancePrimPathPtr
outputs.minInstanceIndex
outputs.minSemanticIndex
outputs.numInstances
outputs.numSemantics
outputs.semanticLabelTokenPtrs
outputs.semanticLocalTransformPtr
outputs.semanticMapPtr
outputs.semanticPrimPathPtr
outputs.semanticWorldTransformPtr
outputs.swhFrameNumber
Predefined Tokens:
tokens.InstanceMappingInfoSDhost
tokens.InstancePrimTokenSDhost
tokens.InstancePrimTokenSD
tokens.SemanticPrimTokenSDhost
tokens.SemanticPrimTokenSD
tokens.InstanceMapSDhost
tokens.InstanceMapSD
tokens.SemanticMapSDhost
tokens.SemanticMapSD
tokens.SemanticWorldTransformSDhost
tokens.SemanticWorldTransformSD
tokens.SemanticLocalTransformSDhost
tokens.SemanticLocalTransformSD
tokens.SemanticLabelTokenSDhost
tokens.SemanticLabelTokenSD
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:cudaPtr', 'bool', 0, None, 'If true, return cuda device pointer instead of host pointer', {ogn.MetadataKeys.DEFAULT: 'false'}, True, False, False, ''),
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:renderResults', 'uint64', 0, None, 'Render results pointer', {}, True, 0, False, ''),
('inputs:semanticFilerTokens', 'token[]', 0, None, 'Tokens identifying the semantic filters applied to the output semantic labels. Each token should correspond to an activated SdSemanticFilter node', {ogn.MetadataKeys.DEFAULT: '[]'}, True, [], False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:instanceMapPtr', 'uint64', 0, None, 'Array pointer of numInstances uint16_t containing the semantic index of the instance prim first semantic prim parent', {}, True, None, False, ''),
('outputs:instancePrimPathPtr', 'uint64', 0, None, 'Array pointer of numInstances uint64_t containing the prim path tokens for every instance prims', {}, True, None, False, ''),
('outputs:minInstanceIndex', 'uint', 0, None, 'Instance index of the first instance prim in the instance arrays', {}, True, None, False, ''),
('outputs:minSemanticIndex', 'uint', 0, None, 'Semantic index of the first semantic prim in the semantic arrays', {}, True, None, False, ''),
('outputs:numInstances', 'uint', 0, None, 'Number of instances prim in the instance arrays', {}, True, None, False, ''),
('outputs:numSemantics', 'uint', 0, None, 'Number of semantic prim in the semantic arrays', {}, True, None, False, ''),
('outputs:semanticLabelTokenPtrs', 'uint64[]', 0, None, 'Array containing for every input semantic filters the corresponding array pointer of numSemantics uint64_t representing the semantic label of the semantic prim', {}, True, None, False, ''),
('outputs:semanticLocalTransformPtr', 'uint64', 0, None, 'Array pointer of numSemantics 4x4 float matrices containing the transform from world to object space for every semantic prims', {}, True, None, False, ''),
('outputs:semanticMapPtr', 'uint64', 0, None, 'Array pointer of numSemantics uint16_t containing the semantic index of the semantic prim first semantic prim parent', {}, True, None, False, ''),
('outputs:semanticPrimPathPtr', 'uint64', 0, None, 'Array pointer of numSemantics uint32_t containing the prim part of the prim path tokens for every semantic prims', {}, True, None, False, ''),
('outputs:semanticWorldTransformPtr', 'uint64', 0, None, 'Array pointer of numSemantics 4x4 float matrices containing the transform from local to world space for every semantic entity', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, None, False, ''),
])
class tokens:
InstanceMappingInfoSDhost = "InstanceMappingInfoSDhost"
InstancePrimTokenSDhost = "InstancePrimTokenSDhost"
InstancePrimTokenSD = "InstancePrimTokenSD"
SemanticPrimTokenSDhost = "SemanticPrimTokenSDhost"
SemanticPrimTokenSD = "SemanticPrimTokenSD"
InstanceMapSDhost = "InstanceMapSDhost"
InstanceMapSD = "InstanceMapSD"
SemanticMapSDhost = "SemanticMapSDhost"
SemanticMapSD = "SemanticMapSD"
SemanticWorldTransformSDhost = "SemanticWorldTransformSDhost"
SemanticWorldTransformSD = "SemanticWorldTransformSD"
SemanticLocalTransformSDhost = "SemanticLocalTransformSDhost"
SemanticLocalTransformSD = "SemanticLocalTransformSD"
SemanticLabelTokenSDhost = "SemanticLabelTokenSDhost"
SemanticLabelTokenSD = "SemanticLabelTokenSD"
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"cudaPtr", "exec", "renderResults", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.cudaPtr, self._attributes.exec, self._attributes.renderResults, self._attributes.swhFrameNumber]
self._batchedReadValues = [False, None, 0, 0]
@property
def semanticFilerTokens(self):
data_view = og.AttributeValueHelper(self._attributes.semanticFilerTokens)
return data_view.get()
@semanticFilerTokens.setter
def semanticFilerTokens(self, value):
if self._setting_locked:
raise og.ReadOnlyError(self._attributes.semanticFilerTokens)
data_view = og.AttributeValueHelper(self._attributes.semanticFilerTokens)
data_view.set(value)
self.semanticFilerTokens_size = data_view.get_array_size()
@property
def cudaPtr(self):
return self._batchedReadValues[0]
@cudaPtr.setter
def cudaPtr(self, value):
self._batchedReadValues[0] = value
@property
def exec(self):
return self._batchedReadValues[1]
@exec.setter
def exec(self, value):
self._batchedReadValues[1] = value
@property
def renderResults(self):
return self._batchedReadValues[2]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[2] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[3]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "instanceMapPtr", "instancePrimPathPtr", "minInstanceIndex", "minSemanticIndex", "numInstances", "numSemantics", "semanticLocalTransformPtr", "semanticMapPtr", "semanticPrimPathPtr", "semanticWorldTransformPtr", "swhFrameNumber", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self.semanticLabelTokenPtrs_size = None
self._batchedWriteValues = { }
@property
def semanticLabelTokenPtrs(self):
data_view = og.AttributeValueHelper(self._attributes.semanticLabelTokenPtrs)
return data_view.get(reserved_element_count=self.semanticLabelTokenPtrs_size)
@semanticLabelTokenPtrs.setter
def semanticLabelTokenPtrs(self, value):
data_view = og.AttributeValueHelper(self._attributes.semanticLabelTokenPtrs)
data_view.set(value)
self.semanticLabelTokenPtrs_size = data_view.get_array_size()
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def instanceMapPtr(self):
value = self._batchedWriteValues.get(self._attributes.instanceMapPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.instanceMapPtr)
return data_view.get()
@instanceMapPtr.setter
def instanceMapPtr(self, value):
self._batchedWriteValues[self._attributes.instanceMapPtr] = value
@property
def instancePrimPathPtr(self):
value = self._batchedWriteValues.get(self._attributes.instancePrimPathPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.instancePrimPathPtr)
return data_view.get()
@instancePrimPathPtr.setter
def instancePrimPathPtr(self, value):
self._batchedWriteValues[self._attributes.instancePrimPathPtr] = value
@property
def minInstanceIndex(self):
value = self._batchedWriteValues.get(self._attributes.minInstanceIndex)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.minInstanceIndex)
return data_view.get()
@minInstanceIndex.setter
def minInstanceIndex(self, value):
self._batchedWriteValues[self._attributes.minInstanceIndex] = value
@property
def minSemanticIndex(self):
value = self._batchedWriteValues.get(self._attributes.minSemanticIndex)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.minSemanticIndex)
return data_view.get()
@minSemanticIndex.setter
def minSemanticIndex(self, value):
self._batchedWriteValues[self._attributes.minSemanticIndex] = value
@property
def numInstances(self):
value = self._batchedWriteValues.get(self._attributes.numInstances)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.numInstances)
return data_view.get()
@numInstances.setter
def numInstances(self, value):
self._batchedWriteValues[self._attributes.numInstances] = value
@property
def numSemantics(self):
value = self._batchedWriteValues.get(self._attributes.numSemantics)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.numSemantics)
return data_view.get()
@numSemantics.setter
def numSemantics(self, value):
self._batchedWriteValues[self._attributes.numSemantics] = value
@property
def semanticLocalTransformPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticLocalTransformPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticLocalTransformPtr)
return data_view.get()
@semanticLocalTransformPtr.setter
def semanticLocalTransformPtr(self, value):
self._batchedWriteValues[self._attributes.semanticLocalTransformPtr] = value
@property
def semanticMapPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticMapPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticMapPtr)
return data_view.get()
@semanticMapPtr.setter
def semanticMapPtr(self, value):
self._batchedWriteValues[self._attributes.semanticMapPtr] = value
@property
def semanticPrimPathPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticPrimPathPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticPrimPathPtr)
return data_view.get()
@semanticPrimPathPtr.setter
def semanticPrimPathPtr(self, value):
self._batchedWriteValues[self._attributes.semanticPrimPathPtr] = value
@property
def semanticWorldTransformPtr(self):
value = self._batchedWriteValues.get(self._attributes.semanticWorldTransformPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.semanticWorldTransformPtr)
return data_view.get()
@semanticWorldTransformPtr.setter
def semanticWorldTransformPtr(self, value):
self._batchedWriteValues[self._attributes.semanticWorldTransformPtr] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdInstanceMappingPtrDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdInstanceMappingPtrDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdInstanceMappingPtrDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 18,594 | Python | 47.550914 | 292 | 0.651178 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdSemanticFilterDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdSemanticFilter
Synthetic Data node to declare a semantic filter.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdSemanticFilterDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdSemanticFilter
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.hierarchicalLabels
inputs.matchingLabels
inputs.name
inputs.predicate
Outputs:
outputs.exec
outputs.name
outputs.predicate
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Dependency', {}, True, None, False, ''),
('inputs:hierarchicalLabels', 'bool', 0, None, 'If true the filter consider all labels in the semantic hierarchy above the prims', {ogn.MetadataKeys.DEFAULT: 'false'}, True, False, False, ''),
('inputs:matchingLabels', 'bool', 0, None, 'If true output only the labels matching the filter (if false keep all labels of the matching prims)', {ogn.MetadataKeys.DEFAULT: 'true'}, True, True, False, ''),
('inputs:name', 'token', 0, None, 'Filter unique identifier [if empty, use the normalized predicate as an identifier]', {ogn.MetadataKeys.DEFAULT: '""'}, True, '', False, ''),
('inputs:predicate', 'token', 0, None, 'The semantic filter specification : a disjunctive normal form of semantic type and label', {ogn.MetadataKeys.DEFAULT: '""'}, True, '', False, ''),
('outputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('outputs:name', 'token', 0, None, 'The semantic filter name identifier', {ogn.MetadataKeys.DEFAULT: '""'}, True, '', False, ''),
('outputs:predicate', 'token', 0, None, 'The semantic filter predicate in normalized form', {ogn.MetadataKeys.DEFAULT: '""'}, True, '', False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "hierarchicalLabels", "matchingLabels", "name", "predicate", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.hierarchicalLabels, self._attributes.matchingLabels, self._attributes.name, self._attributes.predicate]
self._batchedReadValues = [None, False, True, "", ""]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def hierarchicalLabels(self):
return self._batchedReadValues[1]
@hierarchicalLabels.setter
def hierarchicalLabels(self, value):
self._batchedReadValues[1] = value
@property
def matchingLabels(self):
return self._batchedReadValues[2]
@matchingLabels.setter
def matchingLabels(self, value):
self._batchedReadValues[2] = value
@property
def name(self):
return self._batchedReadValues[3]
@name.setter
def name(self, value):
self._batchedReadValues[3] = value
@property
def predicate(self):
return self._batchedReadValues[4]
@predicate.setter
def predicate(self, value):
self._batchedReadValues[4] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "name", "predicate", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def name(self):
value = self._batchedWriteValues.get(self._attributes.name)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.name)
return data_view.get()
@name.setter
def name(self, value):
self._batchedWriteValues[self._attributes.name] = value
@property
def predicate(self):
value = self._batchedWriteValues.get(self._attributes.predicate)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.predicate)
return data_view.get()
@predicate.setter
def predicate(self, value):
self._batchedWriteValues[self._attributes.predicate] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdSemanticFilterDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdSemanticFilterDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdSemanticFilterDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 9,254 | Python | 46.461538 | 213 | 0.632267 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdPostRenderVarToHostDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdPostRenderVarToHost
Expose a host renderVar from the input device renderVar.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdPostRenderVarToHostDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdPostRenderVarToHost
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.gpu
inputs.renderVar
inputs.renderVarHostSuffix
inputs.rp
Outputs:
outputs.renderVar
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:gpu', 'uint64', 0, None, 'Pointer to shared context containing gpu foundations', {}, True, 0, False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the device renderVar to expose on the host', {}, True, '', False, ''),
('inputs:renderVarHostSuffix', 'string', 0, None, 'Suffix appended to the renderVar name', {ogn.MetadataKeys.DEFAULT: '"host"'}, True, 'host', False, ''),
('inputs:rp', 'uint64', 0, None, 'Pointer to render product for this view', {}, True, 0, False, ''),
('outputs:renderVar', 'token', 0, None, 'Name of the resulting renderVar on the host', {}, True, None, False, ''),
])
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"gpu", "renderVar", "renderVarHostSuffix", "rp", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.gpu, self._attributes.renderVar, self._attributes.renderVarHostSuffix, self._attributes.rp]
self._batchedReadValues = [0, "", "host", 0]
@property
def gpu(self):
return self._batchedReadValues[0]
@gpu.setter
def gpu(self, value):
self._batchedReadValues[0] = value
@property
def renderVar(self):
return self._batchedReadValues[1]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[1] = value
@property
def renderVarHostSuffix(self):
return self._batchedReadValues[2]
@renderVarHostSuffix.setter
def renderVarHostSuffix(self, value):
self._batchedReadValues[2] = value
@property
def rp(self):
return self._batchedReadValues[3]
@rp.setter
def rp(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"renderVar", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def renderVar(self):
value = self._batchedWriteValues.get(self._attributes.renderVar)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.renderVar)
return data_view.get()
@renderVar.setter
def renderVar(self, value):
self._batchedWriteValues[self._attributes.renderVar] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdPostRenderVarToHostDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdPostRenderVarToHostDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdPostRenderVarToHostDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 7,115 | Python | 47.081081 | 162 | 0.641181 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/OgnSdRenderVarPtrDatabase.py | """Support for simplified access to data on nodes of type omni.syntheticdata.SdRenderVarPtr
Synthetic Data node exposing the raw pointer data of a rendervar.
"""
import omni.graph.core as og
import omni.graph.core._omni_graph_core as _og
import omni.graph.tools.ogn as ogn
class OgnSdRenderVarPtrDatabase(og.Database):
"""Helper class providing simplified access to data on nodes of type omni.syntheticdata.SdRenderVarPtr
Class Members:
node: Node being evaluated
Attribute Value Properties:
Inputs:
inputs.exec
inputs.renderResults
inputs.renderVar
inputs.swhFrameNumber
Outputs:
outputs.bufferSize
outputs.cudaDeviceIndex
outputs.dataPtr
outputs.exec
outputs.format
outputs.height
outputs.swhFrameNumber
outputs.width
"""
# This is an internal object that provides per-class storage of a per-node data dictionary
PER_NODE_DATA = {}
# This is an internal object that describes unchanging attributes in a generic way
# The values in this list are in no particular order, as a per-attribute tuple
# Name, Type, ExtendedTypeIndex, UiName, Description, Metadata,
# Is_Required, DefaultValue, Is_Deprecated, DeprecationMsg
# You should not need to access any of this data directly, use the defined database interfaces
INTERFACE = og.Database._get_interface([
('inputs:exec', 'execution', 0, None, 'Trigger', {}, True, None, False, ''),
('inputs:renderResults', 'uint64', 0, None, 'Render results pointer', {}, True, 0, False, ''),
('inputs:renderVar', 'token', 0, None, 'Name of the renderVar', {}, True, '', False, ''),
('inputs:swhFrameNumber', 'uint64', 0, None, 'Fabric frame number', {}, True, 0, False, ''),
('outputs:bufferSize', 'uint64', 0, None, 'Size (in bytes) of the buffer (0 if the input is a texture)', {}, True, None, False, ''),
('outputs:cudaDeviceIndex', 'int', 0, None, 'Index of the device where the data lives (-1 for host data)', {ogn.MetadataKeys.DEFAULT: '-1'}, True, -1, False, ''),
('outputs:dataPtr', 'uint64', 0, None, 'Pointer to the raw data (cuda device pointer or host pointer)', {ogn.MetadataKeys.DEFAULT: '0'}, True, 0, False, ''),
('outputs:exec', 'execution', 0, 'Received', 'Executes when the event is received', {}, True, None, False, ''),
('outputs:format', 'uint64', 0, None, 'Format', {}, True, None, False, ''),
('outputs:height', 'uint', 0, None, 'Height (0 if the input is a buffer)', {}, True, None, False, ''),
('outputs:swhFrameNumber', 'uint64', 0, None, 'Frame number', {}, True, None, False, ''),
('outputs:width', 'uint', 0, None, 'Width (0 if the input is a buffer)', {}, True, None, False, ''),
])
@classmethod
def _populate_role_data(cls):
"""Populate a role structure with the non-default roles on this node type"""
role_data = super()._populate_role_data()
role_data.inputs.exec = og.Database.ROLE_EXECUTION
role_data.outputs.exec = og.Database.ROLE_EXECUTION
return role_data
class ValuesForInputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"exec", "renderResults", "renderVar", "swhFrameNumber", "_setting_locked", "_batchedReadAttributes", "_batchedReadValues"}
"""Helper class that creates natural hierarchical access to input attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedReadAttributes = [self._attributes.exec, self._attributes.renderResults, self._attributes.renderVar, self._attributes.swhFrameNumber]
self._batchedReadValues = [None, 0, "", 0]
@property
def exec(self):
return self._batchedReadValues[0]
@exec.setter
def exec(self, value):
self._batchedReadValues[0] = value
@property
def renderResults(self):
return self._batchedReadValues[1]
@renderResults.setter
def renderResults(self, value):
self._batchedReadValues[1] = value
@property
def renderVar(self):
return self._batchedReadValues[2]
@renderVar.setter
def renderVar(self, value):
self._batchedReadValues[2] = value
@property
def swhFrameNumber(self):
return self._batchedReadValues[3]
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedReadValues[3] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _prefetch(self):
readAttributes = self._batchedReadAttributes
newValues = _og._prefetch_input_attributes_data(readAttributes)
if len(readAttributes) == len(newValues):
self._batchedReadValues = newValues
class ValuesForOutputs(og.DynamicAttributeAccess):
LOCAL_PROPERTY_NAMES = {"bufferSize", "cudaDeviceIndex", "dataPtr", "exec", "format", "height", "swhFrameNumber", "width", "_batchedWriteValues"}
"""Helper class that creates natural hierarchical access to output attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
self._batchedWriteValues = { }
@property
def bufferSize(self):
value = self._batchedWriteValues.get(self._attributes.bufferSize)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.bufferSize)
return data_view.get()
@bufferSize.setter
def bufferSize(self, value):
self._batchedWriteValues[self._attributes.bufferSize] = value
@property
def cudaDeviceIndex(self):
value = self._batchedWriteValues.get(self._attributes.cudaDeviceIndex)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.cudaDeviceIndex)
return data_view.get()
@cudaDeviceIndex.setter
def cudaDeviceIndex(self, value):
self._batchedWriteValues[self._attributes.cudaDeviceIndex] = value
@property
def dataPtr(self):
value = self._batchedWriteValues.get(self._attributes.dataPtr)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.dataPtr)
return data_view.get()
@dataPtr.setter
def dataPtr(self, value):
self._batchedWriteValues[self._attributes.dataPtr] = value
@property
def exec(self):
value = self._batchedWriteValues.get(self._attributes.exec)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.exec)
return data_view.get()
@exec.setter
def exec(self, value):
self._batchedWriteValues[self._attributes.exec] = value
@property
def format(self):
value = self._batchedWriteValues.get(self._attributes.format)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.format)
return data_view.get()
@format.setter
def format(self, value):
self._batchedWriteValues[self._attributes.format] = value
@property
def height(self):
value = self._batchedWriteValues.get(self._attributes.height)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.height)
return data_view.get()
@height.setter
def height(self, value):
self._batchedWriteValues[self._attributes.height] = value
@property
def swhFrameNumber(self):
value = self._batchedWriteValues.get(self._attributes.swhFrameNumber)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.swhFrameNumber)
return data_view.get()
@swhFrameNumber.setter
def swhFrameNumber(self, value):
self._batchedWriteValues[self._attributes.swhFrameNumber] = value
@property
def width(self):
value = self._batchedWriteValues.get(self._attributes.width)
if value:
return value
else:
data_view = og.AttributeValueHelper(self._attributes.width)
return data_view.get()
@width.setter
def width(self, value):
self._batchedWriteValues[self._attributes.width] = value
def __getattr__(self, item: str):
if item in self.LOCAL_PROPERTY_NAMES:
return object.__getattribute__(self, item)
else:
return super().__getattr__(item)
def __setattr__(self, item: str, new_value):
if item in self.LOCAL_PROPERTY_NAMES:
object.__setattr__(self, item, new_value)
else:
super().__setattr__(item, new_value)
def _commit(self):
_og._commit_output_attributes_data(self._batchedWriteValues)
self._batchedWriteValues = { }
class ValuesForState(og.DynamicAttributeAccess):
"""Helper class that creates natural hierarchical access to state attributes"""
def __init__(self, node: og.Node, attributes, dynamic_attributes: og.DynamicAttributeInterface):
"""Initialize simplified access for the attribute data"""
context = node.get_graph().get_default_graph_context()
super().__init__(context, node, attributes, dynamic_attributes)
def __init__(self, node):
super().__init__(node)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_INPUT)
self.inputs = OgnSdRenderVarPtrDatabase.ValuesForInputs(node, self.attributes.inputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_OUTPUT)
self.outputs = OgnSdRenderVarPtrDatabase.ValuesForOutputs(node, self.attributes.outputs, dynamic_attributes)
dynamic_attributes = self.dynamic_attribute_data(node, og.AttributePortType.ATTRIBUTE_PORT_TYPE_STATE)
self.state = OgnSdRenderVarPtrDatabase.ValuesForState(node, self.attributes.state, dynamic_attributes)
| 11,600 | Python | 43.619231 | 170 | 0.613362 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/python/nodes/OgnSdTestPrintRawArray.py | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import omni.graph.core as og
import numpy as np
import random
class OgnSdTestPrintRawArray:
@staticmethod
def compute(db) -> bool:
if db.state.initialSWHFrameNumber < 0:
db.state.initialSWHFrameNumber = db.inputs.swhFrameNumber
frameNumber = db.inputs.swhFrameNumber - db.state.initialSWHFrameNumber
rd_seed = db.inputs.randomSeed + ((frameNumber * 17) % 491)
random.seed(rd_seed)
db.outputs.swhFrameNumber = db.inputs.swhFrameNumber
db.outputs.exec = og.ExecutionAttributeState.ENABLED
elemenType = np.uint8
if db.inputs.elementType == db.tokens.uint16:
elemenType = np.uint16
elif db.inputs.elementType == db.tokens.int16:
elemenType = np.int16
elif db.inputs.elementType == db.tokens.uint32:
elemenType = np.uint32
elif db.inputs.elementType == db.tokens.int32:
elemenType = np.int32
elif db.inputs.elementType == db.tokens.float32:
elemenType = np.float32
elif db.inputs.elementType == db.tokens.token:
elemenType = np.uint64
elementCount = db.inputs.elementCount
data = db.inputs.data
data = data.view(elemenType)
if db.inputs.mode == db.tokens.printFormatted:
is2DArray = db.inputs.bufferSize == 0
if not is2DArray:
data = data.reshape(data.shape[0] // elementCount, elementCount) if elementCount > 1 else data
else:
data = (
data.reshape(db.inputs.height, db.inputs.width, elementCount)
if elementCount > 1
else data.reshape(db.inputs.height, db.inputs.width)
)
print("OgnSdPrintRawArray : ", db.inputs.swhFrameNumber)
print(data)
elif (frameNumber in db.inputs.referenceSWHFrameNumbers) and (data.shape[0]>=db.inputs.referenceNumUniqueRandomValues):
if (db.inputs.mode == db.tokens.printReferences):
ref_values = data.astype(np.float32)
random.shuffle(ref_values)
ref_values = ref_values[:db.inputs.referenceNumUniqueRandomValues]
print(ref_values)
else:
ref_values = data.astype(np.float32)
random.shuffle(ref_values)
ref_values = ref_values[:db.inputs.referenceNumUniqueRandomValues]
frame_offset = np.where(db.inputs.referenceSWHFrameNumbers == frameNumber)[0][0]
reference_offset = frame_offset * db.inputs.referenceNumUniqueRandomValues
err = np.square(ref_values - db.inputs.referenceValues[reference_offset:reference_offset+db.inputs.referenceNumUniqueRandomValues]).max()
if err >= db.inputs.referenceTolerance:
print(f"OgnSdTestPrintRawArray [Error]")
return True
| 3,401 | Python | 41.524999 | 153 | 0.633931 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/python/nodes/OgnSdTestStageManipulationScenarii.py | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
import omni.usd
import omni.graph.core as og
from pxr import Gf, Semantics, UsdGeom
import numpy as np
class OgnSdTestStageManipulationScenarii:
_prim_names = ["Sphere", "Capsule", "Plane", "Torus", "Cube", "Cone"]
_sem_types = ["type", "class", "genre"]
_sem_labels = ["sphere", "capsule", "plane", "torus", "cube", "ball", "cone"]
@staticmethod
def add_semantics(prim, semantic_label, semantic_type="class"):
sem = Semantics.SemanticsAPI.Apply(prim, "Semantics")
sem.CreateSemanticTypeAttr()
sem.CreateSemanticDataAttr()
sem.GetSemanticTypeAttr().Set(semantic_type)
sem.GetSemanticDataAttr().Set(semantic_label)
@staticmethod
def get_random_transform(rng):
tf = np.eye(4)
tf[:3, :3] = Gf.Matrix3d(Gf.Rotation(rng.rand(3).tolist(), rng.rand(3).tolist()))
tf[3, :3] = rng.rand(3).tolist()
return Gf.Matrix4d(tf)
@staticmethod
def compute(db) -> bool:
usd_context = omni.usd.get_context()
stage = usd_context.get_stage()
if not stage:
return False
rng = np.random.default_rng(db.inputs.randomSeed + ((db.state.frameNumber * 23) % 1579))
world_prim = stage.GetPrimAtPath(db.inputs.worldPrimPath)
if not world_prim:
world_prim = stage.DefinePrim(db.inputs.worldPrimPath)
if world_prim:
world_xform_prim = UsdGeom.Xformable(world_prim) if world_prim else None
if world_xform_prim:
world_xform_prim.AddTransformOp().Set(OgnSdTestStageManipulationScenarii.get_random_transform(rng))
if not world_prim:
return False
db.state.frameNumber += 1
num_manipulations = rng.randint(0, 3)
for manip_index in range(num_manipulations):
prims = world_prim.GetChildren()
prims.append(world_prim)
prim = rng.choice(prims)
if not prim :
continue
manipulation = rng.randint(0, 38)
if (manipulation < 11):
"""create a new children prim"""
prim_name = rng.choice(OgnSdTestStageManipulationScenarii._prim_names)
prim_path = prim.GetPath().pathString + "/" + prim_name + "_" + str(db.state.frameNumber) + "_" + str(manip_index)
new_prim = stage.DefinePrim(prim_path, prim_name)
new_prim_color_attr = new_prim.GetAttribute("primvars:displayColor") if new_prim else None
if new_prim_color_attr:
new_prim_color_attr.Set([rng.rand(3).tolist()])
xform_prim = UsdGeom.Xformable(new_prim) if new_prim else None
if xform_prim:
xform_prim.AddScaleOp().Set((175.0*rng.random(), 175.0*rng.random(), 175.0*rng.random()))
xform_prim.AddTransformOp().Set(OgnSdTestStageManipulationScenarii.get_random_transform(rng))
elif (manipulation >= 11) and (manipulation <12):
"""remove the prim"""
stage.RemovePrim(prim.GetPath())
elif (manipulation >=12) and (manipulation <23):
"""move the prim"""
xform_prim = UsdGeom.Xformable(prim)
if xform_prim:
xform_prim.ClearXformOpOrder()
xform_prim.AddTransformOp().Set(OgnSdTestStageManipulationScenarii.get_random_transform(rng))
elif (manipulation >=23) and (manipulation < 31):
"""add semantic to the prim"""
OgnSdTestStageManipulationScenarii.add_semantics(prim, rng.choice(OgnSdTestStageManipulationScenarii._sem_labels), rng.choice(OgnSdTestStageManipulationScenarii._sem_types))
elif (manipulation >=31) and (manipulation < 39):
"""change color of the prim"""
prim_color_attr = prim.GetAttribute("primvars:displayColor")
if prim_color_attr:
prim_color_attr.Set([rng.rand(3).tolist()])
return True
| 4,542 | Python | 42.266666 | 189 | 0.606781 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdRenderProductCamera.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdRenderProductCameraDatabase import OgnSdRenderProductCameraDatabase
test_file_name = "OgnSdRenderProductCameraTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdRenderProductCamera")
database = OgnSdRenderProductCameraDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 2)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductPath"))
attribute = test_node.get_attribute("inputs:renderProductPath")
db_value = database.inputs.renderProductPath
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderResults"))
attribute = test_node.get_attribute("inputs:renderResults")
db_value = database.inputs.renderResults
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:cameraApertureOffset"))
attribute = test_node.get_attribute("outputs:cameraApertureOffset")
db_value = database.outputs.cameraApertureOffset
self.assertTrue(test_node.get_attribute_exists("outputs:cameraApertureSize"))
attribute = test_node.get_attribute("outputs:cameraApertureSize")
db_value = database.outputs.cameraApertureSize
self.assertTrue(test_node.get_attribute_exists("outputs:cameraFStop"))
attribute = test_node.get_attribute("outputs:cameraFStop")
db_value = database.outputs.cameraFStop
self.assertTrue(test_node.get_attribute_exists("outputs:cameraFisheyeParams"))
attribute = test_node.get_attribute("outputs:cameraFisheyeParams")
db_value = database.outputs.cameraFisheyeParams
self.assertTrue(test_node.get_attribute_exists("outputs:cameraFocalLength"))
attribute = test_node.get_attribute("outputs:cameraFocalLength")
db_value = database.outputs.cameraFocalLength
self.assertTrue(test_node.get_attribute_exists("outputs:cameraFocusDistance"))
attribute = test_node.get_attribute("outputs:cameraFocusDistance")
db_value = database.outputs.cameraFocusDistance
self.assertTrue(test_node.get_attribute_exists("outputs:cameraModel"))
attribute = test_node.get_attribute("outputs:cameraModel")
db_value = database.outputs.cameraModel
self.assertTrue(test_node.get_attribute_exists("outputs:cameraNearFar"))
attribute = test_node.get_attribute("outputs:cameraNearFar")
db_value = database.outputs.cameraNearFar
self.assertTrue(test_node.get_attribute_exists("outputs:cameraProjection"))
attribute = test_node.get_attribute("outputs:cameraProjection")
db_value = database.outputs.cameraProjection
self.assertTrue(test_node.get_attribute_exists("outputs:cameraViewTransform"))
attribute = test_node.get_attribute("outputs:cameraViewTransform")
db_value = database.outputs.cameraViewTransform
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:metersPerSceneUnit"))
attribute = test_node.get_attribute("outputs:metersPerSceneUnit")
db_value = database.outputs.metersPerSceneUnit
self.assertTrue(test_node.get_attribute_exists("outputs:renderProductResolution"))
attribute = test_node.get_attribute("outputs:renderProductResolution")
db_value = database.outputs.renderProductResolution
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
| 5,723 | Python | 50.567567 | 108 | 0.710292 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostRenderVarTextureToBuffer.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostRenderVarTextureToBufferDatabase import OgnSdPostRenderVarTextureToBufferDatabase
test_file_name = "OgnSdPostRenderVarTextureToBufferTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostRenderVarTextureToBuffer")
database = OgnSdPostRenderVarTextureToBufferDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVar"))
attribute = test_node.get_attribute("inputs:renderVar")
db_value = database.inputs.renderVar
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVarBufferSuffix"))
attribute = test_node.get_attribute("inputs:renderVarBufferSuffix")
db_value = database.inputs.renderVarBufferSuffix
expected_value = "buffer"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:renderVar"))
attribute = test_node.get_attribute("outputs:renderVar")
db_value = database.outputs.renderVar
| 3,241 | Python | 50.460317 | 126 | 0.691762 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostSemantic3dBoundingBoxCameraProjection.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase import OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase
test_file_name = "OgnSdPostSemantic3dBoundingBoxCameraProjectionTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostSemantic3dBoundingBoxCameraProjection")
database = OgnSdPostSemantic3dBoundingBoxCameraProjectionDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:cameraFisheyeParams"))
attribute = test_node.get_attribute("inputs:cameraFisheyeParams")
db_value = database.inputs.cameraFisheyeParams
expected_value = []
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:cameraModel"))
attribute = test_node.get_attribute("inputs:cameraModel")
db_value = database.inputs.cameraModel
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:cameraNearFar"))
attribute = test_node.get_attribute("inputs:cameraNearFar")
db_value = database.inputs.cameraNearFar
expected_value = [0.0, 0.0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMappingInfoSDPtr"))
attribute = test_node.get_attribute("inputs:instanceMappingInfoSDPtr")
db_value = database.inputs.instanceMappingInfoSDPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:metersPerSceneUnit"))
attribute = test_node.get_attribute("inputs:metersPerSceneUnit")
db_value = database.inputs.metersPerSceneUnit
expected_value = 0.01
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductResolution"))
attribute = test_node.get_attribute("inputs:renderProductResolution")
db_value = database.inputs.renderProductResolution
expected_value = [0, 0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBoxExtentCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBoxExtentCudaPtr")
db_value = database.inputs.sdSemBBoxExtentCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBoxInfosCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBoxInfosCudaPtr")
db_value = database.inputs.sdSemBBoxInfosCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticWorldTransformSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticWorldTransformSDCudaPtr")
db_value = database.inputs.semanticWorldTransformSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:viewportNearFar"))
attribute = test_node.get_attribute("inputs:viewportNearFar")
db_value = database.inputs.viewportNearFar
expected_value = [1.0, 10000000.0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:viewportResolution"))
attribute = test_node.get_attribute("inputs:viewportResolution")
db_value = database.inputs.viewportResolution
expected_value = [65536, 65536]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:sdSemBBox3dCamCornersCudaPtr"))
attribute = test_node.get_attribute("outputs:sdSemBBox3dCamCornersCudaPtr")
db_value = database.outputs.sdSemBBox3dCamCornersCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:sdSemBBox3dCamExtentCudaPtr"))
attribute = test_node.get_attribute("outputs:sdSemBBox3dCamExtentCudaPtr")
db_value = database.outputs.sdSemBBox3dCamExtentCudaPtr
| 8,226 | Python | 54.965986 | 152 | 0.705568 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdSimRenderProductCamera.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdSimRenderProductCameraDatabase import OgnSdSimRenderProductCameraDatabase
test_file_name = "OgnSdSimRenderProductCameraTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdSimRenderProductCamera")
database = OgnSdSimRenderProductCameraDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductPath"))
attribute = test_node.get_attribute("inputs:renderProductPath")
db_value = database.inputs.renderProductPath
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
| 1,908 | Python | 47.948717 | 114 | 0.692872 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdOnNewFrame.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdOnNewFrameDatabase import OgnSdOnNewFrameDatabase
test_file_name = "OgnSdOnNewFrameTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdOnNewFrame")
database = OgnSdOnNewFrameDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("outputs:cudaStream"))
attribute = test_node.get_attribute("outputs:cudaStream")
db_value = database.outputs.cudaStream
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:renderProductDataPtrs"))
attribute = test_node.get_attribute("outputs:renderProductDataPtrs")
db_value = database.outputs.renderProductDataPtrs
self.assertTrue(test_node.get_attribute_exists("outputs:renderProductPaths"))
attribute = test_node.get_attribute("outputs:renderProductPaths")
db_value = database.outputs.renderProductPaths
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
| 2,224 | Python | 46.340425 | 93 | 0.696493 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostInstanceMapping.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostInstanceMappingDatabase import OgnSdPostInstanceMappingDatabase
test_file_name = "OgnSdPostInstanceMappingTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostInstanceMapping")
database = OgnSdPostInstanceMappingDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 2)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticFilterName"))
attribute = test_node.get_attribute("inputs:semanticFilterName")
db_value = database.inputs.semanticFilterName
expected_value = "default"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:instanceMapSDCudaPtr"))
attribute = test_node.get_attribute("outputs:instanceMapSDCudaPtr")
db_value = database.outputs.instanceMapSDCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:instanceMappingInfoSDPtr"))
attribute = test_node.get_attribute("outputs:instanceMappingInfoSDPtr")
db_value = database.outputs.instanceMappingInfoSDPtr
self.assertTrue(test_node.get_attribute_exists("outputs:instancePrimTokenSDCudaPtr"))
attribute = test_node.get_attribute("outputs:instancePrimTokenSDCudaPtr")
db_value = database.outputs.instancePrimTokenSDCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticLabelTokenSDCudaPtr"))
attribute = test_node.get_attribute("outputs:semanticLabelTokenSDCudaPtr")
db_value = database.outputs.semanticLabelTokenSDCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticLocalTransformSDCudaPtr"))
attribute = test_node.get_attribute("outputs:semanticLocalTransformSDCudaPtr")
db_value = database.outputs.semanticLocalTransformSDCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticMapSDCudaPtr"))
attribute = test_node.get_attribute("outputs:semanticMapSDCudaPtr")
db_value = database.outputs.semanticMapSDCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticPrimTokenSDCudaPtr"))
attribute = test_node.get_attribute("outputs:semanticPrimTokenSDCudaPtr")
db_value = database.outputs.semanticPrimTokenSDCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticWorldTransformSDCudaPtr"))
attribute = test_node.get_attribute("outputs:semanticWorldTransformSDCudaPtr")
db_value = database.outputs.semanticWorldTransformSDCudaPtr
| 5,269 | Python | 52.232323 | 108 | 0.713418 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdSimInstanceMapping.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdSimInstanceMappingDatabase import OgnSdSimInstanceMappingDatabase
test_file_name = "OgnSdSimInstanceMappingTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdSimInstanceMapping")
database = OgnSdSimInstanceMappingDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:needTransform"))
attribute = test_node.get_attribute("inputs:needTransform")
db_value = database.inputs.needTransform
expected_value = True
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticFilterPredicate"))
attribute = test_node.get_attribute("inputs:semanticFilterPredicate")
db_value = database.inputs.semanticFilterPredicate
expected_value = "*:*"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:semanticFilterPredicate"))
attribute = test_node.get_attribute("outputs:semanticFilterPredicate")
db_value = database.outputs.semanticFilterPredicate
| 2,591 | Python | 49.823528 | 106 | 0.6978 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdNoOp.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdNoOpDatabase import OgnSdNoOpDatabase
test_file_name = "OgnSdNoOpTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdNoOp")
database = OgnSdNoOpDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
| 1,528 | Python | 42.685713 | 92 | 0.670157 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdInstanceMapping.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdInstanceMappingDatabase import OgnSdInstanceMappingDatabase
test_file_name = "OgnSdInstanceMappingTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdInstanceMapping")
database = OgnSdInstanceMappingDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:lazy"))
attribute = test_node.get_attribute("inputs:lazy")
db_value = database.inputs.lazy
expected_value = True
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderResults"))
attribute = test_node.get_attribute("inputs:renderResults")
db_value = database.inputs.renderResults
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMInstanceSemanticMap"))
attribute = test_node.get_attribute("outputs:sdIMInstanceSemanticMap")
db_value = database.outputs.sdIMInstanceSemanticMap
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMInstanceTokens"))
attribute = test_node.get_attribute("outputs:sdIMInstanceTokens")
db_value = database.outputs.sdIMInstanceTokens
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMMaxSemanticHierarchyDepth"))
attribute = test_node.get_attribute("outputs:sdIMMaxSemanticHierarchyDepth")
db_value = database.outputs.sdIMMaxSemanticHierarchyDepth
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMMinInstanceIndex"))
attribute = test_node.get_attribute("outputs:sdIMMinInstanceIndex")
db_value = database.outputs.sdIMMinInstanceIndex
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMMinSemanticIndex"))
attribute = test_node.get_attribute("outputs:sdIMMinSemanticIndex")
db_value = database.outputs.sdIMMinSemanticIndex
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMNumInstances"))
attribute = test_node.get_attribute("outputs:sdIMNumInstances")
db_value = database.outputs.sdIMNumInstances
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMNumSemanticTokens"))
attribute = test_node.get_attribute("outputs:sdIMNumSemanticTokens")
db_value = database.outputs.sdIMNumSemanticTokens
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMNumSemantics"))
attribute = test_node.get_attribute("outputs:sdIMNumSemantics")
db_value = database.outputs.sdIMNumSemantics
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMSemanticLocalTransform"))
attribute = test_node.get_attribute("outputs:sdIMSemanticLocalTransform")
db_value = database.outputs.sdIMSemanticLocalTransform
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMSemanticTokenMap"))
attribute = test_node.get_attribute("outputs:sdIMSemanticTokenMap")
db_value = database.outputs.sdIMSemanticTokenMap
self.assertTrue(test_node.get_attribute_exists("outputs:sdIMSemanticWorldTransform"))
attribute = test_node.get_attribute("outputs:sdIMSemanticWorldTransform")
db_value = database.outputs.sdIMSemanticWorldTransform
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
| 5,597 | Python | 51.317757 | 100 | 0.714311 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdUpdateSwhFrameNumber.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdUpdateSwhFrameNumberDatabase import OgnSdUpdateSwhFrameNumberDatabase
test_file_name = "OgnSdUpdateSwhFrameNumberTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdUpdateSwFrameNumber")
database = OgnSdUpdateSwhFrameNumberDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
| 1,640 | Python | 45.885713 | 110 | 0.692683 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/__init__.py | """====== GENERATED BY omni.graph.tools - DO NOT EDIT ======"""
import omni.graph.tools as ogt
ogt.import_tests_in_directory(__file__, __name__)
| 145 | Python | 35.499991 | 63 | 0.634483 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostCompRenderVarTextures.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostCompRenderVarTexturesDatabase import OgnSdPostCompRenderVarTexturesDatabase
test_file_name = "OgnSdPostCompRenderVarTexturesTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostCompRenderVarTextures")
database = OgnSdPostCompRenderVarTexturesDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:cudaPtr"))
attribute = test_node.get_attribute("inputs:cudaPtr")
db_value = database.inputs.cudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:format"))
attribute = test_node.get_attribute("inputs:format")
db_value = database.inputs.format
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:height"))
attribute = test_node.get_attribute("inputs:height")
db_value = database.inputs.height
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:mode"))
attribute = test_node.get_attribute("inputs:mode")
db_value = database.inputs.mode
expected_value = "line"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:parameters"))
attribute = test_node.get_attribute("inputs:parameters")
db_value = database.inputs.parameters
expected_value = [0, 0, 0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVar"))
attribute = test_node.get_attribute("inputs:renderVar")
db_value = database.inputs.renderVar
expected_value = "LdrColor"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:width"))
attribute = test_node.get_attribute("inputs:width")
db_value = database.inputs.width
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
| 5,147 | Python | 50.999999 | 120 | 0.682728 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdRenderVarDisplayTexture.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdRenderVarDisplayTextureDatabase import OgnSdRenderVarDisplayTextureDatabase
test_file_name = "OgnSdRenderVarDisplayTextureTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdRenderVarDisplayTexture")
database = OgnSdRenderVarDisplayTextureDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:renderResults"))
attribute = test_node.get_attribute("inputs:renderResults")
db_value = database.inputs.renderResults
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVarDisplay"))
attribute = test_node.get_attribute("inputs:renderVarDisplay")
db_value = database.inputs.renderVarDisplay
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:cudaPtr"))
attribute = test_node.get_attribute("outputs:cudaPtr")
db_value = database.outputs.cudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:format"))
attribute = test_node.get_attribute("outputs:format")
db_value = database.outputs.format
self.assertTrue(test_node.get_attribute_exists("outputs:handlePtr"))
attribute = test_node.get_attribute("outputs:handlePtr")
db_value = database.outputs.handlePtr
self.assertTrue(test_node.get_attribute_exists("outputs:height"))
attribute = test_node.get_attribute("outputs:height")
db_value = database.outputs.height
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
self.assertTrue(test_node.get_attribute_exists("outputs:width"))
attribute = test_node.get_attribute("outputs:width")
db_value = database.outputs.width
| 4,093 | Python | 48.325301 | 116 | 0.692402 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdTestInstanceMapping.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdTestInstanceMappingDatabase import OgnSdTestInstanceMappingDatabase
test_file_name = "OgnSdTestInstanceMappingTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdTestInstanceMapping")
database = OgnSdTestInstanceMappingDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMapPtr"))
attribute = test_node.get_attribute("inputs:instanceMapPtr")
db_value = database.inputs.instanceMapPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instancePrimPathPtr"))
attribute = test_node.get_attribute("inputs:instancePrimPathPtr")
db_value = database.inputs.instancePrimPathPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:minInstanceIndex"))
attribute = test_node.get_attribute("inputs:minInstanceIndex")
db_value = database.inputs.minInstanceIndex
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:minSemanticIndex"))
attribute = test_node.get_attribute("inputs:minSemanticIndex")
db_value = database.inputs.minSemanticIndex
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:numInstances"))
attribute = test_node.get_attribute("inputs:numInstances")
db_value = database.inputs.numInstances
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:numSemantics"))
attribute = test_node.get_attribute("inputs:numSemantics")
db_value = database.inputs.numSemantics
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticLabelTokenPtrs"))
attribute = test_node.get_attribute("inputs:semanticLabelTokenPtrs")
db_value = database.inputs.semanticLabelTokenPtrs
expected_value = []
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticLocalTransformPtr"))
attribute = test_node.get_attribute("inputs:semanticLocalTransformPtr")
db_value = database.inputs.semanticLocalTransformPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticMapPtr"))
attribute = test_node.get_attribute("inputs:semanticMapPtr")
db_value = database.inputs.semanticMapPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticPrimPathPtr"))
attribute = test_node.get_attribute("inputs:semanticPrimPathPtr")
db_value = database.inputs.semanticPrimPathPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticWorldTransformPtr"))
attribute = test_node.get_attribute("inputs:semanticWorldTransformPtr")
db_value = database.inputs.semanticWorldTransformPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:stage"))
attribute = test_node.get_attribute("inputs:stage")
db_value = database.inputs.stage
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:testCaseIndex"))
attribute = test_node.get_attribute("inputs:testCaseIndex")
db_value = database.inputs.testCaseIndex
expected_value = -1
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:semanticFilterPredicate"))
attribute = test_node.get_attribute("outputs:semanticFilterPredicate")
db_value = database.outputs.semanticFilterPredicate
self.assertTrue(test_node.get_attribute_exists("outputs:success"))
attribute = test_node.get_attribute("outputs:success")
db_value = database.outputs.success
| 8,424 | Python | 53.354838 | 108 | 0.698362 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostSemantic3dBoundingBoxFilter.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostSemantic3dBoundingBoxFilterDatabase import OgnSdPostSemantic3dBoundingBoxFilterDatabase
test_file_name = "OgnSdPostSemantic3dBoundingBoxFilterTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostSemantic3dBoundingBoxFilter")
database = OgnSdPostSemantic3dBoundingBoxFilterDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMappingInfoSDPtr"))
attribute = test_node.get_attribute("inputs:instanceMappingInfoSDPtr")
db_value = database.inputs.instanceMappingInfoSDPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:metersPerSceneUnit"))
attribute = test_node.get_attribute("inputs:metersPerSceneUnit")
db_value = database.inputs.metersPerSceneUnit
expected_value = 0.01
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBox3dCamCornersCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBox3dCamCornersCudaPtr")
db_value = database.inputs.sdSemBBox3dCamCornersCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBoxInfosCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBoxInfosCudaPtr")
db_value = database.inputs.sdSemBBoxInfosCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:viewportNearFar"))
attribute = test_node.get_attribute("inputs:viewportNearFar")
db_value = database.inputs.viewportNearFar
expected_value = [0.0, -1.0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:sdSemBBoxInfosCudaPtr"))
attribute = test_node.get_attribute("outputs:sdSemBBoxInfosCudaPtr")
db_value = database.outputs.sdSemBBoxInfosCudaPtr
| 5,097 | Python | 52.663157 | 132 | 0.700216 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdInstanceMappingPtr.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdInstanceMappingPtrDatabase import OgnSdInstanceMappingPtrDatabase
test_file_name = "OgnSdInstanceMappingPtrTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdInstanceMappingPtr")
database = OgnSdInstanceMappingPtrDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:cudaPtr"))
attribute = test_node.get_attribute("inputs:cudaPtr")
db_value = database.inputs.cudaPtr
expected_value = False
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:renderResults"))
attribute = test_node.get_attribute("inputs:renderResults")
db_value = database.inputs.renderResults
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticFilerTokens"))
attribute = test_node.get_attribute("inputs:semanticFilerTokens")
db_value = database.inputs.semanticFilerTokens
expected_value = []
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:instanceMapPtr"))
attribute = test_node.get_attribute("outputs:instanceMapPtr")
db_value = database.outputs.instanceMapPtr
self.assertTrue(test_node.get_attribute_exists("outputs:instancePrimPathPtr"))
attribute = test_node.get_attribute("outputs:instancePrimPathPtr")
db_value = database.outputs.instancePrimPathPtr
self.assertTrue(test_node.get_attribute_exists("outputs:minInstanceIndex"))
attribute = test_node.get_attribute("outputs:minInstanceIndex")
db_value = database.outputs.minInstanceIndex
self.assertTrue(test_node.get_attribute_exists("outputs:minSemanticIndex"))
attribute = test_node.get_attribute("outputs:minSemanticIndex")
db_value = database.outputs.minSemanticIndex
self.assertTrue(test_node.get_attribute_exists("outputs:numInstances"))
attribute = test_node.get_attribute("outputs:numInstances")
db_value = database.outputs.numInstances
self.assertTrue(test_node.get_attribute_exists("outputs:numSemantics"))
attribute = test_node.get_attribute("outputs:numSemantics")
db_value = database.outputs.numSemantics
self.assertTrue(test_node.get_attribute_exists("outputs:semanticLabelTokenPtrs"))
attribute = test_node.get_attribute("outputs:semanticLabelTokenPtrs")
db_value = database.outputs.semanticLabelTokenPtrs
self.assertTrue(test_node.get_attribute_exists("outputs:semanticLocalTransformPtr"))
attribute = test_node.get_attribute("outputs:semanticLocalTransformPtr")
db_value = database.outputs.semanticLocalTransformPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticMapPtr"))
attribute = test_node.get_attribute("outputs:semanticMapPtr")
db_value = database.outputs.semanticMapPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticPrimPathPtr"))
attribute = test_node.get_attribute("outputs:semanticPrimPathPtr")
db_value = database.outputs.semanticPrimPathPtr
self.assertTrue(test_node.get_attribute_exists("outputs:semanticWorldTransformPtr"))
attribute = test_node.get_attribute("outputs:semanticWorldTransformPtr")
db_value = database.outputs.semanticWorldTransformPtr
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
| 5,966 | Python | 50.886956 | 106 | 0.708683 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdSemanticFilter.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdSemanticFilterDatabase import OgnSdSemanticFilterDatabase
test_file_name = "OgnSdSemanticFilterTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdSemanticFilter")
database = OgnSdSemanticFilterDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:hierarchicalLabels"))
attribute = test_node.get_attribute("inputs:hierarchicalLabels")
db_value = database.inputs.hierarchicalLabels
expected_value = False
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:matchingLabels"))
attribute = test_node.get_attribute("inputs:matchingLabels")
db_value = database.inputs.matchingLabels
expected_value = True
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:name"))
attribute = test_node.get_attribute("inputs:name")
db_value = database.inputs.name
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:predicate"))
attribute = test_node.get_attribute("inputs:predicate")
db_value = database.inputs.predicate
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:name"))
attribute = test_node.get_attribute("outputs:name")
db_value = database.outputs.name
self.assertTrue(test_node.get_attribute_exists("outputs:predicate"))
attribute = test_node.get_attribute("outputs:predicate")
db_value = database.outputs.predicate
| 3,721 | Python | 48.626666 | 98 | 0.685568 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostRenderVarDisplayTexture.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostRenderVarDisplayTextureDatabase import OgnSdPostRenderVarDisplayTextureDatabase
test_file_name = "OgnSdPostRenderVarDisplayTextureTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostRenderVarDisplayTexture")
database = OgnSdPostRenderVarDisplayTextureDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:cameraFisheyeParams"))
attribute = test_node.get_attribute("inputs:cameraFisheyeParams")
db_value = database.inputs.cameraFisheyeParams
expected_value = []
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:cameraModel"))
attribute = test_node.get_attribute("inputs:cameraModel")
db_value = database.inputs.cameraModel
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:cameraNearFar"))
attribute = test_node.get_attribute("inputs:cameraNearFar")
db_value = database.inputs.cameraNearFar
expected_value = [0.0, 0.0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMapSDCudaPtr"))
attribute = test_node.get_attribute("inputs:instanceMapSDCudaPtr")
db_value = database.inputs.instanceMapSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMappingInfoSDPtr"))
attribute = test_node.get_attribute("inputs:instanceMappingInfoSDPtr")
db_value = database.inputs.instanceMappingInfoSDPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:metersPerSceneUnit"))
attribute = test_node.get_attribute("inputs:metersPerSceneUnit")
db_value = database.inputs.metersPerSceneUnit
expected_value = 0.0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:mode"))
attribute = test_node.get_attribute("inputs:mode")
db_value = database.inputs.mode
expected_value = "autoMode"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:parameters"))
attribute = test_node.get_attribute("inputs:parameters")
db_value = database.inputs.parameters
expected_value = [0.0, 5.0, 0.33, 0.27]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVar"))
attribute = test_node.get_attribute("inputs:renderVar")
db_value = database.inputs.renderVar
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVarDisplay"))
attribute = test_node.get_attribute("inputs:renderVarDisplay")
db_value = database.inputs.renderVarDisplay
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdDisplayHeight"))
attribute = test_node.get_attribute("inputs:sdDisplayHeight")
db_value = database.inputs.sdDisplayHeight
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdDisplayWidth"))
attribute = test_node.get_attribute("inputs:sdDisplayWidth")
db_value = database.inputs.sdDisplayWidth
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBox3dCamCornersCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBox3dCamCornersCudaPtr")
db_value = database.inputs.sdSemBBox3dCamCornersCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBox3dCamExtentCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBox3dCamExtentCudaPtr")
db_value = database.inputs.sdSemBBox3dCamExtentCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBoxExtentCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBoxExtentCudaPtr")
db_value = database.inputs.sdSemBBoxExtentCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:sdSemBBoxInfosCudaPtr"))
attribute = test_node.get_attribute("inputs:sdSemBBoxInfosCudaPtr")
db_value = database.inputs.sdSemBBoxInfosCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticLabelTokenSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticLabelTokenSDCudaPtr")
db_value = database.inputs.semanticLabelTokenSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticMapSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticMapSDCudaPtr")
db_value = database.inputs.semanticMapSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticPrimTokenSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticPrimTokenSDCudaPtr")
db_value = database.inputs.semanticPrimTokenSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticWorldTransformSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticWorldTransformSDCudaPtr")
db_value = database.inputs.semanticWorldTransformSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:cudaPtr"))
attribute = test_node.get_attribute("outputs:cudaPtr")
db_value = database.outputs.cudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:format"))
attribute = test_node.get_attribute("outputs:format")
db_value = database.outputs.format
self.assertTrue(test_node.get_attribute_exists("outputs:height"))
attribute = test_node.get_attribute("outputs:height")
db_value = database.outputs.height
self.assertTrue(test_node.get_attribute_exists("outputs:renderVarDisplay"))
attribute = test_node.get_attribute("outputs:renderVarDisplay")
db_value = database.outputs.renderVarDisplay
self.assertTrue(test_node.get_attribute_exists("outputs:width"))
attribute = test_node.get_attribute("outputs:width")
db_value = database.outputs.width
| 13,206 | Python | 54.259414 | 124 | 0.699606 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostRenderVarToHost.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostRenderVarToHostDatabase import OgnSdPostRenderVarToHostDatabase
test_file_name = "OgnSdPostRenderVarToHostTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostRenderVarToHost")
database = OgnSdPostRenderVarToHostDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVar"))
attribute = test_node.get_attribute("inputs:renderVar")
db_value = database.inputs.renderVar
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVarHostSuffix"))
attribute = test_node.get_attribute("inputs:renderVarHostSuffix")
db_value = database.inputs.renderVarHostSuffix
expected_value = "host"
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:renderVar"))
attribute = test_node.get_attribute("outputs:renderVar")
db_value = database.outputs.renderVar
| 3,188 | Python | 49.619047 | 108 | 0.686637 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdOnNewRenderProductFrame.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdOnNewRenderProductFrameDatabase import OgnSdOnNewRenderProductFrameDatabase
test_file_name = "OgnSdOnNewRenderProductFrameTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdOnNewRenderProductFrame")
database = OgnSdOnNewRenderProductFrameDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductDataPtrs"))
attribute = test_node.get_attribute("inputs:renderProductDataPtrs")
db_value = database.inputs.renderProductDataPtrs
expected_value = []
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductPath"))
attribute = test_node.get_attribute("inputs:renderProductPath")
db_value = database.inputs.renderProductPath
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductPaths"))
attribute = test_node.get_attribute("inputs:renderProductPaths")
db_value = database.inputs.renderProductPaths
expected_value = []
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:swhFrameNumber"))
attribute = test_node.get_attribute("inputs:swhFrameNumber")
db_value = database.inputs.swhFrameNumber
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:cudaStream"))
attribute = test_node.get_attribute("outputs:cudaStream")
db_value = database.outputs.cudaStream
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:renderProductPath"))
attribute = test_node.get_attribute("outputs:renderProductPath")
db_value = database.outputs.renderProductPath
self.assertTrue(test_node.get_attribute_exists("outputs:renderResults"))
attribute = test_node.get_attribute("outputs:renderResults")
db_value = database.outputs.renderResults
self.assertTrue(test_node.get_attribute_exists("outputs:swhFrameNumber"))
attribute = test_node.get_attribute("outputs:swhFrameNumber")
db_value = database.outputs.swhFrameNumber
| 4,282 | Python | 50.602409 | 116 | 0.699673 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/ogn/tests/TestOgnSdPostSemanticBoundingBox.py | import omni.kit.test
import omni.graph.core as og
import omni.graph.core.tests as ogts
import os
class TestOgn(ogts.OmniGraphTestCase):
async def test_data_access(self):
from omni.syntheticdata.ogn.OgnSdPostSemanticBoundingBoxDatabase import OgnSdPostSemanticBoundingBoxDatabase
test_file_name = "OgnSdPostSemanticBoundingBoxTemplate.usda"
usd_path = os.path.join(os.path.dirname(__file__), "usd", test_file_name)
if not os.path.exists(usd_path):
self.assertTrue(False, f"{usd_path} not found for loading test")
(result, error) = await ogts.load_test_file(usd_path)
self.assertTrue(result, f'{error} on {usd_path}')
test_node = og.Controller.node("/TestGraph/Template_omni_syntheticdata_SdPostSemanticBoundingBox")
database = OgnSdPostSemanticBoundingBoxDatabase(test_node)
self.assertTrue(test_node.is_valid())
node_type_name = test_node.get_type_name()
self.assertEqual(og.GraphRegistry().get_node_type_version(node_type_name), 1)
def _attr_error(attribute: og.Attribute, usd_test: bool) -> str:
test_type = "USD Load" if usd_test else "Database Access"
return f"{node_type_name} {test_type} Test - {attribute.get_name()} value error"
self.assertTrue(test_node.get_attribute_exists("inputs:exec"))
attribute = test_node.get_attribute("inputs:exec")
db_value = database.inputs.exec
self.assertTrue(test_node.get_attribute_exists("inputs:gpu"))
attribute = test_node.get_attribute("inputs:gpu")
db_value = database.inputs.gpu
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMapSDCudaPtr"))
attribute = test_node.get_attribute("inputs:instanceMapSDCudaPtr")
db_value = database.inputs.instanceMapSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:instanceMappingInfoSDPtr"))
attribute = test_node.get_attribute("inputs:instanceMappingInfoSDPtr")
db_value = database.inputs.instanceMappingInfoSDPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderProductResolution"))
attribute = test_node.get_attribute("inputs:renderProductResolution")
db_value = database.inputs.renderProductResolution
expected_value = [0, 0]
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:renderVar"))
attribute = test_node.get_attribute("inputs:renderVar")
db_value = database.inputs.renderVar
expected_value = ""
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:rp"))
attribute = test_node.get_attribute("inputs:rp")
db_value = database.inputs.rp
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticLocalTransformSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticLocalTransformSDCudaPtr")
db_value = database.inputs.semanticLocalTransformSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("inputs:semanticMapSDCudaPtr"))
attribute = test_node.get_attribute("inputs:semanticMapSDCudaPtr")
db_value = database.inputs.semanticMapSDCudaPtr
expected_value = 0
actual_value = og.Controller.get(attribute)
ogts.verify_values(expected_value, actual_value, _attr_error(attribute, True))
ogts.verify_values(expected_value, db_value, _attr_error(attribute, False))
self.assertTrue(test_node.get_attribute_exists("outputs:exec"))
attribute = test_node.get_attribute("outputs:exec")
db_value = database.outputs.exec
self.assertTrue(test_node.get_attribute_exists("outputs:sdSemBBoxExtentCudaPtr"))
attribute = test_node.get_attribute("outputs:sdSemBBoxExtentCudaPtr")
db_value = database.outputs.sdSemBBoxExtentCudaPtr
self.assertTrue(test_node.get_attribute_exists("outputs:sdSemBBoxInfosCudaPtr"))
attribute = test_node.get_attribute("outputs:sdSemBBoxInfosCudaPtr")
db_value = database.outputs.sdSemBBoxInfosCudaPtr
| 5,750 | Python | 52.747663 | 116 | 0.70087 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/viewport_legacy.py | from pathlib import Path
from pxr import Sdf
import carb.settings
import omni.ui as ui
import omni.usd
from .SyntheticData import SyntheticData
from .visualizer_window import VisualizerWindow
import weakref
CURRENT_PATH = Path(__file__).parent.absolute()
ICON_PATH = CURRENT_PATH.parent.parent.parent.joinpath("data")
BUTTON_STYLE = {
"height": 22,
"width": 26,
"style": {"Button": {"padding": 4, "background_color": 0x80303030}},
"image_height": 14,
"image_width": 26,
}
MENU_FLAGS = {"flags": ui.WINDOW_FLAGS_POPUP | ui.WINDOW_FLAGS_NO_TITLE_BAR, "auto_resize": True}
class ViewportLegacy:
_g_visualizers = {}
_g_iface = None
@staticmethod
def create_update_subscription():
import omni.kit.viewport_legacy
ViewportLegacy._g_iface = omni.kit.viewport_legacy.get_viewport_interface()
if ViewportLegacy._g_iface is None:
return
import omni.kit.app
event_stream = omni.kit.app.get_app().get_update_event_stream()
return event_stream.create_subscription_to_pop(ViewportLegacy._on_update, name="omni.syntheticdata update")
@staticmethod
def close_viewports():
visualizers, ViewportLegacy._g_visualizers = ViewportLegacy._g_visualizers, {}
if visualizers:
for visualizer, vp_delegate in visualizers.values():
visualizer.close()
vp_delegate.destroy()
@staticmethod
def _on_update(dt):
stage = omni.usd.get_context().get_stage()
if stage is None:
return
# retrieve the list of active viewports
viewport_names = set([ViewportLegacy._g_iface.get_viewport_window_name(vp) for vp in ViewportLegacy._g_iface.get_instance_list()])
visualizers = ViewportLegacy._g_visualizers
# remove obsolete extension viewports data
for vp_name in set(visualizers.keys()).difference(viewport_names):
visualizer, vp_delegate = visualizers[vp_name]
visualizer.close()
vp_delegate.destroy()
del visualizers[vp_name]
# create missing extension viewports data
for vp_name in viewport_names.difference(set(visualizers.keys())):
vp_delegate = ViewportLegacy(vp_name)
visualizer_window = VisualizerWindow(vp_name, vp_delegate)
vp_delegate.set_visualizer_window(weakref.proxy(visualizer_window))
visualizers[vp_name] = visualizer_window, vp_delegate
# update all valid viewport
for vp_name, vis_and_delegate in visualizers.items():
legacy_vp = ViewportLegacy._g_iface.get_viewport_window(ViewportLegacy._g_iface.get_instance(vp_name))
if legacy_vp:
visualizer, vp_delegate = vis_and_delegate
camera_path = legacy_vp.get_active_camera()
vp_delegate._update_legacy_buttons(Sdf.Path(camera_path).name, legacy_vp.is_visible())
visualizer.update(legacy_vp.get_render_product_path(), stage)
def __init__(self, name: str):
self.__window_name = name
self.__visualizer_window = None
# initialize ui
self.__menus = None
self.__btns = {"window": ui.Window(name, detachable=False)}
with self.__btns["window"].frame:
with ui.VStack():
ui.Spacer(height=4)
with ui.HStack(height=0, width=0):
self.__btns["spacer"] = ui.Spacer(width=300)
self.__btns["icon"] = ui.Button(
tooltip="Synthetic Data Sensors", image_url=f"{ICON_PATH}/sensor_icon.svg", **BUTTON_STYLE
)
self.__btns["icon"].set_mouse_pressed_fn(lambda x, y, *_: self._show_legacy_ui_menu(x, y))
def __del__(self):
self.destroy()
def destroy(self):
self.__btns = None
self.__menus = None
self.__window_name = None
self.__visualizer_window = None
def set_visualizer_window(self, visualizer_window):
self.__visualizer_window = visualizer_window
def _update_legacy_buttons(self, cam_name: str, is_visible: bool):
# update the buttons in a legacy viewport (dependent on camera name length)
render_mode = carb.settings.get_settings().get("/rtx/rendermode")
render_spacing = 15
if render_mode == "RaytracedLighting":
render_spacing = 12
elif render_mode == "PathTracing":
render_spacing = 31
spacing = 5 + (len(cam_name) + render_spacing) * 15
self.__btns["spacer"].width = ui.Length(max(300, spacing))
self.__btns["window"].visible = is_visible
def _build_legacy_ui_menu(self):
self.__menus = ui.Window(f"{self.__window_name}-sensor-menu", **MENU_FLAGS)
with self.__menus.frame:
with ui.VStack(width=200, spacing=5):
render_product_combo_model = self.__visualizer_window.render_product_combo_model
if render_product_combo_model:
with ui.HStack(height=40):
ui.Label("RenderProduct", width=150)
ui.ComboBox(render_product_combo_model)
render_var_combo_model = self.__visualizer_window.render_var_combo_model
if render_var_combo_model:
with ui.HStack(height=40):
ui.Label("RenderVar", width=150)
ui.ComboBox(render_var_combo_model)
with ui.HStack(height=20):
model = ui.FloatSlider(name="angle", min=-100.0, max=100.0).model
model.add_value_changed_fn(
lambda m: render_var_combo_model.set_combine_angle(m.get_value_as_float())
)
model = ui.FloatSlider(name="x", min=-100.0, max=100.0).model
model.add_value_changed_fn(
lambda m: render_var_combo_model.set_combine_divide_x(m.get_value_as_float())
)
model = ui.FloatSlider(name="y", min=-100.0, max=100.0).model
model.add_value_changed_fn(
lambda m: render_var_combo_model.set_combine_divide_y(m.get_value_as_float())
)
with ui.HStack(height=40):
ui.Label("Synthetic Data Sensors", width=150)
btn = ui.Button("Clear All")
selection_stack = ui.VStack(spacing=5)
btn.set_clicked_fn(lambda ss=selection_stack: self._clear_all(ss))
selection_stack.clear()
with selection_stack:
self._build_ui_sensor_selection()
self.__menus.visible = False
# callback to reset the sensor selection
def _clear_all(self, selection_stack):
self.__visualizer_window.visualization_activation.clear()
selection_stack.clear()
with selection_stack:
self._build_ui_sensor_selection()
def _show_window(self):
self.__visualizer_window.toggle_enable_visualization()
SyntheticData.disable_async_rendering()
def _build_ui_sensor_selection(self):
for sensor_label, sensor in SyntheticData.get_registered_visualization_template_names_for_display():
with ui.HStack():
ui.Label(sensor_label, width=300)
cb = ui.CheckBox(
width=0, style={"font_size": 24, "margin": 3}, style_type_name_override="Options.CheckBox"
)
cb.model.set_value(sensor in self.__visualizer_window.visualization_activation)
cb.model.add_value_changed_fn(lambda c, s=sensor: self.__visualizer_window.on_sensor_item_clicked(c.as_bool, s))
ui.Button("Show", height=40, clicked_fn=lambda: self._show_window())
def _show_legacy_ui_menu(self, x, y):
self.__menus = None
self._build_legacy_ui_menu()
self.__menus.position_x = x
self.__menus.position_y = y
self.__menus.visible = True
@property
def render_product_path(self):
legacy_vp = ViewportLegacy._g_iface.get_viewport_window(ViewportLegacy._g_iface.get_instance(self.__window_name))
return legacy_vp.get_render_product_path() if legacy_vp else None
@render_product_path.setter
def render_product_path(self, prim_path: str):
legacy_vp = ViewportLegacy._g_iface.get_viewport_window(ViewportLegacy._g_iface.get_instance(self.__window_name))
if legacy_vp:
legacy_vp.set_render_product_path(prim_path)
@property
def usd_context(self):
legacy_vp = ViewportLegacy._g_iface.get_viewport_window(ViewportLegacy._g_iface.get_instance(self.__window_name))
usd_context_name = legacy_vp.get_usd_context_name() if hasattr(legacy_vp, 'get_usd_context_name') else ''
return omni.usd.get_context(usd_context_name)
| 9,000 | Python | 41.658768 | 138 | 0.597889 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/helpers.py | import math
from functools import lru_cache
import numpy.lib.recfunctions as rfn
import carb
import numpy as np
import omni.usd
from pxr import UsdGeom, UsdShade, Semantics
from .. import _syntheticdata
EPS = 1e-8
@lru_cache()
def _get_syntheticdata_iface():
return _syntheticdata.acquire_syntheticdata_interface()
def _interpolate(p, a, b):
p0 = 1.0 - p
return [int(p0 * a[0] + p * b[0]), int(p0 * a[1] + p * b[1]), int(p0 * a[2] + p * b[2]), 255]
def get_bbox_3d_corners(extents):
"""Return transformed points in the following order: [LDB, RDB, LUB, RUB, LDF, RDF, LUF, RUF]
where R=Right, L=Left, D=Down, U=Up, B=Back, F=Front and LR: x-axis, UD: y-axis, FB: z-axis.
Args:
extents (numpy.ndarray): A structured numpy array containing the fields: [`x_min`, `y_min`,
`x_max`, `y_max`, `transform`.
Returns:
(numpy.ndarray): Transformed corner coordinates with shape `(N, 8, 3)`.
"""
rdb = [extents["x_max"], extents["y_min"], extents["z_min"]]
ldb = [extents["x_min"], extents["y_min"], extents["z_min"]]
lub = [extents["x_min"], extents["y_max"], extents["z_min"]]
rub = [extents["x_max"], extents["y_max"], extents["z_min"]]
ldf = [extents["x_min"], extents["y_min"], extents["z_max"]]
rdf = [extents["x_max"], extents["y_min"], extents["z_max"]]
luf = [extents["x_min"], extents["y_max"], extents["z_max"]]
ruf = [extents["x_max"], extents["y_max"], extents["z_max"]]
tfs = extents["transform"]
corners = np.stack((ldb, rdb, lub, rub, ldf, rdf, luf, ruf), 0)
corners_homo = np.pad(corners, ((0, 0), (0, 1), (0, 0)), constant_values=1.0)
return np.einsum("jki,ikl->ijl", corners_homo, tfs)[..., :3]
def reduce_bboxes_2d(bboxes, instance_mappings):
"""
Reduce 2D bounding boxes of leaf nodes to prims with a semantic label.
Args:
bboxes (numpy.ndarray): A structured numpy array containing the fields: `[
("instanceId", "<u4"), ("semanticId", "<u4"), ("x_min", "<i4"),
("y_min", "<i4"), ("x_max", "<i4"), ("y_max", "<i4")]`
instance_mappings (numpy.ndarray): A structured numpy array containing the fields:
`[("uniqueId", np.int32), ("name", "O"), ("semanticId", "<u4"), ("semanticLabel", "O"),
("instanceIds", "O"), ("metadata", "O")]`
Returns:
(numpy.ndarray): A structured numpy array containing the fields: `[
("uniqueId", np.int32), ("name", "O"), ("semanticLabel", "O"), ("instanceIds", "O"),
("semanticId", "<u4"), ("metadata", "O"), ("x_min", "<i4"), ("y_min", "<i4"),
("x_max", "<i4"), ("y_max", "<i4")]`
"""
bboxes = bboxes[bboxes["x_min"] < 2147483647]
reduced_bboxes = []
for im in instance_mappings:
if im["instanceIds"]: # if mapping has descendant instance ids
mask = np.isin(bboxes["instanceId"], im["instanceIds"])
bbox_masked = bboxes[mask]
if len(bbox_masked) > 0:
reduced_bboxes.append(
(
im["uniqueId"],
im["name"],
im["semanticLabel"],
im["metadata"],
im["instanceIds"],
im["semanticId"],
np.min(bbox_masked["x_min"]),
np.min(bbox_masked["y_min"]),
np.max(bbox_masked["x_max"]),
np.max(bbox_masked["y_max"]),
)
)
return np.array(
reduced_bboxes,
dtype=[("uniqueId", np.int32), ("name", "O"), ("semanticLabel", "O"), ("metadata", "O"), ("instanceIds", "O")]
+ bboxes.dtype.descr[1:],
)
def reduce_bboxes_3d(bboxes, instance_mappings):
"""
Reduce 3D bounding boxes of leaf nodes to prims with a semantic label.
Args:
bboxes (numpy.ndarray): A structured numpy array containing the fields: `[
("instanceId", "<u4"), ("semanticId", "<u4"), ("x_min", "<i4"),
("y_min", "<i4"), ("z_min", "<i4"), ("x_max", "<i4"), ("y_max", "<i4"),
("z_max", "<i4"), ("transform", "<f4", (4, 4))]`
instance_mappings (numpy.ndarray): A structured numpy array containing the fields:
`[("uniqueId", np.int32), ("name", "O"), ("semanticId", "<u4"), ("semanticLabel", "O"),
("instanceIds", "<u4"), ("metadata", "O")]`
Returns:
(numpy.ndarray): A structured numpy array containing the fields: `[("uniqueId", np.int32)
("name", "O"), ("semanticLabel", "O"), ("instanceIds", "O"), ("metadata", "O"),
("semanticId", "<u4"),("x_min", "<i4"), ("y_min", "<i4"), ("z_min", "<i4"),
("x_max", "<i4"), ("y_max", "<i4"), ("z_max", "<i4"), ("transform", "<f4", (4, 4))]`
If `corners` field is supplied in `bboxes` argument, the field will be updated accordingly.
"""
current_time = omni.timeline.get_timeline_interface().get_current_time()
reduced_bboxes = []
stage = omni.usd.get_context().get_stage()
if "corners" in bboxes.dtype.names:
corners = bboxes["corners"]
else:
# TODO if not corners, use extents
corners = get_bbox_3d_corners(bboxes)
max_instance_id = bboxes["instanceId"].max()
idx_lut = np.zeros(max_instance_id + 1, dtype=np.uint32)
for i, bb_id in enumerate(bboxes["instanceId"]):
idx_lut[bb_id] = i
for i, im in enumerate(instance_mappings):
prim = stage.GetPrimAtPath(im["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(current_time))
tf_inv = np.linalg.inv(tf)
# filter instance ids that corresponding to invisible bounding boxes (not filtered in the instance mapping)
instIds = [instId for instId in im["instanceIds"] if instId < len(idx_lut)]
if len(instIds) == 0:
continue
idxs = idx_lut[instIds]
children_corners = corners[idxs]
children_corners_homo = np.pad(children_corners.reshape(-1, 3), ((0, 0), (0, 1)), constant_values=1.0)
corners_local = np.einsum("bj,jk->bk", children_corners_homo, tf_inv)[:, :3]
corners_local_min = corners_local[..., :3].reshape(-1, 3).min(0)
corners_local_max = corners_local[..., :3].reshape(-1, 3).max(0)
extents_local = np.stack([corners_local_min, corners_local_max])
row = [
im["uniqueId"],
im["name"],
im["semanticLabel"],
im["metadata"],
im["instanceIds"],
im["semanticId"],
*extents_local.reshape(-1),
tf,
]
if "corners" in bboxes.dtype.names:
world_corners = get_bbox_3d_corners(
{
"x_min": [extents_local[0, 0]],
"x_max": [extents_local[1, 0]],
"y_min": [extents_local[0, 1]],
"y_max": [extents_local[1, 1]],
"z_min": [extents_local[0, 2]],
"z_max": [extents_local[1, 2]],
"transform": [tf],
}
)
row.append(world_corners)
reduced_bboxes.append(tuple(row))
return np.array(
reduced_bboxes,
dtype=[("uniqueId", np.int32), ("name", "O"), ("semanticLabel", "O"), ("metadata", "O"), ("instanceIds", "O")]
+ bboxes.dtype.descr[1:],
)
def merge_sensors(
bounding_box_2d_tight=None, bounding_box_2d_loose=None, bounding_box_3d=None, occlusion_quadrants=None
):
"""
Merge sensor structured array outputs.
Args:
bounding_box_2d_tight (numpy.ndarray, optional): A structured numpy array
containing the fields: `[("uniqueId", "<i4"), ("name", "O"), ("semanticLabel", "O"),
("semanticId", "<u4"), ("metadata", "O"), ("instanceIds", "O"),
("x_min", "<i4"), ("y_min", "<i4"), ("x_max", "<i4"), ("y_max", "<i4")]`
bounding_box_2d_loose (numpy.ndarray, optional): A structured numpy array
containing the fields: `[("uniqueId", "<i4"), ("name", "O"), ("semanticLabel", "O"),
("instanceId", "<u4"), ("semanticId", "<u4"), ("metadata", "O"), ("instanceIds", "O"),
("x_min", "<i4"), ("y_min", "<i4"), ("x_max", "<i4"), ("y_max", "<i4")]`
bounding_box_3d (numpy.ndarray, optional): A structured numpy array containing the fields:
`[("uniqueId", "<i4"), ("name", "O"), ("semanticLabel", "O"), ("semanticId", "<u4"),
("metadata", "O"), ("instanceIds", "O"), ("x_min", "<i4"), ("y_min", "<i4"), ("z_min", "<i4"),
("x_max", "<i4"), ("y_max", "<i4"), ("z_max", "<i4"), ("transform", "<f4", (4, 4))]`
occlusion_quadrants (numpy.ndarray, optional): A structured numpy array containing the fields:
[("uniqueId", "<i4"), ("name", "O"), ("semanticLabel", "O"),("semanticId", "<u4"),
("metadata", "O"), ("instanceIds", "O"), ("occlusion_quadrant", "O")]
Returns:
(numpy.ndarray): A structured array containing merged data from the arguments supplied.
"""
arrays = []
array_suffixes = []
defaults = {"x_min": -1, "x_max": -1, "y_min": -1, "y_max": -1, "z_min": -1, "z_max": -1}
# Add valid arrays to merge list and set suffixes
if bounding_box_2d_tight is not None:
arrays.append(bounding_box_2d_tight)
array_suffixes.append("_bbox2d_tight")
if bounding_box_2d_loose is not None:
arrays.append(bounding_box_2d_loose)
array_suffixes.append("_bbox2d_loose")
if bounding_box_3d is not None:
arrays.append(bounding_box_3d)
array_suffixes.append("_bbox3d")
if occlusion_quadrants is not None:
arrays.append(occlusion_quadrants)
array_suffixes.append("_occ")
if not arrays:
return None
r0 = arrays.pop()
r0_suf = array_suffixes.pop()
while arrays:
r1 = arrays.pop()
r1_suf = array_suffixes.pop()
# Add suffixes
r0.dtype.names = [f"{n}{r0_suf}" if n in defaults.keys() else n for n in r0.dtype.names]
r1.dtype.names = [f"{n}{r1_suf}" if n in defaults.keys() else n for n in r1.dtype.names]
defaults_suf = {}
defaults_suf.update({f"{k}{r0_suf}": v for k, v in defaults.items()})
defaults_suf.update({f"{k}{r1_suf}": v for k, v in defaults.items()})
r0 = rfn.join_by(
["uniqueId", "name", "semanticId", "semanticLabel", "metadata", "instanceIds"],
r0,
r1,
defaults=defaults_suf,
r1postfix=r0_suf,
r2postfix=r1_suf,
jointype="outer",
usemask=False,
)
r0_suf = ""
return r0
def get_projection_matrix(fov, aspect_ratio, z_near, z_far):
"""
Calculate the camera projection matrix.
Args:
fov (float): Field of View (in radians)
aspect_ratio (float): Image aspect ratio (Width / Height)
z_near (float): distance to near clipping plane
z_far (float): distance to far clipping plane
Returns:
(numpy.ndarray): View projection matrix with shape `(4, 4)`
"""
a = -1.0 / math.tan(fov / 2)
b = -a * aspect_ratio
c = z_far / (z_far - z_near)
d = z_near * z_far / (z_far - z_near)
return np.array([[a, 0.0, 0.0, 0.0], [0.0, b, 0.0, 0.0], [0.0, 0.0, c, 1.0], [0.0, 0.0, d, 0.0]])
def get_view_proj_mat(view_params):
"""
Get View Projection Matrix.
Args:
view_params (dict): dictionary containing view parameters
"""
z_near, z_far = view_params["clipping_range"]
view_matrix = np.linalg.inv(view_params["view_to_world"])
fov = 2 * math.atan(view_params["horizontal_aperture"] / (2 * view_params["focal_length"]))
projection_mat = get_projection_matrix(fov, view_params["aspect_ratio"], z_near, z_far)
return np.dot(view_matrix, projection_mat)
def project_pinhole(points, view_params):
"""
Project 3D points to 2D camera view using a pinhole camera model.
Args:
points (numpy.ndarray): Array of points in world frame of shape (num_points, 3).
view_params:
Returns:
(numpy.ndarray): Image-space points of shape (num_points, 3)
"""
view_proj_matrix = get_view_proj_mat(view_params)
homo = np.pad(points, ((0, 0), (0, 1)), constant_values=1.0)
tf_points = np.dot(homo, view_proj_matrix)
tf_points = tf_points / (tf_points[..., -1:])
tf_points[..., :2] = 0.5 * (tf_points[..., :2] + 1)
return tf_points[..., :3]
def _parse_semantic_schemas(prim):
""" Return the class name and (type, data) pairs of metadata """
schemas = [s.split(":")[1] for s in prim.GetAppliedSchemas() if "SemanticsAPI" in s]
metadata = []
semantic_class = None
for schema in schemas:
sem = Semantics.SemanticsAPI.Get(prim, schema)
sem_type = sem.GetSemanticTypeAttr().Get()
sem_data = sem.GetSemanticDataAttr().Get()
if sem_type == "class":
semantic_class = sem_data
else:
metadata.append((sem_type, sem_data))
return semantic_class, metadata
def _parse_instance_mappings(cur_prim):
""" Recursively parse instance mappings. """
# TODO @jlafleche currently not compatible with two labels per prim
instance_mappings = []
children = cur_prim.GetChildren()
instance_ids = _get_syntheticdata_iface().get_instance_segmentation_id(cur_prim.GetPath().pathString).tolist()
if children:
for child in children:
child_instance_ids, child_instance_mappings = _parse_instance_mappings(child)
instance_ids += child_instance_ids
instance_mappings += child_instance_mappings
has_prim_semantics = cur_prim.HasAPI(Semantics.SemanticsAPI)
material = UsdShade.MaterialBindingAPI(cur_prim).ComputeBoundMaterial()[0].GetPrim()
has_material_semantics = material and material.HasAPI(Semantics.SemanticsAPI)
if has_prim_semantics and instance_ids:
semantic_class, metadata = _parse_semantic_schemas(cur_prim)
if semantic_class:
semantic_id = _get_syntheticdata_iface().get_semantic_segmentation_id_from_data("class", semantic_class)
instance_mappings.append((str(cur_prim.GetPath()), semantic_id, semantic_class, instance_ids, metadata))
elif has_material_semantics and instance_ids:
semantic_class, metadata = _parse_semantic_schemas(material)
if semantic_class:
semantic_id = _get_syntheticdata_iface().get_semantic_segmentation_id_from_data("class", semantic_class)
instance_mappings.append((str(cur_prim.GetPath()), semantic_id, semantic_class, instance_ids, metadata))
return instance_ids, instance_mappings
def get_instance_mappings():
"""
Get instance mappings.
Uses update number as frame ID for caching.
"""
app = omni.kit.app.get_app_interface()
frame_id = app.get_update_number()
mappings = _get_instance_mappings(frame_id)
return mappings
@lru_cache(maxsize=1)
def _get_instance_mappings(frame_id=None):
"""
Get instance mappings.
Uses `frame_id` for caching.
"""
stage = omni.usd.get_context().get_stage()
""" Use the C++ API to retrieve the instance mapping """
# _, instance_mappings = _parse_instance_mappings(stage.GetPseudoRoot())
# mappings_raw = [(i + 1, *im) for i, im in enumerate(instance_mappings)]
mappings_raw = _get_syntheticdata_iface().get_instance_mapping_list()
mappings = np.array(
mappings_raw,
dtype=[
("uniqueId", np.int32),
("name", "O"),
("semanticId", np.int32),
("semanticLabel", "O"),
("instanceIds", "O"),
("metadata", "O"),
],
)
return mappings
def reduce_occlusion(occlusion_data, instance_mappings):
"""
Reduce occlusion value of leaf nodes to prims with a semantic label.
Args:
sensor_data (numpy.ndarray): A structured numpy array with the fields: [("instanceId", "<u4"),
("semanticId", "<u4"), ("occlusionRatio", "<f4")], where occlusion ranges from 0
(not occluded) to 1 (fully occluded).
Returns:
(numpy.ndarray): A structured numpy array with the fields: [("uniqueId", np.int32)
("name", "O"), ("semanticLabel", "O"), ("instanceIds", "O"), ("semanticId", "<u4"),
("metadata", "O"), ("occlusionRatio", "<f4")]
"""
mapped_data = []
occlusion_data = occlusion_data[~np.isnan(occlusion_data["occlusionRatio"])]
for im in instance_mappings:
if im["instanceIds"]: # if mapping has descendant instance ids
mask = np.isin(occlusion_data["instanceId"], im["instanceIds"])
if mask.sum() > 1:
carb.log_warn(
f"[syntheticdata.viz] Mapping on {im['name']} contains multiple child meshes, occlusion value may be incorrect."
)
occ = occlusion_data[mask]
if len(occ) > 0:
mapped_data.append(
(
im["uniqueId"],
im["name"],
im["semanticLabel"],
im["metadata"],
im["instanceIds"],
im["semanticId"],
np.mean(occ["occlusionRatio"]),
)
)
return np.array(
mapped_data,
dtype=[("uniqueId", np.int32), ("name", "O"), ("semanticLabel", "O"), ("metadata", "O"), ("instanceIds", "O")]
+ occlusion_data.dtype.descr[1:],
)
def _join_struct_arrays(arrays):
"""
Join N numpy structured arrays.
"""
n = len(arrays[0])
assert all([len(a) == n for a in arrays])
dtypes = sum(([d for d in a.dtype.descr if d[0]] for a in arrays), [])
joined = np.empty(n, dtype=dtypes)
for a in arrays:
joined[list(a.dtype.names)] = a
return joined
def _fish_eye_map_to_sphere(screen, screen_norm, theta, max_fov):
""" Utility function to map a sample from a disk on the image plane to a sphere. """
direction = np.array([[0, 0, -1]] * screen.shape[0], dtype=np.float)
extent = np.zeros(screen.shape[0], dtype=np.float)
# A real fisheye have some maximum FOV after which the lens clips.
valid_mask = theta <= max_fov
# Map to a disk: screen / R normalizes the polar direction in screen space.
xy = screen[valid_mask]
screen_norm_mask = screen_norm[valid_mask] > 1e-5
xy[screen_norm_mask] = xy[screen_norm_mask] / screen_norm[valid_mask, None]
# Map disk to a sphere
cos_theta = np.cos(theta[valid_mask])
sin_theta = np.sqrt(1.0 - cos_theta ** 2)
# Todo: is this right? Do we assume z is negative (RH coordinate system)?
z = -cos_theta
xy = xy * sin_theta[:, None]
direction[valid_mask] = np.stack([xy[valid_mask, 0], xy[valid_mask, 1], z], axis=1)
extent[valid_mask] = 1.0 # < far clip is not a plane, it's a sphere!
return direction, extent
def project_fish_eye_map_to_sphere(direction):
z = direction[:, 2:]
cos_theta = -z
theta = np.arccos(np.clip(cos_theta, 0.0, 1.0))
theta = np.arccos(cos_theta)
# TODO currently projecting outside of max FOV
sin_theta = np.sqrt(1.0 - cos_theta * cos_theta + EPS)
xy = direction[:, :2] / (sin_theta + EPS)
return xy, theta
def fish_eye_polynomial(ndc, view_params):
""" FTheta camera model based on DW src/rigconfiguration/CameraModelsNoEigen.hpp """
# Convert NDC pixel position to screen space... well almost. It is screen space but the extent of x is [-0.5, 0.5]
# and the extent of y is [-0.5/aspectRatio, 0.5/aspectRatio].
screen = ndc - 0.5
aspect_ratio = view_params["aspect_ratio"]
screen[:, 1] /= -aspect_ratio
# The FTheta polynomial works at a nominal resolution. So far we have done calculations in NDC to be
# resolution independent. Here we scale by the nominal resolution in X.
screen = (screen - view_params["ftheta"]["c_ndc"]) * view_params["ftheta"]["width"]
# Compute the radial distance on the screen from its center point
r = np.sqrt(screen[:, 0] ** 2 + screen[:, 1] ** 2)
theta = ftheta_distortion(view_params["ftheta"], r)
max_fov = math.radians(view_params["ftheta"]["max_fov"] / 2)
return _fish_eye_map_to_sphere(screen, r, theta, max_fov)
def project_fish_eye_polynomial(points, view_params):
""" Project F-Theta camera model.
Args:
points (numpy.ndarray): Array of points in world frame of shape (num_points, 3).
view_params (dict): dictionary containing view parameters
Returns:
(numpy.ndarray): Image-space points of shape (num_points, 3)
"""
points_h = np.pad(points, ((0, 0), (0, 1)), constant_values=1)
points_cam_frame = np.einsum("jk,kl->jl", points_h, view_params["world_to_view"])[..., :3]
directions = points_cam_frame / np.linalg.norm(points_cam_frame + EPS, axis=1)[:, None]
xy, theta = project_fish_eye_map_to_sphere(directions)
r = _ftheta_distortion_solver(view_params["ftheta"], theta)
screen = xy * r
screen = screen / view_params["ftheta"]["width"] + view_params["ftheta"]["c_ndc"]
screen[:, 1] *= -view_params["aspect_ratio"]
ndc = screen + 0.5
ndc = np.pad(ndc, ((0, 0), (0, 1)), constant_values=0)
return ndc
def get_view_params(viewport):
""" Get view parameters.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Returns:
(dict): Dictionary containing view parameters.
"""
stage = omni.usd.get_context().get_stage()
camera = stage.GetPrimAtPath(viewport.camera_path)
current_time = omni.timeline.get_timeline_interface().get_current_time()
view_to_world = UsdGeom.Imageable(camera).ComputeLocalToWorldTransform(current_time)
world_to_view = view_to_world.GetInverse()
width, height = viewport.resolution
projection_type = camera.GetAttribute("cameraProjectionType").Get(current_time)
if projection_type == "fisheyePolynomial":
ftheta = {
"width": camera.GetAttribute("fthetaWidth").Get(),
"height": camera.GetAttribute("fthetaHeight").Get(),
"cx": camera.GetAttribute("fthetaCx").Get(),
"cy": camera.GetAttribute("fthetaCy").Get(),
"poly_a": camera.GetAttribute("fthetaPolyA").Get(),
"poly_b": camera.GetAttribute("fthetaPolyB").Get(),
"poly_c": camera.GetAttribute("fthetaPolyC").Get(),
"poly_d": camera.GetAttribute("fthetaPolyD").Get(),
"poly_e": camera.GetAttribute("fthetaPolyE").Get(),
"max_fov": camera.GetAttribute("fthetaMaxFov").Get(),
}
ftheta["edge_fov"] = ftheta_distortion(ftheta, ftheta["width"] / 2)
ftheta["c_ndc"] = np.array(
[
(ftheta["cx"] - ftheta["width"] / 2) / ftheta["width"],
(ftheta["height"] / 2 - ftheta["cy"]) / ftheta["width"],
]
)
else:
ftheta = None
view_params = {
"view_to_world": np.array(view_to_world),
"world_to_view": np.array(world_to_view),
"projection_type": projection_type,
"ftheta": ftheta,
"width": width,
"height": height,
"aspect_ratio": width / height,
"clipping_range": camera.GetAttribute("clippingRange").Get(current_time),
"horizontal_aperture": camera.GetAttribute("horizontalAperture").Get(current_time),
"focal_length": camera.GetAttribute("focalLength").Get(current_time),
}
return view_params
def image_to_world(image_coordinates, view_params):
""" Map each image coordinate to a corresponding direction vector.
Args:
pixel (numpy.ndarray): Pixel coordinates of shape (num_pixels, 2)
view_params (dict): dictionary containing view parameters
Returns
(numpy.ndarray): Direction vectors of shape (num_pixels, 3)
"""
ndc = image_coordinates / np.array([view_params["width"], view_params["height"]])
direction, extent = fish_eye_polynomial(ndc, view_params)
view_to_world = view_params["view_to_world"]
origin = np.matmul(np.array([0, 0, 0, 1]), view_to_world)[:3]
direction = np.matmul(np.pad(direction, ((0, 0), (0, 1)), constant_values=0), view_to_world)[:, :3]
direction /= np.linalg.norm(direction, axis=1, keepdims=True)
return origin, direction
def world_to_image(points, viewport, view_params=None):
""" Project world coordinates to image-space.
Args:
points (numpy.ndarray): Array of points in world frame of shape (num_points, 3).
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
view_params (dict, Optional): View parameters dictionary obtained from
`omni.syntheticdata.helpers.get_view_params(viewport)`. Will be computed for current viewport state
if not provided.
Returns:
(numpy.ndarray): Image-space points of shape (num_points, 3)
"""
if view_params is None:
view_params = get_view_params(viewport)
if view_params["projection_type"] == "pinhole" or view_params["projection_type"] is None:
points_image_space = project_pinhole(points, view_params)
elif view_params["projection_type"] == "fisheyePolynomial":
points_image_space = project_fish_eye_polynomial(points, view_params)
else:
raise ValueError(f"Projection type {view_params['projection_type']} is not currently supported.")
return points_image_space
def ftheta_distortion(ftheta, x):
""" F-Theta distortion. """
return ftheta["poly_a"] + x * (
ftheta["poly_b"] + x * (ftheta["poly_c"] + x * (ftheta["poly_d"] + x * ftheta["poly_e"]))
)
def ftheta_distortion_prime(ftheta, x):
""" Derivative to f_theta_distortion. """
return ftheta["poly_b"] + x * (2 * ftheta["poly_c"] + x * (3 * ftheta["poly_d"] + x * 4 * ftheta["poly_e"]))
def _ftheta_distortion_solver(ftheta, y):
# Guess by linear approximation. 2 loops provides sufficient precision in working range.
ratio = ftheta["width"] / 2 / ftheta["edge_fov"]
guess = y * ratio
for i in range(2):
guessed_y = ftheta_distortion(ftheta, guess)
dy = y - guessed_y
dx = ftheta_distortion_prime(ftheta, guess)
mask = dx != 0
guess[mask] += dy[mask] / dx[mask]
guess[~mask] += dy[~mask] * ratio
return guess
| 24,371 | Python | 37.08125 | 117 | 0.636289 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/sensors.py | import carb
import omni.usd
import omni.kit
from pxr import UsdGeom
import numpy as np
import asyncio
from .. import _syntheticdata
from . import helpers
from .SyntheticData import *
def get_synthetic_data():
sdg = SyntheticData.Get()
if not sdg:
SyntheticData.Initialize()
sdg = SyntheticData.Get()
assert sdg
return sdg
async def next_sensor_data_async(viewport=None, waitSimFrame: bool = False, inViewportId: int = None):
"""Wait for frame complete event from Kit for specific viewport. """
# next_sensor_data_async API previously passed inViewportId as ViewportHandle
# This is actually incorrect and bad due to waiting on that handle, which can
# change for a variety of reasons between the retrieval of the handle and
# the wait on it below.
if hasattr(viewport, "frame_info"):
inViewportId = viewport.frame_info.get("viewport_handle")
else:
if inViewportId is None:
if isinstance(viewport, int):
inViewportId = viewport
else:
inViewportId = 0
viewport = None
carb.log_warn(
f"Depreacted usage of next_sensor_data_async with inViewportId={inViewportId}, pass the Viewport instead")
app = omni.kit.app.get_app()
# wait for the next pre_update call
pre_f = asyncio.Future()
def on_pre_event(e: carb.events.IEvent):
if not pre_f.done():
swhFrameNumber = e.payload["SWHFrameNumber"]
# drivesim legacy name
if not swhFrameNumber:
swhFrameNumber = e.payload["frameNumber"]
pre_f.set_result(swhFrameNumber)
sub_pre = app.get_pre_update_event_stream().create_subscription_to_pop(on_pre_event,
name="omni.kit.app._pre_update_async")
# wait the next frame to be rendered
render_f = asyncio.Future()
def on_render_event(e: carb.events.IEvent):
# Grab the ViewportHandle to match from the Viewport if we have it or the legacy inViewportId
cur_viewport_handle = viewport.frame_info.get("viewport_handle") if viewport else inViewportId
viewId = e.payload["viewport_handle"]
frameNumber = e.payload["swh_frame_number"]
if ((viewId == cur_viewport_handle) and (not waitSimFrame or (pre_f.done() and (frameNumber >= pre_f.result())))):
if not render_f.done():
render_f.set_result(frameNumber)
sub_render = (
omni.usd.get_context()
.get_rendering_event_stream()
.create_subscription_to_pop_by_type(
int(omni.usd.StageRenderingEventType.NEW_FRAME),
on_render_event,
name="omni.syntheticdata.sensors._next_sensor_data_async",
order=0,
)
)
MAX_NUM_SKIPPED_UPDATE = 150
num_skipped_update = 0
while (num_skipped_update < MAX_NUM_SKIPPED_UPDATE) and (not render_f.done()):
await app.next_update_async()
num_skipped_update += 1
if num_skipped_update >= MAX_NUM_SKIPPED_UPDATE:
raise SyntheticDataException(f"waiting for next frame failed.")
def enable_sensors(viewport, sensor_types):
""" activate the host buffer copy nodes for given sensor
NB: This function is deprecated
"""
for sensor_type in sensor_types:
rendervar_name = SyntheticData.convert_sensor_type_to_rendervar(sensor_type.name)
get_synthetic_data().activate_node_template(rendervar_name + "ExportRawArray", 0, [viewport.render_product_path])
def disable_sensors(viewport, sensor_types):
""" deactivate the host buffer copy nodes for given sensor
NB: This function is deprecated
"""
for sensor_type in sensor_types:
rendervar_name = SyntheticData.convert_sensor_type_to_rendervar(sensor_type.name)
get_synthetic_data().deactivate_node_template(rendervar_name + "ExportRawArray", 0, [viewport.render_product_path])
def create_or_retrieve_sensor(viewport, sensor_type):
""" Retrieve a sensor for the specified viewport and sensor type.
If the sensor does not exist, it is created. Note that the sensor will be
uninitialized until a frame is rendered after the sensor is created.
NB: This function is deprecated and the asynchronous version below
(create_or_retrieve_sensor_async) should be used instead to ensure sensors
are properly initialized by the renderer after creation
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
sensor_type (omni.syntheticdata._syntheticdata.SensorType): Type of sensor to retrieve/create.
"""
enable_sensors(viewport, [sensor_type])
return sensor_type
async def create_or_retrieve_sensor_async(viewport, sensor_type):
""" Retrieve a sensor for the specified viewport and sensor type.
If the sensor does not exist, it is created. Note that the sensor will be
uninitialized until a frame is rendered after the sensor is created.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
sensor_type (omni.syntheticdata._syntheticdata.SensorType): Type of sensor to retrieve/create.
"""
enable_sensors(viewport, [sensor_type])
await next_sensor_data_async(viewport, True)
return sensor_type
async def initialize_async(viewport, sensor_types):
""" Initialize sensors in the list provided.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
sensor_types (list of omni.syntheticdata._syntheticdata.SensorType): List of sensor types to initialize.
"""
await omni.kit.app.get_app_interface().next_update_async()
enable_sensors(viewport, sensor_types)
await next_sensor_data_async(viewport, True)
def get_sensor_array(viewport, sensor_type, elemType, elemCount, is2DArray):
""" Retrieve the sensor array data from the last sensor node evaluation.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
sensor_type : Sensor type to retrieve the data from.
is2DArray : True if the array to be retrieved is a 2d array
"""
output_names = ["outputs:data"]
if is2DArray:
output_names.append("outputs:width")
output_names.append("outputs:height")
else:
output_names.append("outputs:bufferSize")
rendervar_name = SyntheticData.convert_sensor_type_to_rendervar(sensor_type.name)
outputs = get_synthetic_data().get_node_attributes(rendervar_name + "ExportRawArray", output_names,
viewport.render_product_path)
data = outputs["outputs:data"] if outputs and ("outputs:data" in outputs) else None
if is2DArray:
height = outputs["outputs:height"] if outputs and ("outputs:height" in outputs) else 0
width = outputs["outputs:width"] if outputs and ("outputs:width" in outputs) else 0
bufferSize = height * width * elemCount * np.dtype(elemType).itemsize
else:
bufferSize = outputs["outputs:bufferSize"] if outputs and ("outputs:bufferSize" in outputs) else 0
if (data is None) or (len(data) < np.dtype(elemType).itemsize):
if is2DArray:
shape = (0, 0, elemCount) if elemCount > 1 else (0, 0)
else:
shape = (0, elemCount) if elemCount > 1 else (0)
return np.empty(shape, elemType)
assert bufferSize == len(data)
data = data.view(elemType)
assert len(data) > 0
if not is2DArray:
return data.reshape(data.shape[0] // elemCount, elemCount) if elemCount > 1 else data
return data.reshape(height, width, elemCount) if elemCount > 1 else data.reshape(height, width)
def get_rgb(viewport):
""" Get RGB sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A uint8 array of shape (height, width, 4)
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.Rgb, np.uint8, 4, True)
def get_depth(viewport):
""" Get Inverse Depth sensor output. *** DEPRECATED ***
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape (height, width, 1).
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.Depth, np.float32, 1, True)
def get_depth_linear(viewport):
""" Get Linear Depth sensor output. *** DEPRECATED ***
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape (height, width, 1).
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.DepthLinear, np.float32, 1, True)
def get_distance_to_image_plane(viewport):
""" Get distance to image plane sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape (height, width, 1).
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.DistanceToImagePlane, np.float32, 1, True)
def get_distance_to_camera(viewport):
""" Get distance to camera sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape (height, width, 1).
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.DistanceToCamera, np.float32, 1, True)
def get_camera_3d_position(viewport):
""" Get camera space 3d position sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape (height, width, 4).
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.Camera3dPosition, np.float32, 4, True)
def get_bounding_box_3d(viewport, parsed=False, return_corners=False, camera_frame=False, instance_mappings=None):
""" Get bounding box 3D sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
parsed (bool): If True, return a single bounding box for each prim with a semantic schema.
Otherwise, a bounding box will be provided for each leaf prim.
include_corners (bool): if True, calculate and return the 8 corners of each 3D bounding box.
Corners are returned in the order: [LDB, RDB, LUB, RUB, LDF, RDF, LUF, RUF] where
L=Left, R=Right, D=Down, U=Up, B=Back, F=Front and LR: x-axis, UD: y-axis, FB: z-axis.
camera_frame (bool): If True, the transforms and corners will be returned in the camera's
reference frame. Otherwise, coordinates are returned with respect to the world frame.
Note: The coordinate system is right-handed.
instance_mappings (numpy.ndarray, optional): A structured array returned by `helpers.get_instance_mappings`.
If not provided (default), a new instance mappings will be computed.
Return:
(numpy.ndarray): A structured array with the fields: `[('instanceId', '<u4'), ('semanticId', '<u4'),
("metadata", "O"), ('x_min', '<f4'), ('y_min', '<f4'), ('z_min', '<f4'), ('x_max', '<f4'), ('y_max', '<f4'),
('z_max', '<f4'), ('transform', '<f4', (4, 4))]`. If `return_corners` is `True`, an additional
field `('corners', '<f4', (8, 3)` is returned.
"""
BoundingBox3DValuesType = np.dtype(
[
("instanceId", "<u4"),
("semanticId", "<u4"),
("x_min", "<f4"),
("y_min", "<f4"),
("z_min", "<f4"),
("x_max", "<f4"),
("y_max", "<f4"),
("z_max", "<f4"),
("transform", "<f4", (4, 4)),
]
)
bboxes_3d_data = get_sensor_array(
viewport, _syntheticdata.SensorType.BoundingBox3D, BoundingBox3DValuesType, 1, False
)
# Return immediately if empty
if bboxes_3d_data.size == 0:
return bboxes_3d_data
if return_corners:
corners = helpers.get_bbox_3d_corners(bboxes_3d_data)
corners_struc = np.zeros(len(corners), dtype=[("corners", np.float32, (8, 3))])
corners_struc["corners"] = corners
bboxes_3d_data = helpers._join_struct_arrays([bboxes_3d_data, corners_struc])
if parsed:
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
bboxes_3d_data = helpers.reduce_bboxes_3d(bboxes_3d_data, instance_mappings)
if camera_frame:
stage = omni.usd.get_context().get_stage()
camera = stage.GetPrimAtPath(viewport.camera_path)
current_time = omni.timeline.get_timeline_interface().get_current_time()
tf_mat = np.array(UsdGeom.Camera(camera).ComputeLocalToWorldTransform(current_time))
view_matrix = np.linalg.inv(tf_mat)
bboxes_3d_data["transform"] = np.einsum("ijk,kl->ijl", bboxes_3d_data["transform"], view_matrix)
if return_corners:
corners_homo = np.pad(bboxes_3d_data["corners"], ((0, 0), (0, 0), (0, 1)), constant_values=1.0)
bboxes_3d_data["corners"] = np.einsum("ijk,kl->ijl", corners_homo, view_matrix)[..., :3]
return bboxes_3d_data
def get_bounding_box_2d_tight(viewport, instance_mappings=None):
""" Get Bounding Box 2D Tight sensor output.
Tight bounding boxes only bound the visible or unoccluded portions of an object. If an object is
completely occluded, it is omitted from the returned array. Bounds units are in pixels.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
instance_mappings (numpy.ndarray, optional): A structured array returned by `helpers.get_instance_mappings`.
If not provided (default), a new instance mappings will be computed.
Return:
(np.ndarray): A structured numpy array with the fields: `[('name', 'O'), ('semanticLabel', 'O'),
('instanceId', '<u4'), ('semanticId', '<u4'), ("metadata", "O"), ('x_min', '<i4'), ('y_min', '<i4'),
('x_max', '<i4'), ('y_max', '<i4')]`
"""
BoundingBox2DValuesType = np.dtype(
[
("instanceId", "<u4"),
("semanticId", "<u4"),
("x_min", "<i4"),
("y_min", "<i4"),
("x_max", "<i4"),
("y_max", "<i4"),
]
)
bboxes_2d_data = get_sensor_array(
viewport, _syntheticdata.SensorType.BoundingBox2DTight, BoundingBox2DValuesType, 1, is2DArray=False
)
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
bboxes_2d_data = helpers.reduce_bboxes_2d(bboxes_2d_data, instance_mappings)
return bboxes_2d_data
def get_bounding_box_2d_loose(viewport, instance_mappings=None):
""" Get Bounding Box 2D Loose sensor output.
Loose bounding boxes bound the full extents of an object, even if totally occluded. Bounds units are
in pixels.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
instance_mappings (numpy.ndarray, optional): A structured array returned by `helpers.get_instance_mappings`.
If not provided (default), a new instance mappings will be computed.
Return:
(np.ndarray): A structured numpy array with the fields: `[('name', 'O'), ('semanticLabel', 'O'),
('instanceId', '<u4'), ('semanticId', '<u4'), ("metadata", "O"), ('x_min', '<i4'), ('y_min', '<i4'),
('x_max', '<i4'), ('y_max', '<i4')]`
"""
BoundingBox2DValuesType = np.dtype(
[
("instanceId", "<u4"),
("semanticId", "<u4"),
("x_min", "<i4"),
("y_min", "<i4"),
("x_max", "<i4"),
("y_max", "<i4"),
]
)
bboxes_2d_data = get_sensor_array(
viewport, _syntheticdata.SensorType.BoundingBox2DLoose, BoundingBox2DValuesType, 1, is2DArray=False
)
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
bboxes_2d_data = helpers.reduce_bboxes_2d(bboxes_2d_data, instance_mappings)
return bboxes_2d_data
def get_semantic_segmentation(viewport):
""" Get semantic segmentation sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
output (np.ndarray): A uint32 array of shape `(height, width)`.
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.SemanticSegmentation, np.uint32, 1, True)
def get_instance_segmentation(viewport, parsed=False, return_mapping=False, instance_mappings=None):
""" Get instance segmentation sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
parsed (bool): If True, map each leaf prim to a parent with a semantic schema applied. Otherwise,
each leaf prim is returned as a unique instance.
return_mapping (bool): Whether to also return an array mapping instance IDs to their corresponding prims.
instance_mappings (numpy.ndarray, optional): A structured array returned by `helpers.get_instance_mappings`.
If not provided (default), a new instance mappings will be computed.
Return:
output (np.ndarray): A uint32 array of shape `(height, width)`.
mapping (list): (optional) If `return_mapping` is True, there will be an additional array containing the
mapping of instance IDs to their corresponding prims. Each row corresponds to a prim with a SemanticSchema
of Type="class". The mapping is provided in the following format:
(ID (int), path (str), semanticID (int), semanticLabel (str), descendentIDs (list of int))
"""
instance_data = get_sensor_array(viewport, _syntheticdata.SensorType.InstanceSegmentation, np.uint32, 1, True)
if parsed:
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
if len(instance_mappings) == 0:
return instance_data
instances_list = [(im[0], im[4]) for im in instance_mappings][::-1]
if len(instances_list) == 0:
carb.log_warn("[omni.syntheticdata.visualize] No instances found.")
return instance_data
max_instance_id_list = max([max(il[1]) for il in instances_list])
max_instance_id = instance_data.max()
lut = np.zeros(max(max_instance_id, max_instance_id_list) + 1, dtype=np.uint32)
# todo this avoids that overlapping instances are mapped to the same id, but it's not clear if this is the correct way
for uid, il in instances_list:
for j in il:
if lut[j] == 0:
lut[j] = uid
instance_data = np.take(lut, instance_data)
if return_mapping:
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
return instance_data, instance_mappings
else:
return instance_data
def get_normals(viewport):
""" Get Normals sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape `(height, width, 3)` with values in the range of
`(-1., 1.)`.
"""
normals = get_sensor_array(viewport, _syntheticdata.SensorType.Normal, np.float32, 4, True)[..., :3]
# Return (0, 0, 0) for background pixels
# HACK: background is returned as (-0., -0., 1.), so use negative sign of 0 as background indicator
bkg_mask = np.all(normals == np.array([0.0, 0.0, -1.0]), axis=-1) & np.all(
np.copysign(np.ones_like(normals), normals) == -np.ones(3), axis=-1
)
normals[bkg_mask] = 0.0
return normals
def get_motion_vector(viewport):
""" Get Motion Vector sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
TOCHECK : this does not describe what the legacy interface was returning
(numpy.ndarray): A float32 array of shape `(height, width, 3)` with values in the range of
`(-1., 1.)`.
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.MotionVector, np.float32, 4, True)
def get_cross_correspondence(viewport):
""" Get Cross Correspondence sensor output.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Return:
(numpy.ndarray): A float32 array of shape `(height, width, 4)` with values in the range of
`(-1., 1.)`.
"""
return get_sensor_array(viewport, _syntheticdata.SensorType.CrossCorrespondence, np.float32, 4, True)
def get_occlusion(viewport, parsed=False, instance_mappings=None):
"""Get Occlusion values.
Returns occlusion of instances as a ratio from 0. to 1. Note that this sensor is only applied to leaf prims.
For example, if an asset is composed of multiple sub-meshes, an occlusion value will be calculated for each
sub-mesh.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
parsed (bool): If True, map occlusion values to prims with a semantic class. If the mapped prim has more than
one child with an occlusion value, a naive average will be performed. Note that this value will likely not
be accurate.
instance_mappings (numpy.ndarray, optional): A structured array returned by `helpers.get_instance_mappings`.
If not provided (default), a new instance mappings will be computed.
Returns:
(numpy.ndarray): A structured numpy array with the fields: [('instanceId', '<u4'), ('semanticId', '<u4'),
('occlusionRatio', '<f4')], where occlusion ranges from 0 (not occluded) to 1 (fully occluded).
If `parsed` is True, the additional fields [('name', 'O'), ('semanticLabel', 'O'), ("metadata", "O")]
are returned.
"""
OcclusionType = np.dtype([("instanceId", "<u4"), ("semanticId", "<u4"), ("occlusionRatio", "<f4")])
data = get_sensor_array(viewport, _syntheticdata.SensorType.Occlusion, OcclusionType, 1, is2DArray=False)
if parsed:
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
return helpers.reduce_occlusion(data, instance_mappings)
return data
def get_semantic_data(instance_mappings=None):
""" Get Semantic Data.
Args:
instance_mappings (numpy.ndarray, optional): A structured array returned by `helpers.get_instance_mappings`.
If not provided (default), a new instance mappings will be computed.
Returns:
(numpy.ndarray): A structured numpy array with the fields: [('uniqueId', '<i4'),
('name', 'O'), ('semanticLabel', 'O'), ('metadata', 'O')]
"""
if instance_mappings is None:
instance_mappings = helpers.get_instance_mappings()
output = []
for row in instance_mappings:
output.append((row[0], row[1], row[3], row[5]))
output = np.array(output, dtype=[("uniqueId", np.int32), ("name", "O"), ("semanticLabel", "O"), ("metadata", "O")])
return output
def get_occlusion_quadrant(viewport, return_bounding_boxes=False):
""" Get Occlusion Quadrant.
Uses loose and tight bounding boxes to return the occluded quadrant of all prims with semantic class.
Note that the label "fully-visible" specifies that the full height and width of the prim's bounds
can be determined, and the prim may still be partially occluded.
Args:
viewport (opaque Viewport instance): Viewport from which to retrieve/create sensor.
Returns:
(numpy.ndarray): A structured numpy array with the fields: [('name', 'O'), ('semanticLabel', 'O'),
('instanceId', '<u4'), ('semanticId', '<u4'), ('occlusion_quadrant', 'O')], where
occlusion_quadrant is a string from ['bottom', 'top', 'right', 'left',
'bottom-right', 'bottom-left', 'top-right', 'top-left', 'fully-visible', 'fully-occluded'].
If `return_bounding_boxes` is True, the fields `x_min`, `y_min`, `x_max`, `y_max` for
with suffixes `_bbox2d_tight` and `_bbox2d_loose` will be returned as well.
"""
tight_data = get_bounding_box_2d_tight(viewport)
loose_data = get_bounding_box_2d_loose(viewport)
merged_data = helpers.merge_sensors(bounding_box_2d_tight=tight_data, bounding_box_2d_loose=loose_data)
is_fully_occluded = merged_data["x_min_bbox2d_tight"] == -1
is_occluded_left = (merged_data["x_min_bbox2d_tight"] > merged_data["x_min_bbox2d_loose"]) & ~is_fully_occluded
is_occluded_right = (merged_data["x_max_bbox2d_tight"] < merged_data["x_max_bbox2d_loose"]) & ~is_fully_occluded
is_occluded_top = (merged_data["y_min_bbox2d_tight"] > merged_data["y_min_bbox2d_loose"]) & ~is_fully_occluded
is_occluded_bottom = (merged_data["y_max_bbox2d_tight"] < merged_data["y_max_bbox2d_loose"]) & ~is_fully_occluded
is_occluded_bottom_left = is_occluded_bottom & is_occluded_left
is_occluded_bottom_right = is_occluded_bottom & is_occluded_right
is_occluded_top_right = is_occluded_top & is_occluded_right
is_occluded_top_left = is_occluded_top & is_occluded_left
label = np.array(["fully-visible"] * len(merged_data), dtype=[("occlusion_quadrant", "O")])
label[is_occluded_top] = "top"
label[is_occluded_bottom] = "bottom"
label[is_occluded_right] = "right"
label[is_occluded_left] = "left"
label[is_occluded_bottom_left] = "bottom-left"
label[is_occluded_bottom_right] = "bottom-right"
label[is_occluded_top_left] = "top-left"
label[is_occluded_top_right] = "top-right"
label[is_fully_occluded] = "fully-occluded"
if return_bounding_boxes:
output = helpers._join_struct_arrays([merged_data, label])
else:
output = helpers._join_struct_arrays(
[merged_data[["uniqueId", "name", "semanticLabel", "metadata", "instanceIds"]], label]
)
return output
| 24,981 | Python | 39.621138 | 120 | 0.686922 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/visualize.py | import random
import colorsys
import numpy as np
import carb
from PIL import Image, ImageDraw
from . import helpers
from . import sensors
# Colorize Helpers
def colorize_distance(image_data):
height, width = image_data.shape[:2]
colorized_image = np.zeros((height, width, 4))
image_data[image_data == 0.0] = 1e-5
image_data = np.clip(image_data, 0, 255)
image_data -= np.min(image_data)
image_data /= np.max(image_data) + 1e-8
colorized_image[:, :, 0] = image_data
colorized_image[:, :, 1] = image_data
colorized_image[:, :, 2] = image_data
colorized_image[:, :, 3] = 1
colorized_image = (colorized_image * 255).astype(int)
return colorized_image
def colorize_segmentation(segmentation_image):
segmentation_ids = np.unique(segmentation_image)
num_colours = len(segmentation_ids)
# This is to avoid generating lots of colours for semantic classes not in frame
lut = np.array([segmentation_ids, list(range(num_colours))])
new_segmentation_image = lut[1, np.searchsorted(lut[0, :], segmentation_image)]
colours = np.array([[0.0] * 4] + random_colours(num_colours))
segmentation_image_rgba = (colours[new_segmentation_image] * 255).astype(int)
return segmentation_image_rgba
def colorize_semantic_from_instance(instance_image, instance_mappings):
if len(instance_mappings) == 0:
blank = np.zeros_like(instance_image)
return colorize_segmentation(blank)
semantic_instances = {}
for im in instance_mappings[::-1]:
semantic_instances.setdefault(im["semanticId"], []).extend(im["instanceIds"])
max_semantic_instance_id = np.max([max(il) for _, il in semantic_instances.items()])
max_instance_id = instance_image.max()
lut = np.zeros(max(max_semantic_instance_id, max_instance_id) + 1, dtype=np.uint32)
for i, (_, il) in enumerate(semantic_instances.items()):
lut[np.array(il)] = i + 1 # +1 to differentiate from background
re_instanced = np.take(lut, instance_image)
colours = np.array([[0.0] * 4] + random_colours(len(semantic_instances)))
instance_rgba = (colours[re_instanced] * 255).astype(np.uint8)
return instance_rgba
def colorize_bboxes(bboxes_2d_data, bboxes_2d_rgb):
semantic_id_list = []
bbox_2d_list = []
for bbox_2d in bboxes_2d_data:
if bbox_2d["semanticId"] > 0:
semantic_id_list.append(bbox_2d["semanticId"])
bbox_2d_list.append(bbox_2d)
semantic_id_list_np = np.unique(np.array(semantic_id_list))
color_list = random_colours(len(semantic_id_list_np.tolist()))
img = Image.fromarray(bboxes_2d_rgb)
draw = ImageDraw.Draw(img)
for bbox_2d in bbox_2d_list:
index = np.where(semantic_id_list_np == bbox_2d["semanticId"])[0][0]
bbox_color = color_list[index]
draw.rectangle(
xy=[(bbox_2d["x_min"], bbox_2d["y_min"]), (bbox_2d["x_max"], bbox_2d["y_max"])],
outline=(
int(255 * bbox_color[0]),
int(255 * bbox_color[1]),
int(255 * bbox_color[2]),
int(255 * bbox_color[3]),
),
width=4,
)
return np.asarray(img)
def colorize_bboxes_3d(bboxes_3d_corners, rgb):
"""bboxes_3d_corners: in the local camera frame"""
height, width = rgb.shape[:2]
# FILTER BOXES
mask_uv = ~np.any(np.all(bboxes_3d_corners < 0, axis=1), axis=1) & ~np.any(
np.all(bboxes_3d_corners > 1, axis=1), axis=1
)
mask_z = np.all(np.all(bboxes_3d_corners[..., 2:] >= 0, axis=1), axis=1) & np.all(
np.all(bboxes_3d_corners[..., 2:] <= 1, axis=1), axis=1
)
bboxes_3d_corners = bboxes_3d_corners[mask_uv & mask_z]
bboxes_3d_corners = bboxes_3d_corners[..., :2].reshape(-1, 8, 2) * np.array([[width, height]])
face_idx_list = [[0, 1, 3, 2], [4, 5, 7, 6], [2, 3, 7, 6], [0, 1, 5, 4], [0, 2, 6, 4], [1, 3, 7, 5]]
colours = random_colours(len(face_idx_list))
master_overlay = np.zeros_like(rgb)
master_overlay_img = Image.fromarray(master_overlay)
for face_idxs, colour in zip(face_idx_list, colours):
overlay = Image.new("RGBA", (width, height))
draw = ImageDraw.Draw(overlay)
colour = [int(c * 255) for c in colour]
for p in bboxes_3d_corners:
draw.polygon([tuple(xy) for xy in p[face_idxs]], fill=tuple([*colour[:3], 120]))
draw.line([tuple(xy) for xy in p[face_idxs]], width=3, fill=tuple(colour))
master_overlay_img = Image.alpha_composite(master_overlay_img, overlay)
rgb_img = Image.fromarray(rgb)
rgb_img = Image.alpha_composite(rgb_img, master_overlay_img)
return np.asarray(rgb_img)
def random_colours(N):
"""
Generate random colors.
Generate visually distinct colours by linearly spacing the hue
channel in HSV space and then convert to RGB space.
"""
colour_rand = random.Random(2018) # Produces consistent random colours
start = colour_rand.random()
hues = [(start + i / N) % 1.0 for i in range(N)]
colours = [list(colorsys.hsv_to_rgb(h, 0.9, 1.0)) + [1.0] for i, h in enumerate(hues)]
colour_rand.shuffle(colours)
return colours
def get_bbox2d_tight(viewport):
rgb_data = sensors.get_rgb(viewport)
bboxes_2d_data = sensors.get_bounding_box_2d_tight(viewport)
bboxes_2d_rgb = colorize_bboxes(bboxes_2d_data, rgb_data)
return bboxes_2d_rgb
def get_bbox2d_loose(viewport):
rgb_data = sensors.get_rgb(viewport)
bboxes_2d_data = sensors.get_bounding_box_2d_loose(viewport)
bboxes_2d_rgb = colorize_bboxes(bboxes_2d_data, rgb_data)
return bboxes_2d_rgb
def get_normals(viewport):
normals = sensors.get_normals(viewport)
background_mask = np.sum(normals, axis=-1) == 0.0
# normalize from [-1, 1] to [0, 255]
normals = (normals + 1.0) / 2 * 255
# Set background alpha to 0.
normals = np.pad(normals, ((0, 0), (0, 0), (0, 1)), constant_values=255)
normals[background_mask, 3] = 0.0
return normals.astype(np.uint8)
def get_motion_vector(viewport):
motion_vector = sensors.get_motion_vector(viewport)
_min, _max = motion_vector.min(), motion_vector.max()
motion_vector = (motion_vector - _min) / (_max - _min) * 255.0
return motion_vector.astype(np.uint8)
def get_cross_correspondence(viewport):
cross_correspondence = sensors.get_cross_correspondence(viewport)
# normalize from [-1, 1] to [0, 255]
# invalid values of -1 convert to 0
cross_correspondence = ((cross_correspondence + 1.0) / 2) * 255
return cross_correspondence.astype(np.uint8)
def get_instance_segmentation(viewport, mode=None):
if not mode:
carb.log_info('[omni.syntheticdata.visualize] No semantic mode provided, defaulting to "parsed"')
mode = "parsed"
if mode == "raw":
instance_data = sensors.get_instance_segmentation(viewport, parsed=False)
elif mode == "parsed":
instance_data = sensors.get_instance_segmentation(viewport, parsed=True)
else:
raise NotImplementedError
instance_image = colorize_segmentation(instance_data)
return instance_image
def get_semantic_segmentation(viewport, mode=""):
if not mode:
carb.log_info('[omni.syntheticdata.visualize] No semantic mode provided, defaulting to "parsed"')
mode = "instance_map"
# s = time.time()
if mode == "raw":
semantic_data = sensors.get_semantic_segmentation(viewport)
semantic_image = colorize_segmentation(semantic_data)
elif mode == "parsed":
instance_data = sensors.get_instance_segmentation(viewport)
instance_mappings = helpers.get_instance_mappings()
semantic_image = colorize_semantic_from_instance(instance_data, instance_mappings)
else:
raise NotImplementedError
return semantic_image
def get_bbox3d(viewport, mode="parsed"):
rgb_data = sensors.get_rgb(viewport)
bbox_3d_data = sensors.get_bounding_box_3d(viewport, parsed=(mode == "parsed"), return_corners=True)
if bbox_3d_data.size == 0:
carb.log_info("[omni.syntheticdata.visualize] No 3D bounding boxes found.")
return rgb_data
bbox_3d_corners = bbox_3d_data["corners"]
projected_corners = helpers.world_to_image(bbox_3d_corners.reshape(-1, 3), viewport).reshape(-1, 8, 3)
bboxes_3d_rgb = colorize_bboxes_3d(projected_corners, rgb_data)
return bboxes_3d_rgb
# *** DEPRECATED ***
def get_depth(viewport, mode="linear"):
if mode == "linear":
depth_data = sensors.get_depth_linear(viewport)
depth_data[depth_data == depth_data.max()] = 0.0
elif mode == "inverse_depth":
depth_data = sensors.get_depth(viewport)
else:
raise ValueError(f"Mode {mode} is invalid. Choose between " "['linear', 'inverse_depth'].")
return colorize_distance(depth_data.squeeze())
def get_distance(viewport, mode="image_plane"):
if mode == "image_plane":
distance_data = sensors.get_distance_to_image_plane(viewport)
distance_data[distance_data == distance_data.max()] = 0.0
elif mode == "camera":
distance_data = sensors.get_distance_to_camera(viewport)
distance_data[distance_data == distance_data.max()] = 0.0
else:
raise ValueError(f"Mode {mode} is invalid. Choose between " "['image_plane', 'camera'].")
return colorize_distance(distance_data.squeeze())
| 9,390 | Python | 37.966805 | 106 | 0.646858 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/extension.py | from pxr import Tf, Trace, Usd
import carb.settings
import omni.kit
import omni.ext
# legacy extension export
from . import helpers
from . import visualize
from . import sensors
from .SyntheticData import *
EXTENSION_NAME = "Synthetic Data"
_extension_instance = None
class Extension(omni.ext.IExt):
def __init__(self):
self.__viewport_legacy_event_sub = None
self.__viewport_legacy_close = None
self.__extension_loaded = None
self.__menu_container = None
def __menubar_core_loaded(self):
from .menu import SynthDataMenuContainer
self.__menu_container = SynthDataMenuContainer()
def __menubar_core_unloaded(self):
if self.__menu_container:
self.__menu_container.destroy()
self.__menu_container = None
def __viewport_legcy_loaded(self):
from .viewport_legacy import ViewportLegacy
self.__viewport_legacy_event_sub = ViewportLegacy.create_update_subscription()
self.__viewport_legacy_close = ViewportLegacy.close_viewports
def __viewport_legcy_unloaded(self):
if self.__viewport_legacy_event_sub:
self.__viewport_legacy_event_sub = None
if self.__viewport_legacy_close:
self.__viewport_legacy_close()
self.__viewport_legacy_close = None
def on_startup(self, ext_id):
global _extension_instance
_extension_instance = self
carb.log_info("[omni.syntheticdata] SyntheticData startup")
manager = omni.kit.app.get_app().get_extension_manager()
self.__extension_loaded = (
manager.subscribe_to_extension_enable(
lambda _: self.__menubar_core_loaded(),
lambda _: self.__menubar_core_unloaded(),
ext_name="omni.kit.viewport.menubar.core",
hook_name=f"{ext_id} omni.kit.viewport.menubar.core listener",
),
manager.subscribe_to_extension_enable(
lambda _: self.__viewport_legcy_loaded(),
lambda _: self.__viewport_legcy_unloaded(),
ext_name="omni.kit.window.viewport",
hook_name=f"{ext_id} omni.kit.window.viewport listener",
)
)
self._stage_event_sub = (
omni.usd.get_context()
.get_stage_event_stream()
.create_subscription_to_pop(self._on_stage_event, name="omni.syntheticdata stage update")
)
self._usd_event_listener = None
# self._usd_event_listener = Tf.Notice.Register(Usd.Notice.ObjectsChanged, self._on_usd_changed, None)
# force settings
settings = carb.settings.get_settings()
settings.set("/rtx/hydra/enableSemanticSchema", True) # TODO : deprecate
if settings.get_as_bool("/app/asyncRendering") or settings.get_as_bool("/app/asyncRenderingLowLatency"):
carb.log_warn(f"SyntheticData extension is not supporting asyncRendering")
stageHistoryFrameCount = settings.get_as_int("/app/settings/flatCacheStageFrameHistoryCount")
if not stageHistoryFrameCount or (int(stageHistoryFrameCount) < 3):
carb.log_warn(f"SyntheticData extension needs at least a stageFrameHistoryCount of 3")
if settings.get_as_bool("/rtx/gatherColorToDisplayDevice") and settings.get_as_bool("/renderer/multiGpu/enabled"):
carb.log_error("SyntheticData extension does not support /rtx/gatherColorToDisplayDevice=true with multiple GPUs.")
SyntheticData.Initialize()
# @Trace.TraceFunction
# def _on_usd_changed(self, notice, stage):
# if notice.GetResyncedPaths():
# self._viewports = {}
def _on_stage_event(self, event):
if event.type == int(omni.usd.StageEventType.CLOSING):
if self.__viewport_legacy_close:
self.__viewport_legacy_close()
# FIXME : this cause rendering issues (added for unittests)
SyntheticData.Get().reset(False)
# this is fishy but if we reset the graphs in the closing event the rendering is not happy
elif event.type == int(omni.usd.StageEventType.OPENED):
SyntheticData.Get().reset(False)
def on_shutdown(self):
global _extension_instance
_extension_instance = None
self.__extension_loaded = None
self._stage_event_sub = None
self.__viewport_legcy_unloaded()
self.__menubar_core_unloaded()
if self._usd_event_listener:
self._usd_event_listener.Revoke()
self._usd_event_listener = None
SyntheticData.Reset()
def get_name(self):
return EXTENSION_NAME
@staticmethod
def get_instance():
return _extension_instance
| 4,736 | Python | 37.201613 | 127 | 0.635769 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/SyntheticData.py | from sqlite3 import connect
from pxr import Sdf, Usd, UsdRender
import carb
import omni.graph.core as og
import omni.usd
import omni.kit
from dataclasses import dataclass, field
""" SyntheticData class is the prototype interface implementation (will be eventually integrated in SynthetiData C++ interface )
- contains the definition of all omnigraphs
- expose methods for the user to
- add / remove custom nodes to graphs
"""
_sdg_iface = None
class SyntheticDataException(Exception):
def __init__(self, message="error"):
self.message = message
super().__init__(self.message)
class SyntheticDataStage:
# stage is set automatically from the node connections' stages
AUTO = -1
# global simulation : node scheduled in the simulation graph
SIMULATION = 0
# prerender : node scheduled in the prerender graph
PRE_RENDER = 1
# postrender : node scheduled in the postrender graph for a specific renderproduct
POST_RENDER = 2
# on demand : node scheduled in the postprocess graph
ON_DEMAND = 3
class SyntheticData:
_graphPathRoot = "/Render"
_graphName = "SDGPipeline"
_simulationGraphPath = "Simulation/" + _graphName
_preRenderGraphPath = "PreRender/" + _graphName
_postRenderGraphPath = "PostRender/" + _graphName
_postProcessGraphPath = "PostProcess/" + _graphName
_rendererTemplateName = "GpuInteropEntry"
_renderVarBuffSuffix = "buff"
_renderVarHostSuffix = "host"
_renderVarToHostTemplateName = "PostRenderVarToHost"
_renderProductAttributeName = "inputs:renderProductPath"
_instanceMappingCtrl = "InstanceMappingPre"
_defaultSemanticFilterName = "DefaultSemanticFilter"
# graph registry : contains node templates used to construct a graph
# node template name / id
# list containing :
# - node type
# - list of template dependencies description :
# - connection node template name or renderVar name
# - index of the render product in the list provided during activation
# - dictionnary of inputs / outputs mapping
# - node attributes name/value dictionnary to be set during the activation
#
@dataclass
class NodeConnectionTemplate:
node_template_id: str
render_product_idxs: tuple = (0,)
attributes_mapping: dict = field(default_factory=dict)
@dataclass
class NodeTemplate:
pipeline_stage: int
node_type_id: str
connections: list = field(default_factory=list)
attributes: dict = field(default_factory=dict)
_ogn_templates_registry = {
# --- Camera
"RenderProductCameraPrimPath": NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdSimRenderProductCamera"
),
"PostRenderProductCamera": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdRenderProductCamera",
[
NodeConnectionTemplate(
_rendererTemplateName,
attributes_mapping={
"outputs:rp": "inputs:renderResults",
"outputs:swhFrameNumber": "inputs:swhFrameNumber",
"outputs:exec": "inputs:exec"
}),
NodeConnectionTemplate("RenderProductCameraPrimPath", attributes_mapping={
"outputs:exec": "inputs:exec"})
]
),
# --- GPUInterop
_rendererTemplateName: NodeTemplate(SyntheticDataStage.POST_RENDER, "omni.graph.nodes.GpuInteropRenderProductEntry"),
# --- InstanceMapping
_instanceMappingCtrl : NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdSimInstanceMapping",
attributes={"inputs:needTransform": False, "inputs:semanticFilterPredicate":"*:*"}
),
_defaultSemanticFilterName: NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdSemanticFilter",
attributes={"inputs:name": "default", "inputs:predicate": "*:*"}
),
"InstanceMappingTransforms": NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdSimInstanceMapping",
[
NodeConnectionTemplate(_instanceMappingCtrl, render_product_idxs=())
],
{"inputs:needTransform": True}
),
"InstanceMappingPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostInstanceMapping",
[
NodeConnectionTemplate("InstanceIdTokenMapSD"),
NodeConnectionTemplate(_instanceMappingCtrl, attributes_mapping={"outputs:exec": "inputs:exec"}, render_product_idxs=())
],
{},
),
# --- NoOp node used to expose the semantic transforms renderVars
"InstanceMappingPostWithTransforms": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdNoOp",
[
NodeConnectionTemplate("InstanceMappingTransforms", attributes_mapping={"outputs:exec": "inputs:exec"}, render_product_idxs=()),
NodeConnectionTemplate("InstanceMappingPost", attributes_mapping={"outputs:exec": "inputs:exec"})
],
{},
),
# --- BoundingBoxes
"BoundingBox2DTightReduction": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostSemanticBoundingBox",
[
NodeConnectionTemplate("BoundingBox2DTightSD"),
NodeConnectionTemplate("InstanceMappingPost")
],
{"inputs:renderVar": "BoundingBox2DTightSD"},
),
"BoundingBox2DLooseReduction": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostSemanticBoundingBox",
[
NodeConnectionTemplate("BoundingBox2DLooseSD"),
NodeConnectionTemplate("InstanceMappingPost")
],
{"inputs:renderVar": "BoundingBox2DLooseSD"},
),
"BoundingBox3DReduction": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostSemanticBoundingBox",
[
NodeConnectionTemplate("BoundingBox3DSD"),
NodeConnectionTemplate("InstanceMappingTransforms", attributes_mapping={"outputs:exec": "inputs:exec"}, render_product_idxs=()),
NodeConnectionTemplate("InstanceMappingPost")
],
{"inputs:renderVar": "BoundingBox3DSD"},
),
"BoundingBox3DCameraProjection": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostSemantic3dBoundingBoxCameraProjection",
[
NodeConnectionTemplate("BoundingBox3DSD"),
NodeConnectionTemplate("BoundingBox3DReduction"),
NodeConnectionTemplate("PostRenderProductCamera"),
NodeConnectionTemplate("InstanceMappingTransforms", attributes_mapping={"outputs:exec": "inputs:exec"}, render_product_idxs=()),
NodeConnectionTemplate("InstanceMappingPost")
]
),
"BoundingBox3DFilter": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostSemantic3dBoundingBoxFilter",
[
NodeConnectionTemplate("BoundingBox3DSD"),
NodeConnectionTemplate("BoundingBox3DCameraProjection"),
NodeConnectionTemplate("PostRenderProductCamera"),
NodeConnectionTemplate("BoundingBox3DReduction"),
NodeConnectionTemplate("InstanceMappingPost")
]
),
# --- PostRenderVarDisplay
"LdrColorDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("LdrColorSD")],
{"inputs:renderVar": "LdrColorSD"},
),
"DistanceToImagePlaneDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("DistanceToImagePlaneSD")],
{
"inputs:renderVar": "DistanceToImagePlaneSD",
"inputs:parameters": [0.0, 100.0, 0.0, 0.0]
},
),
"DistanceToCameraDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("DistanceToCameraSD")],
{
"inputs:renderVar": "DistanceToCameraSD",
"inputs:parameters": [0.0, 100.0, 0.0, 0.0]
},
),
"Camera3dPositionDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("Camera3dPositionSD")],
{"inputs:renderVar": "Camera3dPositionSD"},
),
"NormalDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("NormalSD")],
{"inputs:renderVar": "NormalSD"},
),
"CrossCorrespondenceDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("CrossCorrespondenceSD")],
{"inputs:renderVar": "CrossCorrespondenceSD"},
),
"TargetMotionDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("TargetMotionSD")],
{
"inputs:renderVar": "TargetMotionSD",
"inputs:parameters": [1.0, 5.0, 0.0, 0.0]
},
),
"InstanceIdSegmentationDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("InstanceSegmentationSD")],
{"inputs:renderVar": "InstanceSegmentationSD",
"inputs:renderVarDisplay": "RawInstanceSegmentationSDDisplay", "inputs:mode": "segmentationMapMode"},
),
"InstanceSegmentationDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[
NodeConnectionTemplate("InstanceSegmentationSD"),
NodeConnectionTemplate("InstanceMappingPost")
],
{"inputs:renderVar": "InstanceSegmentationSD", "inputs:mode": "semanticPathMode"},
),
"SemanticSegmentationDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[
NodeConnectionTemplate("InstanceSegmentationSD"),
NodeConnectionTemplate("InstanceMappingPost"),
],
{"inputs:renderVar": "InstanceSegmentationSD",
"inputs:renderVarDisplay": "SemanticSegmentationSDDisplay", "inputs:mode": "semanticLabelMode"},
),
"SemanticIdSegmentationDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[NodeConnectionTemplate("SemanticSegmentationSD")],
{"inputs:renderVar": "SemanticSegmentationSD",
"inputs:renderVarDisplay": "RawSemanticSegmentationSDDisplay", "inputs:mode": "segmentationMapMode"},
),
"BoundingBox2DTightDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[
NodeConnectionTemplate("LdrColorSD"),
NodeConnectionTemplate("InstanceMappingPost"),
NodeConnectionTemplate("BoundingBox2DTightReduction"),
],
{"inputs:renderVar": "LdrColorSD", "inputs:renderVarDisplay": "BoundingBox2DTightSDDisplay",
"inputs:mode": "semanticBoundingBox2dMode"},
),
"BoundingBox2DLooseDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[
NodeConnectionTemplate("LdrColorSD"),
NodeConnectionTemplate("InstanceMappingPost"),
NodeConnectionTemplate("BoundingBox2DLooseReduction"),
],
{"inputs:renderVar": "LdrColorSD", "inputs:renderVarDisplay": "BoundingBox2DLooseSDDisplay",
"inputs:mode": "semanticBoundingBox2dMode"},
),
"BoundingBox3DDisplayPost": NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarDisplayTexture",
[
NodeConnectionTemplate("LdrColorSD"),
NodeConnectionTemplate("Camera3dPositionSD"),
NodeConnectionTemplate("PostRenderProductCamera"),
NodeConnectionTemplate("InstanceMappingPost"),
NodeConnectionTemplate("BoundingBox3DFilter"),
NodeConnectionTemplate("BoundingBox3DCameraProjection"),
NodeConnectionTemplate("BoundingBox3DReduction"),
],
{
"inputs:renderVar": "LdrColorSD",
"inputs:renderVarDisplay": "BoundingBox3DSDDisplay",
"inputs:mode": "semanticBoundingBox3dMode",
"inputs:parameters": [0.0, 5.0, 0.027, 0.27]
},
),
# --- PostProcess
"PostProcessDispatcher": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdOnNewFrame"
),
"PostProcessDispatch": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdOnNewRenderProductFrame",
[NodeConnectionTemplate("PostProcessDispatcher", render_product_idxs=())]
),
"PostProcessRenderProductCamera": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdRenderProductCamera",
[
NodeConnectionTemplate("PostProcessDispatch"),
NodeConnectionTemplate("RenderProductCameraPrimPath", attributes_mapping={
"outputs:exec": "inputs:exec"}),
NodeConnectionTemplate(_rendererTemplateName, attributes_mapping={
"outputs:exec": "inputs:exec"}) # provide the renderResults
]
),
"InstanceMapping": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdInstanceMapping",
[
NodeConnectionTemplate("PostProcessDispatch"),
NodeConnectionTemplate("InstanceMappingPost", attributes_mapping={"outputs:exec": "inputs:exec"})
]
),
"InstanceMappingWithTransforms": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdInstanceMapping",
[
NodeConnectionTemplate("PostProcessDispatch"),
NodeConnectionTemplate("InstanceMappingTransforms", attributes_mapping={"outputs:exec": "inputs:exec"}, render_product_idxs=()),
NodeConnectionTemplate("InstanceMappingPost", attributes_mapping={"outputs:exec": "inputs:exec"})
]
),
"InstanceMappingPtr": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdInstanceMappingPtr",
[
NodeConnectionTemplate("PostProcessDispatch"),
NodeConnectionTemplate("InstanceMappingPost", attributes_mapping={"outputs:exec": "inputs:exec"})
]
),
"InstanceMappingPtrWithTransforms": NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdInstanceMappingPtr",
[
NodeConnectionTemplate("PostProcessDispatch"),
NodeConnectionTemplate("InstanceMappingTransforms", attributes_mapping={"outputs:exec": "inputs:exec"}, render_product_idxs=()),
NodeConnectionTemplate("InstanceMappingPost", attributes_mapping={"outputs:exec": "inputs:exec"})
]
)
}
# set of rendervars associated to the node exposing them :
# - renderVar generated by the renderer are exposed by the GpuInteropEntry
# - others renderVars are generated by some postRender nodes
# FIXME : the list of renderer rendervars should be queried from the renderer
_ogn_rendervars = {
# renderer renderVars
"LdrColorSD": _rendererTemplateName,
"Camera3dPositionSD": _rendererTemplateName,
"DistanceToImagePlaneSD": _rendererTemplateName,
"DistanceToCameraSD": _rendererTemplateName,
"DepthSD": _rendererTemplateName,
"DepthLinearSD": _rendererTemplateName,
"InstanceSegmentationSD": _rendererTemplateName,
"SemanticSegmentationSD": _rendererTemplateName,
"NormalSD": _rendererTemplateName,
"TargetMotionSD": _rendererTemplateName,
"BoundingBox2DTightSD": _rendererTemplateName,
"BoundingBox2DLooseSD": _rendererTemplateName,
"BoundingBox3DSD": _rendererTemplateName,
"OcclusionSD": _rendererTemplateName,
"TruncationSD": _rendererTemplateName,
"CrossCorrespondenceSD": _rendererTemplateName,
"InstanceIdTokenMapSD": _rendererTemplateName,
"SemanticIdTokenMapSD": _rendererTemplateName,
# postRender nodes rendervars
"InstanceMappingInfoSDhost": "InstanceMappingPost",
"SemanticMapSD": "InstanceMappingPost",
"SemanticMapSDhost": "InstanceMappingPost",
"SemanticPrimTokenSD": "InstanceMappingPost",
"SemanticPrimTokenSDhost": "InstanceMappingPost",
"InstanceMapSD": "InstanceMappingPost",
"InstanceMapSDhost": "InstanceMappingPost",
"InstancePrimTokenSD": "InstanceMappingPost",
"InstancePrimTokenSDhost": "InstanceMappingPost",
"SemanticLabelTokenSD": "InstanceMappingPost",
"SemanticLabelTokenSDhost": "InstanceMappingPost",
"SemanticLocalTransformSD": "InstanceMappingPostWithTransforms",
"SemanticLocalTransformSDhost": "InstanceMappingPostWithTransforms",
"SemanticWorldTransformSD": "InstanceMappingPostWithTransforms",
"SemanticWorldTransformSDhost": "InstanceMappingPostWithTransforms",
"SemanticBoundingBox2DExtentTightSD": "BoundingBox2DTightReduction",
"SemanticBoundingBox2DInfosTightSD": "BoundingBox2DTightReduction",
"SemanticBoundingBox2DExtentLooseSD": "BoundingBox2DLooseReduction",
"SemanticBoundingBox2DInfosLooseSD": "BoundingBox2DLooseReduction",
"SemanticBoundingBox3DExtentSD": "BoundingBox3DReduction",
"SemanticBoundingBox3DInfosSD": "BoundingBox3DReduction",
"SemanticBoundingBox3DCamCornersSD": "BoundingBox3DCameraProjection",
"SemanticBoundingBox3DCamExtentSD": "BoundingBox3DCameraProjection",
"SemanticBoundingBox3DFilterInfosSD": "BoundingBox3DFilter"
}
_ogn_post_display_types = [
"omni.syntheticdata.SdPostRenderVarDisplayTexture"
]
_ogn_display_types = [
"omni.syntheticdata.SdRenderVarDisplayTexture",
"omni.syntheticdata.SdLinearArrayToTexture"
]
"""lst: List of omnigraph node types conforming the display api.
Todo : use reflexivity on the node outputs."""
@staticmethod
def register_display_rendervar_templates() -> None:
"""Automatically register SdRenderVarDisplayTexture node template for all registerd nodes whose type is in the post display type.
The function is called for every statically registered nodes during the interface initialization .
It may be called after having registered nodes whose type is omni.syntheticdata.SdPostRenderVarDisplayTexture.
"""
ogn_registry_keys = [key for key in SyntheticData._ogn_templates_registry.keys()]
for tplName in ogn_registry_keys:
tplParams = SyntheticData._ogn_templates_registry[tplName]
tplNameDisplay = tplName[:-11] + "Display"
if (tplParams.node_type_id in SyntheticData._ogn_post_display_types) and (tplNameDisplay not in SyntheticData._ogn_templates_registry):
SyntheticData.register_node_template(SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdRenderVarDisplayTexture",
[
SyntheticData.NodeConnectionTemplate("PostProcessDispatch"),
SyntheticData.NodeConnectionTemplate(tplName)
],
),
template_name=tplNameDisplay
)
@staticmethod
def register_combine_rendervar_templates() -> None:
"""Automatically register SdPostCompRenderVarTextures node template for all registerd nodes whose type is in the post display type list.
The function is called for every statically registered nodes during the interface initialization .
It may be called after having registered nodes whose type is in the post display type list.
"""
ogn_registry_keys = [key for key in SyntheticData._ogn_templates_registry.keys()]
for tplName in ogn_registry_keys:
tplParams = SyntheticData._ogn_templates_registry[tplName]
if (tplParams.node_type_id in SyntheticData._ogn_post_display_types) and (
tplName + "Combine" not in SyntheticData._ogn_templates_registry
):
SyntheticData.register_combine_rendervar_template(tplName)
@staticmethod
def register_combine_rendervar_template(template_name: str) -> None:
"""Automatically register SdPostCompRenderVarTextures node template for the given template name.
Args:
template_name: name of the node template for which registering a SdPostCompRenderVarTextures template
"""
if not template_name in SyntheticData._ogn_templates_registry:
raise SyntheticDataException(f'graph node template "{template_name}" not registered')
# cannot combine node results from the ondemand graph
if SyntheticData._ogn_templates_registry[template_name].pipeline_stage > SyntheticDataStage.POST_RENDER:
return
templateParams = SyntheticData._ogn_templates_registry[template_name]
if templateParams.node_type_id not in SyntheticData._ogn_post_display_types:
raise SyntheticDataException(f'graph node template "{template_name}" not registered as a display node')
templateNameCombine = template_name + "Combine"
if templateNameCombine not in SyntheticData._ogn_templates_registry:
SyntheticData.register_node_template(SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostCompRenderVarTextures",
[
SyntheticData.NodeConnectionTemplate(SyntheticData._rendererTemplateName),
SyntheticData.NodeConnectionTemplate(
template_name,
attributes_mapping={
"outputs:cudaPtr": "inputs:cudaPtr",
"outputs:width": "inputs:width",
"outputs:height": "inputs:height",
"outputs:format": "inputs:format"
}
)
]
),
template_name=templateNameCombine,
)
@staticmethod
def register_device_rendervar_to_host_templates(rendervars: list) -> None:
"""Automatically register SdPostRenderVarToHost node templates for the given rendervars
Args:
rendervars: list of renderVar names to register the rendervar device to host copy node template
"""
# copy the rendervars list since the registration may modify the list
rendervars_copy = rendervars.copy()
for rv in rendervars_copy:
rv_host = rv+SyntheticData._renderVarHostSuffix
if rv.endswith(SyntheticData._renderVarHostSuffix) or (rv_host in SyntheticData._ogn_rendervars):
continue
template_name = rv + "PostCopyToHost"
if template_name not in SyntheticData._ogn_templates_registry:
SyntheticData.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarToHost",
[
SyntheticData.NodeConnectionTemplate(rv),
SyntheticData.NodeConnectionTemplate(
SyntheticData._rendererTemplateName,
attributes_mapping={
"outputs:rp": "inputs:rp",
"outputs:gpu": "inputs:gpu"
}
)
],
{
"inputs:renderVar": rv,
"inputs:renderVarHostSuffix" : SyntheticData._renderVarHostSuffix
}
),
rendervars=[rv_host],
template_name=template_name,
)
@staticmethod
def register_device_rendervar_tex_to_buff_templates(rendervars: list) -> None:
"""Automatically register SdPostRenderVarTextureToBuffer node templates for the given rendervars
Args:
rendervars: list of renderVar names to register the rendervar device texture to buffer copy node template
"""
# copy the rendervars list since the registration may modify the list
rendervars_copy = rendervars.copy()
for rv in rendervars_copy:
rv_buff = rv+SyntheticData._renderVarBuffSuffix
if rv.endswith(SyntheticData._renderVarBuffSuffix) or (rv_buff in SyntheticData._ogn_rendervars):
continue
template_name = rv + "PostCopyToBuff"
if template_name not in SyntheticData._ogn_templates_registry:
SyntheticData.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdPostRenderVarTextureToBuffer",
[
SyntheticData.NodeConnectionTemplate(rv),
SyntheticData.NodeConnectionTemplate(
SyntheticData._rendererTemplateName,
attributes_mapping={
"outputs:rp": "inputs:rp",
"outputs:gpu": "inputs:gpu"
}
)
],
{
"inputs:renderVar": rv,
"inputs:renderVarBufferSuffix" : SyntheticData._renderVarBuffSuffix
}
),
rendervars=[rv_buff],
template_name=template_name,
)
@staticmethod
def register_export_rendervar_ptr_templates(rendervars: list) -> None:
"""Automatically register SdRenderVarPtr node templates for the given rendervars
Args:
rendervars: list of renderVar names to register the ptr node template
"""
for rv in rendervars:
template_name = rv + "Ptr"
if template_name not in SyntheticData._ogn_templates_registry:
SyntheticData.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdRenderVarPtr",
[
SyntheticData.NodeConnectionTemplate(rv, (0,), None),
SyntheticData.NodeConnectionTemplate("PostProcessDispatch")
],
{"inputs:renderVar": rv}
),
template_name=template_name,
)
@staticmethod
def register_export_rendervar_array_templates(rendervars: list) -> None:
"""Automatically register SdRenderVarToRawArray node templates for the given rendervars
Args:
rendervars: list of renderVar names to register the export raw array node template
"""
for rv in rendervars:
template_name = rv + "ExportRawArray"
if template_name not in SyntheticData._ogn_templates_registry:
SyntheticData.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdRenderVarToRawArray",
[
SyntheticData.NodeConnectionTemplate(rv, (0,), None),
SyntheticData.NodeConnectionTemplate("PostProcessDispatch")
],
{"inputs:renderVar": rv}
),
template_name=template_name,
)
@staticmethod
def convert_sensor_type_to_rendervar(legacy_type_name: str) -> None:
"""Convert of legacy sensor type name to its rendervar name
Args:
legacy_type_name: legacy sensor type name to convert
Returns:
the name of the renderVar correspoding to the legacy name
"""
if legacy_type_name == "Rgb":
return "LdrColorSD"
elif legacy_type_name == "MotionVector":
return "TargetMotionSD"
else:
return legacy_type_name + "SD"
@staticmethod
def disable_async_rendering():
"""Disable asynchronous rendering
Since asyncRendering is not supported by the fabric, graphs are currently not compatible with this mode.
"""
settings = carb.settings.get_settings()
if settings.get("/app/asyncRendering") or settings.get("/app/asyncRenderingLowLatency"):
carb.log_warn(f"SyntheticData is not supporting asyncRendering : switching it off.")
settings.set("/app/asyncRendering", False)
settings.set("/app/asyncRenderingLowLatency", False)
@staticmethod
def _has_rendervar(renderProductPath: str, renderVar: str, usdStage: Usd.Stage = None) -> bool:
if not usdStage:
usdStage = omni.usd.get_context().get_stage()
if not usdStage:
raise SyntheticDataException("No stage provided or in use by default UsdContext")
renderProductPrim = usdStage.GetPrimAtPath(renderProductPath)
if not renderProductPrim:
raise SyntheticDataException(f"invalid renderProduct {renderProductPath}")
renderVarPrimPath = f"/Render/Vars/{renderVar}"
renderVarPrim = usdStage.GetPrimAtPath(renderVarPrimPath)
if not renderVarPrim:
return False
renderProductRenderVarRel = renderProductPrim.GetRelationship("orderedVars")
if not renderProductRenderVarRel:
return False
return renderVarPrimPath in renderProductRenderVarRel.GetTargets()
@staticmethod
def _add_rendervar(renderProductPath: str, renderVar: str, usdStage: Usd.Stage = None) -> None:
# FIXME : we have to use the legacy Viewport interface to modify the renderproduct, otherwise changes may be overwritten
vp_1found = False
try:
import omni.kit.viewport_legacy
vp_iface = omni.kit.viewport_legacy.get_viewport_interface()
viewports = vp_iface.get_instance_list()
for viewport in viewports:
vpw = vp_iface.get_viewport_window(viewport)
if vpw.get_render_product_path() == renderProductPath:
vpw.add_aov(renderVar, False)
vp_1found = True
except ImportError:
pass
# Both Viewport-1 and Viewport-2 won't share a common renderProductPath
if vp_1found:
return
if not usdStage:
usdStage = omni.usd.get_context().get_stage()
if not usdStage:
raise SyntheticDataException("No stage provided or in use by default UsdContext")
with Usd.EditContext(usdStage, usdStage.GetSessionLayer()):
renderProductPrim = usdStage.GetPrimAtPath(renderProductPath)
if not renderProductPrim:
raise SyntheticDataException(f"invalid renderProduct {renderProductPath}")
renderVarPrimPath = f"/Render/Vars/{renderVar}"
renderVarPrim = usdStage.GetPrimAtPath(renderVarPrimPath)
if not renderVarPrim:
renderVarPrim = usdStage.DefinePrim(renderVarPrimPath)
if not renderVarPrim:
raise SyntheticDataException(f"cannot create renderVar {renderVarPrimPath}")
renderVarPrim.CreateAttribute("sourceName", Sdf.ValueTypeNames.String).Set(renderVar)
renderVarPrim.SetMetadata("hide_in_stage_window", True)
renderVarPrim.SetMetadata("no_delete", True)
renderProductRenderVarRel = renderProductPrim.GetRelationship("orderedVars")
if not renderProductRenderVarRel:
renderProductRenderVarRel = renderProductPrim.CreateRelationship("orderedVars")
if not renderProductRenderVarRel:
raise SyntheticDataException(
f"cannot set orderedVars relationship for renderProduct {renderProductPath}")
renderProductRenderVarRel.AddTarget(renderVarPrimPath)
@staticmethod
def _remove_rendervar(renderProductPath: str, renderVar: str, usdStage: Usd.Stage = None) -> None:
# we should not remove the LdrColor since it is the default renderVar
if renderVar == "LdrColor":
return
# FIXME : we have to use the legacy Viewport interface to modify the renderproduct, otherwise changes may be overwritten
vp_1found = False
try:
import omni.kit.viewport_legacy
vp_iface = omni.kit.viewport_legacy.get_viewport_interface()
viewports = vp_iface.get_instance_list()
for viewport in viewports:
vpw = vp_iface.get_viewport_window(viewport)
if vpw.get_render_product_path() == renderProductPath:
vpw.add_aov(renderVar, False)
vp_1found = True
except ImportError:
pass
# Both Viewport-1 and Viewport-2 won't share a common renderProductPath
if vp_1found:
return
if not usdStage:
usdStage = omni.usd.get_context().get_stage()
if not usdStage:
raise SyntheticDataException("No stage provided or in use by default UsdContext")
with Usd.EditContext(usdStage, usdStage.GetSessionLayer()):
renderProductPrim = usdStage.GetPrimAtPath(renderProductPath)
if not renderProductPrim:
raise SyntheticDataException(f"invalid renderProduct {renderProductPath}")
renderVarPrimPath = f"/Render/Vars/{renderVar}"
renderProductRenderVarRel = renderProductPrim.GetRelationship("orderedVars")
if not renderProductRenderVarRel:
return
renderProductRenderVarRel.RemoveTarget(renderVarPrimPath)
@staticmethod
def get_registered_visualization_template_names() -> list:
"""Get the registered node template names which types are in the display type list
Returns:
list of registered template names which types are in the display type list
"""
registeredTemplateName = []
for name, val in SyntheticData._ogn_templates_registry.items():
if val.node_type_id in SyntheticData._ogn_display_types:
registeredTemplateName.append(name)
return registeredTemplateName
@staticmethod
def get_registered_visualization_template_names_for_display() -> list:
"""Get the registered node template names which types are in the display type list and their display name
Returns:
list of tuples of registered template names which types are in the display type list and their display name
"""
for sensor in SyntheticData.get_registered_visualization_template_names():
# by convention visualization sensors end with "Display"
yield (sensor[0:-7] if sensor.endswith("Display") else sensor, sensor)
@staticmethod
def _get_graph_path(stage: int, renderProductPath: str = None) -> str:
# simulation stages live in the same graph
if stage == SyntheticDataStage.SIMULATION:
return f"{SyntheticData._graphPathRoot}/{SyntheticData._simulationGraphPath}"
elif stage == SyntheticDataStage.PRE_RENDER:
# check if the renderProductPath has already an associated graph
usdStage = omni.usd.get_context().get_stage()
prim = usdStage.GetPrimAtPath(renderProductPath)
ogpreprocesspath_attribute = prim.GetAttribute("ogPreProcessPath")
if ogpreprocesspath_attribute:
return f"{ogpreprocesspath_attribute.Get()}/{SyntheticData._graphName}"
else:
return f"{renderProductPath}/{SyntheticData._preRenderGraphPath}"
# postprocess stages live in the same graph
elif stage == SyntheticDataStage.ON_DEMAND:
return f"{SyntheticData._graphPathRoot}/{SyntheticData._postProcessGraphPath}"
elif stage == SyntheticDataStage.POST_RENDER:
# check if the renderProductPath has already an associated graph
usdStage = omni.usd.get_context().get_stage()
prim = usdStage.GetPrimAtPath(renderProductPath)
ogpostprocesspath_attribute = prim.GetAttribute("ogPostProcessPath")
if ogpostprocesspath_attribute:
return f"{ogpostprocesspath_attribute.Get()}/{SyntheticData._graphName}"
else:
return f"{renderProductPath}/{SyntheticData._postRenderGraphPath}"
@staticmethod
def _get_node_path(templateName: str, renderProductPath: str = None) -> str:
if templateName not in SyntheticData._ogn_templates_registry:
raise SyntheticDataException(f'graph node template "{templateName}" not registered')
nodeStage = SyntheticData._ogn_templates_registry[templateName].pipeline_stage
graphPath = SyntheticData._get_graph_path(nodeStage, renderProductPath)
# prefix the node name by the renderproduct name for nodes living in the same graph
# (simulation and postprocess graphs)
nodeName = templateName
if renderProductPath:
renderProductName = renderProductPath.split("/")[-1]
nodeName = f"{renderProductName}_{nodeName}"
return f"{graphPath}/{nodeName}"
@staticmethod
def _unregister_node_template_rec(templateList: list) -> None:
if not templateList:
return
templateDependenciesList = []
for templateName in templateList:
if templateName not in SyntheticData._ogn_templates_registry:
continue
dependencyNames = []
for rv, tpl in SyntheticData._ogn_rendervars.items():
if tpl == templateName:
dependencyNames.append(rv)
for rv in dependencyNames:
SyntheticData._ogn_rendervars.pop(rv)
dependencyNames.append(templateName)
SyntheticData._ogn_templates_registry.pop(templateName)
for otherTemplateName, otherTemplateVal in SyntheticData._ogn_templates_registry.items():
for otherTemplateConnection in otherTemplateVal.connections:
if otherTemplateConnection.node_template_id in dependencyNames:
templateDependenciesList.append(otherTemplateName)
SyntheticData._unregister_node_template_rec(templateDependenciesList)
@staticmethod
def _connect_nodes(srcNode, dstNode, connectionMap, enable) -> bool:
success = True
for srcAttrName, dstAttrName in connectionMap.items():
if (not srcNode.get_attribute_exists(srcAttrName)) or (not dstNode.get_attribute_exists(dstAttrName)):
carb.log_error(
f"SyntheticData failed to (dis)connect node {srcNode.get_prim_path()}:{srcAttrName} to {dstNode.get_prim_path()}:{dstAttrName}"
)
success = False
# best effort
continue
dstAttr = dstNode.get_attribute(dstAttrName)
srcAttr = srcNode.get_attribute(srcAttrName)
if enable:
srcAttr.connect(dstAttr, True)
else:
srcAttr.disconnect(dstAttr, True)
return success
@staticmethod
def _auto_connect_nodes(srcNode, dstNode, enable, srcIndex=0) -> bool:
"""Connect a source node to destination node
The connections are made by matching outputs / inputs node attributes names
In case of outputs attributes name clashing, the first node in the list is connected
Optionnally outputs attributes name could be indexed : terminated by underscore followed by the srcNode list index (no leading zero)
Indexed outputs attributes names take precedence
"""
success = False
for attr in srcNode.get_attributes():
srcAttrName = attr.get_name()
if not srcAttrName.startswith("outputs:"):
continue
dstAttrName = "inputs:%s_%d" % (srcAttrName[8:], srcIndex)
if (
not dstNode.get_attribute_exists(dstAttrName)
or dstNode.get_attribute(dstAttrName).get_upstream_connection_count()
):
dstAttrName = "inputs:%s" % srcAttrName[8:]
if (
not dstNode.get_attribute_exists(dstAttrName)
or dstNode.get_attribute(dstAttrName).get_upstream_connection_count()
):
continue
dstAttr = dstNode.get_attribute(dstAttrName)
srcAttr = srcNode.get_attribute(srcAttrName)
if enable:
srcAttr.connect(dstAttr, True)
else:
srcAttr.disconnect(dstAttr, True)
success = True
return success
@staticmethod
def Initialize():
"""Initialize interface singleton instance."""
global _sdg_iface
if _sdg_iface is None:
SyntheticData.register_device_rendervar_tex_to_buff_templates(SyntheticData._ogn_rendervars)
SyntheticData.register_device_rendervar_to_host_templates(SyntheticData._ogn_rendervars)
SyntheticData.register_display_rendervar_templates()
SyntheticData.register_combine_rendervar_templates()
SyntheticData.register_export_rendervar_ptr_templates(SyntheticData._ogn_rendervars)
SyntheticData.register_export_rendervar_array_templates(SyntheticData._ogn_rendervars)
_sdg_iface = SyntheticData()
@staticmethod
def Get():
"""Get the interface singleton instance."""
global _sdg_iface
return _sdg_iface
@staticmethod
def Reset():
"""Reset the interface singleton """
global _sdg_iface
if _sdg_iface:
_sdg_iface.reset()
_sdg_iface = None
@staticmethod
def register_node_template(node_template: NodeTemplate, rendervars: list = None, template_name: str = None) -> str:
"""Register a node template.
Add a node template in the node registry. After the template has been added it may be activated for being executed in its associated stage.
Args:
node_template : template to be added to the registry
rendervars : list of renderVar the node is producing
template_name : unique name id of the template
Returns:
the unique name id of the registered template
"""
# check type
if og.GraphRegistry().get_node_type_version(node_template.node_type_id) is None:
raise SyntheticDataException(
f"failed to register node template. Type {node_template.node_type_id} is not in the registry")
# check template_name
if template_name is None:
numTypeTemplates = 0
for template in SyntheticData._ogn_templates_registry.values():
if template.node_type_id == node_template.node_type_id:
numTypeTemplates += 1
template_name = "%s_%04d" % (node_template.node_type_id.split(".")[-1], numTypeTemplates)
elif template_name in SyntheticData._ogn_templates_registry:
raise SyntheticDataException(
f"failed to register node template. Template {template_name} is already in the registry")
elif template_name in SyntheticData._ogn_rendervars:
raise SyntheticDataException(
f"failed to register node template. Template {template_name} is already registered as a renderVar")
# check connections
autoStage = SyntheticDataStage.POST_RENDER if rendervars else SyntheticDataStage.SIMULATION
i_connections = node_template.connections if node_template.connections else []
for conn in i_connections:
conn_name = conn.node_template_id
if conn_name in SyntheticData._ogn_rendervars:
conn_name = SyntheticData._ogn_rendervars[conn_name]
if conn_name not in SyntheticData._ogn_templates_registry:
raise SyntheticDataException(
f"failed to register node template. Connection template name {conn_name} is not in the registry")
conn_stage = SyntheticData._ogn_templates_registry[conn_name].pipeline_stage
autoStage = max(autoStage, conn_stage)
conn_map = conn.attributes_mapping if conn.attributes_mapping else {}
if not type(conn_map) is dict:
raise SyntheticDataException(
f"failed to register node template. connection attributes map is not a dictionnary")
# check stage
if node_template.pipeline_stage == SyntheticDataStage.AUTO:
node_template.pipeline_stage = autoStage
if node_template.pipeline_stage < autoStage:
raise SyntheticDataException(
f"failed to register node template. Stage {node_template.pipeline_stage} is not compatible with the connections")
# check and register renderVars
if rendervars:
if node_template.pipeline_stage != SyntheticDataStage.POST_RENDER:
raise SyntheticDataException(
f"failed to register node template. Only postRender nodes may produce renderVars")
for rv in rendervars:
if (rv in SyntheticData._ogn_templates_registry) or (rv in SyntheticData._ogn_rendervars):
raise SyntheticDataException(f"failed to register node template. RenderVar {rv} already registered")
else:
SyntheticData._ogn_rendervars[rv] = template_name
SyntheticData._ogn_templates_registry[template_name] = node_template
return template_name
@staticmethod
def is_node_template_registered(template_name: str) -> bool:
"""Check if a node template has already been registered.
Args:
template_name: name of the node template to check
Returns:
True if the template_name specifie a node template within the registry, False otherwise
"""
return template_name in SyntheticData._ogn_templates_registry
@staticmethod
def unregister_node_template(template_name: str) -> None:
"""Unregister a node template.
Remove a node template from the registry and all its dependencies. After removing a template, it cannot be activated anymore, nor its dependent templates.
"""
SyntheticData._unregister_node_template_rec([template_name])
def _reset_node_graph(self, nodeGraph):
graph = nodeGraph.get_wrapped_graph()
for node in graph.get_nodes():
graph.destroy_node(node.get_prim_path(), True)
orchestration_graph = nodeGraph.get_graph()
orchestration_graph.destroy_node(nodeGraph.get_prim_path(), True)
def _clear_empty_graphs(self):
emptyGraph = []
for graphPath, nodeGraph in self._nodeGraphs.items():
if nodeGraph.get_wrapped_graph().get_nodes():
emptyGraph.append(graphPath)
for graphPath in emptyGraph:
self._reset_node_graph(nodeGraph)
self._nodeGraphs.pop(graphPath)
def _set_process_path(self, renderProductPath, graphPath, processPathAttribueName):
if not renderProductPath:
raise SyntheticDataException("invalid renderProductPath")
usdStage = omni.usd.get_context().get_stage()
prim = usdStage.GetPrimAtPath(renderProductPath)
ogprocesspath_attribute = prim.GetAttribute(processPathAttribueName)
if not ogprocesspath_attribute:
assert graphPath.endswith("/" + SyntheticData._graphName)
ogProcessPath = graphPath[: -len("/" + SyntheticData._graphName)]
prim.CreateAttribute(processPathAttribueName, Sdf.ValueTypeNames.String).Set(ogProcessPath)
def _get_or_create_graph(self, path: str, stage: int, renderProductPath: object) -> object:
if path in self._nodeGraphs:
return self._nodeGraphs[path]
settings = carb.settings.get_settings()
use_legacy_simulation_pipeline = settings.get("/persistent/omnigraph/useLegacySimulationPipeline")
pipelineStage = og.GraphPipelineStage.GRAPH_PIPELINE_STAGE_SIMULATION
executionModel = "push"
backingType = og.GraphBackingType.GRAPH_BACKING_TYPE_FLATCACHE_SHARED
if (stage == SyntheticDataStage.PRE_RENDER) and (not use_legacy_simulation_pipeline):
pipelineStage = og.GraphPipelineStage.GRAPH_PIPELINE_STAGE_PRERENDER
backingType = og.GraphBackingType.GRAPH_BACKING_TYPE_FLATCACHE_SHARED # GRAPH_BACKING_TYPE_FLATCACHE_WITHOUT_HISTORY
elif (stage == SyntheticDataStage.POST_RENDER) and (not use_legacy_simulation_pipeline):
pipelineStage = og.GraphPipelineStage.GRAPH_PIPELINE_STAGE_POSTRENDER
# GRAPH_BACKING_TYPE_FLATCACHE_WITHOUT_HISTORY
backingType = backingType = og.GraphBackingType.GRAPH_BACKING_TYPE_FLATCACHE_SHARED
elif (stage == SyntheticDataStage.ON_DEMAND) or (stage == SyntheticDataStage.ON_DEMAND):
pipelineStage = og.GraphPipelineStage.GRAPH_PIPELINE_STAGE_SIMULATION # ONDEMAND (FIXME)
executionModel = "execution"
usdStage = omni.usd.get_context().get_stage()
primExistWorkaround = not usdStage.GetPrimAtPath(path)
orchestration_graphs = og.get_global_orchestration_graphs_in_pipeline_stage(pipelineStage)
nodeGraph = orchestration_graphs[0].create_graph_as_node(
path.replace("/", "_"),
path,
executionModel,
True,
primExistWorkaround,
backingType,
pipelineStage,
)
if stage == SyntheticDataStage.PRE_RENDER:
self._set_process_path(renderProductPath, path, "ogPreProcessPath")
elif stage == SyntheticDataStage.POST_RENDER:
self._set_process_path(renderProductPath, path, "ogPostProcessPath")
self._nodeGraphs[path] = nodeGraph
return nodeGraph
def _activate_node_rec(self, templateName: str, renderProductIndex: int = -1, renderProductPaths: list = None, render_var_activations: dict = None) -> None:
renderProductPath = renderProductPaths[renderProductIndex] if renderProductIndex > -1 else None
# renderVar template
if templateName in SyntheticData._ogn_rendervars:
renderVarName = templateName
templateName = SyntheticData._ogn_rendervars[templateName]
if (not render_var_activations is None) and renderProductPath and (templateName == SyntheticData._rendererTemplateName):
if renderProductPath not in render_var_activations:
render_var_activations[renderProductPath]={renderVarName:0}
elif renderVarName not in render_var_activations[renderProductPath]:
render_var_activations[renderProductPath][renderVarName]=0
render_var_activations[renderProductPath][renderVarName]+=1
if templateName not in SyntheticData._ogn_templates_registry:
raise SyntheticDataException(f"graph node template depends on unregistered template {templateName}")
nodePath = SyntheticData._get_node_path(templateName, renderProductPath)
if nodePath in self._graphNodes:
return templateName
template = SyntheticData._ogn_templates_registry[templateName]
nodeStage = template.pipeline_stage
graphPath = SyntheticData._get_graph_path(nodeStage, renderProductPath)
nodeGraph = self._get_or_create_graph(graphPath, nodeStage, renderProductPath)
nodeType = template.node_type_id
usdStage = omni.usd.get_context().get_stage()
primExistWorkaround = not usdStage.GetPrimAtPath(nodePath)
self._graphNodes[nodePath] = nodeGraph.get_wrapped_graph().create_node(nodePath, nodeType, primExistWorkaround)
node = self._graphNodes[nodePath]
# setup static attributes
for attrName, attrVal in template.attributes.items():
if node.get_attribute_exists(attrName):
node.get_attribute(attrName).set(attrVal)
else:
carb.log_error(f"SyntheticData failed to set node {nodePath} static attribute {attrName}")
# do not return error : the default value in the ogn spec will be used
# set inputs:renderProductPathPath
if renderProductPath and node.get_attribute_exists(SyntheticData._renderProductAttributeName):
node.get_attribute(SyntheticData._renderProductAttributeName).set(renderProductPath)
# recursive call for upstream connections
for connIndex in range(len(template.connections)):
connection = template.connections[connIndex]
connTemplateName = connection.node_template_id
connRenderProductPaths = [renderProductPaths[idx] for idx in connection.render_product_idxs] if (
renderProductPaths and connection.render_product_idxs) else None
# activate the template
connTemplateName = self._activate_node_rec(connTemplateName, 0 if connRenderProductPaths else -
1, connRenderProductPaths, render_var_activations)
# setup connection attributes
connRenderProductPath = connRenderProductPaths[0] if connRenderProductPaths else None
connNodePath = SyntheticData._get_node_path(connTemplateName, connRenderProductPath)
connNode = self._graphNodes[connNodePath]
connMap = connection.attributes_mapping
if not connMap is None:
if connMap:
SyntheticData._connect_nodes(connNode, node, connMap, True)
else:
SyntheticData._auto_connect_nodes(connNode, node, True, connIndex)
return templateName
def _deactivate_node_rec(
self,
templateName: str,
renderProductIndex: int = -1,
renderProductPaths: list = None,
render_var_deactivations: dict = None,
only_automatically_activated_nodes: bool = True,
manual_deactivation: bool = True
) -> None:
renderProductPath = renderProductPaths[renderProductIndex] if renderProductIndex > -1 else None
if templateName in SyntheticData._ogn_rendervars:
renderVarName = templateName
templateName = SyntheticData._ogn_rendervars[templateName]
if (not render_var_deactivations is None) and renderProductPath and (templateName == SyntheticData._rendererTemplateName):
if renderProductPath not in render_var_deactivations:
render_var_deactivations[renderProductPath]={renderVarName:0}
elif renderVarName not in render_var_deactivations[renderProductPath]:
render_var_deactivations[renderProductPath][renderVarName]=0
render_var_deactivations[renderProductPath][renderVarName]+=1
nodePath = SyntheticData._get_node_path(templateName, renderProductPath)
# prevent automatically deactivating manually activated node
if (nodePath not in self._graphNodes) or (not manual_deactivation and only_automatically_activated_nodes and (nodePath in self._activatedNodePaths)):
return templateName
node = self._graphNodes[nodePath]
template = SyntheticData._ogn_templates_registry[templateName]
# abort if the node has a downstream connection
for attr in node.get_attributes():
if attr.get_downstream_connection_count():
return templateName
node.get_graph().destroy_node(nodePath, True)
self._graphNodes.pop(nodePath)
# remove unused connections
for connection in template.connections:
connTemplateName = connection.node_template_id
connRenderProductPaths = [renderProductPaths[idx] for idx in connection.render_product_idxs] if (
renderProductPaths and connection.render_product_idxs) else None
# deactivate the template
self._deactivate_node_rec(connTemplateName,
0 if connRenderProductPaths else -1,
connRenderProductPaths,
render_var_deactivations,
only_automatically_activated_nodes,
False)
return templateName
def _set_node_attributes(self, nodePath, attributes) -> None:
if not attributes:
return
if not nodePath in self._graphNodes:
raise SyntheticDataException(f"invalid node {nodePath}")
node = self._graphNodes[nodePath]
for attrName, attrVal in attributes.items():
if node.get_attribute_exists(attrName):
og.Controller(attribute=node.get_attribute(attrName)).set(value=attrVal)
else:
raise SyntheticDataException(f"invalid node attribute {nodePath}.{attrName}")
def _get_node_attributes(self, nodePath, attribute_names: list, gpu=False) -> dict:
if not nodePath in self._graphNodes:
return None
node = self._graphNodes[nodePath]
attributes = {}
for attrName in attribute_names:
if node.get_attribute_exists(attrName):
attributes[attrName] = og.Controller(attribute=node.get_attribute(attrName)).get(on_gpu=gpu)
return attributes
def __init__(self) -> None:
self._nodeGraphs = {}
self._graphNodes = {}
self._activatedNodePaths = []
self._render_product_var_activations = {}
def reset(self, usd=True, remove_activated_render_vars=False) -> None:
"""Reset the SyntheticData instance
Args:
usd : if true reset the graph in the usd stage session layer
remove_activated_render_vars : if True and usd is True remove the render vars activated by the node activation
If the stage is valid it will destroy every graph created.
"""
stage = omni.usd.get_context().get_stage()
if stage and usd:
session_layer = stage.GetSessionLayer()
with Usd.EditContext(stage, session_layer):
for nodeGraph in self._nodeGraphs.values():
self._reset_node_graph(nodeGraph)
if remove_activated_render_vars:
for rp, rvs in self._render_product_var_activations.items():
for rv, num_act in rvs.items():
if num_act[1] and (num_act[0] > 0):
self._remove_rendervar(rp,rv,stage)
self._render_product_var_activations = {}
self._activatedNodePaths = []
self._graphNodes = {}
self._nodeGraphs = {}
def get_graph(self, stage: int = SyntheticDataStage.ON_DEMAND, renderProductPath: str = None) -> object:
"""Return the graph at a given stage, for a given renderProduct.
Gives access to the SyntheticData graphs.
Args:
stage : SyntheticDataStage of the queried graph
renderProductPath : (for POST_RENDER stage only) the renderProductPath for which to get the POST_RENDER graph
Returns:
the graph at the given stage for the given renderProductPath.
"""
if renderProductPath and stage != SyntheticDataStage.POST_RENDER:
raise SyntheticDataException("invalid graph")
graphPath = SyntheticData._get_graph_path(stage, renderProductPath)
return self._get_or_create_graph(graphPath, stage, renderProductPath)
def activate_node_template(
self,
template_name: str,
render_product_path_index: int = -1,
render_product_paths: list = None,
attributes: dict = None,
stage: Usd.Stage = None,
activate_render_vars: bool = True
) -> None:
"""Activate a registered node.
Create a node instance for the given node template and all its missing dependencies (including nodes and renderVar).
The node will be executed during the next stage execution.
Args:
template_name : name of the node template to be activate
render_product_path_index : if the node template is associated to a render product, index of the associated render product in the render product path list
render_product_paths : render product path list to be used for specifying the render product of the node template and its dependencies to activate
attributes : dictionnary of attributes to set to the activated "template_name" node
stage : the stage to change, if None use the stage of the current usd context
activate_render_vars : if True activate the required render_vars, if False it is the user responsability to activate the required render_vars
Return:
A dictionnary containing for every render products the list of render var dependencies of this activation
NB : if activate_render_vars is True those render vars are added
"""
if (template_name not in SyntheticData._ogn_templates_registry) and (template_name not in SyntheticData._ogn_rendervars):
raise SyntheticDataException(f'graph node template "{template_name}" unregistered')
node_path = SyntheticData._get_node_path(
template_name, render_product_paths[render_product_path_index] if render_product_path_index > -1 else None
)
if node_path in self._activatedNodePaths:
return
if not stage:
stage = omni.usd.get_context().get_stage()
if not stage:
raise SyntheticDataException("invalid USD stage")
session_layer = stage.GetSessionLayer()
with Usd.EditContext(stage, session_layer):
render_var_activations = {}
self._activate_node_rec(template_name, render_product_path_index, render_product_paths, render_var_activations)
self._set_node_attributes(node_path, attributes)
self._activatedNodePaths.append(node_path)
# maintain the render_vars activation number for every render products
activated_render_vars = {}
for rp, rvs in render_var_activations.items():
if rp not in self._render_product_var_activations:
self._render_product_var_activations[rp]={}
for rv, num in rvs.items():
need_activation = not self._has_rendervar(rp,rv,stage)
if rv not in self._render_product_var_activations[rp]:
self._render_product_var_activations[rp][rv] = [num, need_activation and activate_render_vars]
else:
self._render_product_var_activations[rp][rv][0] += num
self._render_product_var_activations[rp][rv][1] = need_activation and activate_render_vars
if need_activation:
if rp not in activated_render_vars:
activated_render_vars[rp]=[]
if rv not in activated_render_vars[rp]:
activated_render_vars[rp].append(rv)
if activate_render_vars:
for rp, rvs in activated_render_vars.items():
for rv in rvs:
SyntheticData._add_rendervar(rp, rv, stage)
return activated_render_vars
def is_node_template_activated(
self,
template_name: str,
render_product_path: str = None,
only_manually_activated: bool = False
) -> None:
"""Query the activation status of a node template.
Args:
template_name : name of the node template to query the activation status
render_product_path : render product path for which to check the template activation status (None if not applicable)
only_manually_activated: if True check the activation for only the explicitely activated templates ( exclude the automatically activated template )
Return:
True if the node template is currently activated and, if only_explicitely_activated is True, if it has been explicitely activated
"""
node_path = SyntheticData._get_node_path(template_name, render_product_path)
return node_path in self._activatedNodePaths if only_manually_activated else node_path in self._graphNodes
def deactivate_node_template(
self,
template_name: str,
render_product_path_index: int = -1,
render_product_paths: list = [],
stage: Usd.Stage = None,
deactivate_render_vars: bool = False,
recurse_only_automatically_activated: bool = True
) -> None:
"""Deactivate a registered node.
Delete a node instance for the given node template and all its automatically activated dependencies with no more downstream connections.
The node won't be executed anymore starting with the next stage execution.
Args:
template_name : name of the node template to deactivate
render_product_path_index : if the node template is associated to a render product, index of the associated render product in the render product path list
render_product_paths : render product path list to be used for specifying the render product of the node template and its dependencies to deactivate
stage : the stage to change, if None use the stage of the current usd context
deactivate_render_vars : if True deactivate the render_vars that have been activated in a call to activate_node_template and which are not used anymore by the managed graphs.
Beware that in some cases, some of these render vars maybe actually used by other graphs, hence it is False by default
if False it is the user responsability to deactivate the unused render_vars.
recurse_only_automatically_activated : if True recursively deactivate only automatically activated upstream nodes without other connections
if False recursively deactivate all upstream nodes without other connections
Return:
A dictionnary containing for every render products path the list of render var dependencies that have been activated by activate_node_template and are not used anymore by the managed graphs.
NB : if deactivate_render_vars is True those render vars are removed
"""
if not stage:
stage = omni.usd.get_context().get_stage()
if not stage:
raise SyntheticDataException("invalid USD stage")
session_layer = stage.GetSessionLayer()
with Usd.EditContext(stage, session_layer):
render_var_deactivations = {}
self._deactivate_node_rec(template_name, render_product_path_index, render_product_paths, render_var_deactivations, recurse_only_automatically_activated)
node_path = SyntheticData._get_node_path(
template_name, render_product_paths[render_product_path_index] if render_product_path_index > -1 else None
)
if (node_path in self._activatedNodePaths) and (node_path not in self._graphNodes):
self._activatedNodePaths.remove(node_path)
# maintain the render_vars activation number for every render products
deactivated_render_vars = {}
for rp, rvs in render_var_deactivations.items():
valid_rp = rp in self._render_product_var_activations
for rv, num in rvs.items():
valid_rv = valid_rp and rv in self._render_product_var_activations[rp]
if valid_rv and (self._render_product_var_activations[rp][rv][0] <= num):
if self._render_product_var_activations[rp][rv][1]:
if rp not in deactivated_render_vars:
deactivated_render_vars[rp]=[rv]
else:
deactivated_render_vars[rp].append(rv)
self._render_product_var_activations[rp].pop(rv)
elif valid_rv:
self._render_product_var_activations[rp][rv][0] -= num
if deactivate_render_vars:
for rp, rvs in deactivated_render_vars.items():
for rv in rvs:
SyntheticData._remove_rendervar(rp, rv, stage)
return deactivated_render_vars
def connect_node_template(self, src_template_name: str, dst_template_name: str, render_product_path: str=None, connection_map: dict=None):
"""Connect the given source node template to the destination node template
Args:
src_template_name : name of the source node template
dst_template_name : name of the destination node template
render_product_path : render product path of the node templates (None if the node are not specific to a render product)
connection_map : attribute mapping for the source inputs to the destination outputs. (None for an automatic mapping based on names)
"""
src_node_path = SyntheticData._get_node_path(src_template_name, render_product_path)
if src_node_path not in self._graphNodes:
raise SyntheticDataException(f'cannot connect node template : "{src_node_path}" not activated')
else:
src_node = self._graphNodes[src_node_path]
dst_node_path = SyntheticData._get_node_path(dst_template_name, render_product_path)
if dst_node_path not in self._graphNodes:
raise SyntheticDataException(f'cannot connect node template : "{dst_node_path}" not activated')
else:
dst_node = self._graphNodes[dst_node_path]
if connection_map:
SyntheticData._connect_nodes(src_node, dst_node, connection_map, True)
else:
SyntheticData._auto_connect_nodes(src_node, dst_node, True)
def disconnect_node_template(self, src_template_name: str, dst_template_name: str, render_product_path: str=None, connection_map: dict=None):
"""Disconnect the given source node template to the destination node template
Args:
src_template_name : name of the source node template
dst_template_name : name of the destination node template
render_product_path : render product path of the node templates (None if the node are not specific to a render product)
connection_map : attribute mapping for the source inputs to the destination outputs. (None for an automatic mapping based on names)
"""
src_node_path = SyntheticData._get_node_path(src_template_name, render_product_path)
if src_node_path not in self._graphNodes:
raise SyntheticDataException(f'cannot disconnect node template : "{src_node_path}" not activated')
else:
src_node = self._graphNodes[src_node_path]
dst_node_path = SyntheticData._get_node_path(dst_template_name, render_product_path)
if dst_node_path not in self._graphNodes:
raise SyntheticDataException(f'cannot disconnect node template : "{dst_node_path}" not activated')
else:
dst_node = self._graphNodes[dst_node_path]
if connection_map:
SyntheticData._connect_nodes(src_node, dst_node, connection_map, False)
else:
SyntheticData._auto_connect_nodes(src_node, dst_node, False)
def set_node_attributes(self, template_name: str, attributes: dict, render_product_path: str=None) -> None:
"""Set the value of an activated node attribute.
The function may be used to set the value of multiple activated node input attributes before the execution of its stage.
Args:
template_name : name of the activated node
render_product_path : if the activated node is associated to a render product, provide its path
attributes : dictionnary of attribute name/value to set
"""
node_path = SyntheticData._get_node_path(template_name, render_product_path)
self._set_node_attributes(node_path, attributes)
def get_node_attributes(
self, template_name: str, attribute_names: list, render_product_path=None, gpu=False
) -> dict:
"""Get the value of several activated node's attributes.
The function may be used to retrieve the value of multiple activated node output attributes after the execution of its graph.
Args:
template_name : name of the activated node
attribute_names : list of node attribute names to retrieve the value
render_product_path : if the activated node is associated to a render product, provide its path
gpu : for array data attribute, get a gpu data
Returns:
A dictionnary of attribute name/value for every successfully retrieved attributes
None if the node is not a valid activated node
"""
node_path = SyntheticData._get_node_path(template_name, render_product_path)
return self._get_node_attributes(node_path, attribute_names, gpu)
def set_instance_mapping_semantic_filter(self, predicate="*:*"):
"""Set the semantic filter predicate to be applied to the instance mapping. Contrary to the default
semantic filter this filter affect the instance mapping. All semantic data filtered at this level is
not available in the instance mapping.
Args:
predicate : a semantic filter predicate.
predicate examples :
"typeA : labelA & !labelB | labelC , typeB: labelA ; typeC: labelD"
"typeA : * ; * : labelA"
"""
SyntheticData._ogn_templates_registry[SyntheticData._instanceMappingCtrl].attributes["inputs:semanticFilterPredicate"] = predicate
node_path = SyntheticData._get_node_path(SyntheticData._instanceMappingCtrl)
if node_path in self._graphNodes:
self.set_node_attributes(SyntheticData._instanceMappingCtrl, {"inputs:semanticFilterPredicate":predicate})
def set_default_semantic_filter(self, predicate="*:*", hierarchical_labels=False, matching_labels=True):
"""Set the default semantic filter predicate.
Args:
predicate : a semantic filter predicate.
hierarchical_labels : option to propagate semantic labels within the hiearchy, from parent to childrens
matching_labels : option to remove from the set of labels the one that do not match the predicate
predicate examples :
"typeA : labelA & !labelB | labelC , typeB: labelA ; typeC: labelD"
"typeA : * ; * : labelA"
"""
node_path = SyntheticData._get_node_path(SyntheticData._defaultSemanticFilterName)
attributes = {"inputs:predicate": predicate, "inputs:hierarchicalLabels": hierarchical_labels,
"inputs:matchingLabels": matching_labels}
if node_path in self._graphNodes:
self.set_node_attributes(SyntheticData._defaultSemanticFilterName, attributes)
else:
self.activate_node_template(SyntheticData._defaultSemanticFilterName, attributes=attributes)
def enable_rendervar(self, render_product_path:str, render_var:str, usd_stage: Usd.Stage = None) -> None:
"""Explicitely enable the computation of a render_var for a given render_product.
Args:
render_product_path : the render_product for which to enable the given render_var computation
render_var : the name of the render_var to enable
usd_stage : usd stage
"""
SyntheticData._add_rendervar(render_product_path, render_var, usd_stage)
def disable_rendervar(self, render_product_path:str, render_var:str, usd_stage: Usd.Stage = None) -> None:
"""Explicitely disable the computation of a render_var for a given render_product.
Args:
render_product_path : the render_product for which to disable the given render_var computation
render_var : the name of the render_var to disable
usd_stage : usd stage
"""
SyntheticData._remove_rendervar(render_product_path, render_var, usd_stage)
def is_rendervar_used(self, render_product_path:str, render_var:str) -> None:
""" query the used status of a render var for a render product
Args:
render_product_path: the path of the render product
renver_var: the name of the render_var
Returns:
True if the given render var is currently in use by the activated syntheticData nodes for the given render product
"""
if (render_product_path in self._render_product_var_activations) and (render_var in self._render_product_var_activations[render_product_path]):
return self._render_product_var_activations[render_product_path][render_var][0] > 0
else:
return False
def is_rendervar_enabled(self, render_product_path:str, render_var:str, only_sdg_activated: bool = False, usd_stage: Usd.Stage = None) -> None:
""" query the enabled status of a render var for a render product
Args:
render_product_path: the path of the render product
renver_var: the name of the render_var
only_sdg_activated: consider only the render var automatically enabled by a call to activate_node_template
usd_stage: the usd stage (if None use the current usd context stage)
Returns:
True if the given render var is currently enabled for the given render product
and, if only_sdg_activated is True, if it has been enabled by a call to activate_node_template
"""
if only_sdg_activated:
if (render_product_path in self._render_product_var_activations) and (render_var in self._render_product_var_activations[render_product_path]):
return self._render_product_var_activations[render_product_path][render_var][1]
else:
return False
else:
return SyntheticData._has_rendervar(render_product_path, render_var, usd_stage)
| 81,667 | Python | 48.405929 | 202 | 0.633095 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/model.py | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
__all__ = ['RenderProductModel', 'RenderVarModel']
import omni.usd
import omni.ui as ui
from .SyntheticData import SyntheticData
from pxr import Usd
class RenderProductItem(ui.AbstractItem):
def __init__(self, model):
super().__init__()
self.model = model
class RenderProductModel(ui.AbstractItemModel):
def __init__(self, viewport_name: str, viewport_api):
super().__init__()
# Omniverse interfaces
self._viewport_api = viewport_api
self._stage_update = omni.stageupdate.get_stage_update_interface()
self._stage_subscription = self._stage_update.create_stage_update_node(
"RenderProductModel_" + viewport_name,
None,
None,
None,
self._on_prim_created,
None,
self._on_prim_removed,
)
# The list of the cameras is here
self._render_products = []
# The current index of the editable_combo box
self._current_index = ui.SimpleIntModel()
self._current_index.add_value_changed_fn(self._current_index_changed)
# Iterate the stage and get all the renderProduct
stage = viewport_api.usd_context.get_stage()
if stage:
for prim in Usd.PrimRange(stage.GetPseudoRoot()):
if prim.IsA("UsdRenderProduct"):
self._render_products.append(
RenderProductItem(ui.SimpleStringModel(prim.GetPath().pathString))
)
def destroy(self):
self._viewport_api = None
def get_item_children(self, item):
return self._render_products
def get_item_value_model(self, item, column_id):
if item is None:
return self._current_index
return item.model
def _on_prim_created(self, path):
self._render_products.append(RenderProductItem(ui.SimpleStringModel(path)))
self._item_changed(None)
def _on_prim_removed(self, path):
render_products = [rp.model.as_string for rp in self._render_products]
if path in render_products:
index = render_products.index(path)
del self._render_products[index]
self._current_index.as_int = 0
self._item_changed(None)
def _current_index_changed(self, model):
index = model.as_int
render_product_path = self._render_products[index].model.as_string
self._viewport_api.render_product_path = render_product_path
self._item_changed(None)
class RenderVarItem(ui.AbstractItem):
def __init__(self, model):
super().__init__()
self.model = model
class RenderVarModel(ui.AbstractItemModel):
def _create_item(self, name):
return RenderVarItem(ui.SimpleStringModel(name))
def __init__(self, viewport_api):
super().__init__()
self._viewport_api = viewport_api
self._render_vars = [
self._create_item(rv[0:-7]) for rv in SyntheticData.get_registered_visualization_template_names()
]
self._default_index_int = 0
self._current_index = ui.SimpleIntModel()
self._current_index.add_value_changed_fn(self._current_index_changed)
self._previous_index_int = self._current_index.as_int
self._combine_params = [0, 0, -100]
def destroy(self):
self._viewport_api = None
def get_item_children(self, item):
return self._render_vars
def get_item_value_model(self, item, column_id):
if item is None:
return self._current_index
return item.model
def _current_index_changed(self, model):
index = model.as_int
isdg = SyntheticData.Get()
if isdg:
render_prod_path = self.get_render_product_path()
stage = self._viewport_api.usd_context.get_stage()
if self._render_vars[self._previous_index_int].model.as_string != "LdrColor":
isdg.deactivate_node_template(
self._render_vars[self._previous_index_int].model.as_string + "DisplayPostCombine", 0, [render_prod_path], stage
)
if self._render_vars[index].model.as_string != "LdrColor":
isdg.activate_node_template(
self._render_vars[index].model.as_string + "DisplayPostCombine", 0, [render_prod_path], None, stage
)
SyntheticData.disable_async_rendering()
self._previous_index_int = index
self.update_combine()
self._item_changed(None)
def set_default_item(self):
self._current_index.set_value(self._default_index_int)
def get_render_product_path(self):
render_prod_path = self._viewport_api.render_product_path
# XXX: Issue with Viewport-2 and omni.kit.hydra_texture
# The default product path is returned as a string that isn't the prim-path
# We can work around it by noting the path isn't absolute and fixing it u pi that case.
if render_prod_path and (not render_prod_path.startswith('/')):
render_prod_path = f'/Render/RenderProduct_{render_prod_path}'
return render_prod_path
def set_combine_angle(self, angle):
self._combine_params[0] = angle
self.update_combine()
def set_combine_divide_x(self, divide):
self._combine_params[1] = divide
self.update_combine()
def set_combine_divide_y(self, divide):
self._combine_params[2] = divide
self.update_combine()
def get_combine_angle(self):
return self._combine_params[0]
def get_combine_divide_x(self):
return self._combine_params[1]
def get_combine_divide_y(self):
return self._combine_params[2]
def update_combine(self):
if self._render_vars[self._previous_index_int].model.as_string == "LdrColor":
return
isdg = SyntheticData.Get()
if isdg:
isdg.set_node_attributes(
self._render_vars[self._previous_index_int].model.as_string + "DisplayPostCombine",
{"inputs:parameters": self._combine_params},
self.get_render_product_path()
)
| 6,627 | Python | 35.021739 | 132 | 0.622001 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/menu.py | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
__all__ = ["SynthDataMenuContainer"]
from omni.kit.viewport.menubar.core import (
ComboBoxModel,
ComboBoxItem,
ComboBoxMenuDelegate,
CheckboxMenuDelegate,
IconMenuDelegate,
SliderMenuDelegate,
ViewportMenuContainer,
ViewportMenuItem,
ViewportMenuSeparator
)
from .SyntheticData import SyntheticData
from .visualizer_window import VisualizerWindow
import carb
import omni.ui as ui
from pathlib import Path
import weakref
ICON_PATH = Path(carb.tokens.get_tokens_interface().resolve("${omni.syntheticdata}")).joinpath("data")
UI_STYLE = {"Menu.Item.Icon::SyntheticData": {"image_url": str(ICON_PATH.joinpath("sensor_icon.svg"))}}
class SensorAngleModel(ui.AbstractValueModel):
def __init__(self, getter, setter, *args, **kwargs):
super().__init__(*args, **kwargs)
self.__getter = getter
self.__setter = setter
def destroy(self):
self.__getter = None
self.__setter = None
def get_value_as_float(self) -> float:
return self.__getter()
def get_value_as_int(self) -> int:
return int(self.get_value_as_float())
def set_value(self, value):
value = float(value)
if self.get_value_as_float() != value:
self.__setter(value)
self._value_changed()
class SensorVisualizationModel(ui.AbstractValueModel):
def __init__(self, sensor: str, visualizer_window, *args, **kwargs):
super().__init__(*args, **kwargs)
self.__sensor = sensor
self.__visualizer_window = visualizer_window
def destroy(self):
self.__visualizer_window = None
def get_value_as_bool(self) -> bool:
try:
return bool(self.__sensor in self.__visualizer_window.visualization_activation)
except:
return False
def get_value_as_int(self) -> int:
return 1 if self.get_value_as_bool() else 0
def set_value(self, enabled):
enabled = bool(enabled)
if self.get_value_as_bool() != enabled:
self.__visualizer_window.on_sensor_item_clicked(enabled, self.__sensor)
self._value_changed()
class SynthDataMenuContainer(ViewportMenuContainer):
def __init__(self):
super().__init__(name="SyntheticData",
delegate=IconMenuDelegate("SyntheticData"), # tooltip="Synthetic Data Sensors"),
order=-10, style=UI_STYLE)
self.__hide_on_click = False
self.__visualizer_window = None
self.__sensor_models = set()
def __del__(self):
self.destroy()
def destroy(self):
self.__sensor_models = set()
if self.__visualizer_window:
self.__visualizer_window.close()
self.__visualizer_window = None
super().destroy()
def build_fn(self, desc: dict):
viewport_api = desc.get("viewport_api")
if not viewport_api:
raise RuntimeError("Need a viewport_api")
if self.__visualizer_window:
self.__visualizer_window.close()
self.__visualizer_window = None
name = f"{viewport_api.usd_context_name}"
self.__visualizer_window = VisualizerWindow(name, viewport_api)
with self:
self.add_render_settings_items()
ViewportMenuSeparator()
self.add_angles_items()
ViewportMenuSeparator()
self.add_sensor_selection()
ViewportMenuSeparator()
ViewportMenuItem(name="Clear All", hide_on_click=self.__hide_on_click, onclick_fn=self.clear_all)
ViewportMenuItem(name="Show Window", hide_on_click=self.__hide_on_click, onclick_fn=self.show_window)
super().build_fn(desc)
def add_render_settings_items(self):
render_product_combo_model = self.__visualizer_window.render_product_combo_model
if render_product_combo_model:
ViewportMenuItem(
"RenderProduct",
delegate=ComboBoxMenuDelegate(model=render_product_combo_model),
hide_on_click=self.__hide_on_click,
)
render_var_combo_model = self.__visualizer_window.render_var_combo_model
if render_var_combo_model:
ViewportMenuItem(
"RenderVar",
delegate=ComboBoxMenuDelegate(model=render_var_combo_model),
hide_on_click=self.__hide_on_click,
)
def add_angles_items(self):
render_var_combo_model = self.__visualizer_window.render_var_combo_model
if render_var_combo_model:
ViewportMenuItem(
name="Angle",
hide_on_click=self.__hide_on_click,
delegate=SliderMenuDelegate(
model=SensorAngleModel(render_var_combo_model.get_combine_angle,
render_var_combo_model.set_combine_angle),
min=-100.0,
max=100.0,
tooltip="Set Combine Angle",
),
)
ViewportMenuItem(
name="X",
hide_on_click=self.__hide_on_click,
delegate=SliderMenuDelegate(
model=SensorAngleModel(render_var_combo_model.get_combine_divide_x,
render_var_combo_model.set_combine_divide_x),
min=-100.0,
max=100.0,
tooltip="Set Combine Divide X",
),
)
ViewportMenuItem(
name="Y",
hide_on_click=self.__hide_on_click,
delegate=SliderMenuDelegate(
model=SensorAngleModel(render_var_combo_model.get_combine_divide_y,
render_var_combo_model.set_combine_divide_y),
min=-100.0,
max=100.0,
tooltip="Set Combine Divide Y",
),
)
def add_sensor_selection(self):
for sensor_label, sensor in SyntheticData.get_registered_visualization_template_names_for_display():
model = SensorVisualizationModel(sensor, weakref.proxy(self.__visualizer_window))
self.__sensor_models.add(model)
ViewportMenuItem(
name=sensor_label,
hide_on_click=self.__hide_on_click,
delegate=CheckboxMenuDelegate(model=model, tooltip=f'Enable "{sensor}" visualization')
)
def clear_all(self, *args, **kwargs):
for smodel in self.__sensor_models:
smodel.set_value(False)
# XXX: This isn't really neccessary
if self.__visualizer_window:
self.__visualizer_window.visualization_activation.clear()
def show_window(self, *args, **kwargs):
self.__visualizer_window.toggle_enable_visualization()
SyntheticData.disable_async_rendering()
| 7,377 | Python | 34.301435 | 113 | 0.591975 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/scripts/visualizer_window.py | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
#
__all__ = ["VisualizerWindow"]
import omni.ui as ui
from .SyntheticData import SyntheticData
from .model import RenderProductModel, RenderVarModel
import math
DEBUG_VIEW = False
class VisualizerWindow:
def __init__(self, name, viewport_api):
# create the window
self._visualize_window = ui.Window(name + " Sensors Output ", width=800, height=600)
self._visualize_window.set_width_changed_fn(lambda _: self._update_visualization_ui())
self._visualize_window.set_height_changed_fn(lambda _: self._update_visualization_ui())
self._visualize_window.visible = False
self._render_product_combo_model = RenderProductModel(name, viewport_api) if DEBUG_VIEW else None
self._render_var_combo_model = RenderVarModel(viewport_api)
self._render_product_path = self._render_var_combo_model.get_render_product_path()
# activated visualization contains the set of display node that have been activated through the UI
self._visualization_activation = set()
# visualisation_data contain the image provider for all currently activated display node
self._activated_visualization_data = {}
if hasattr(viewport_api, 'subscribe_to_frame_change'):
self.__frame_changed_sub = viewport_api.subscribe_to_frame_change(self.__frame_changed)
def __frame_changed(self, viewport_api):
render_product = self._render_var_combo_model.get_render_product_path()
self.update(render_product, viewport_api.stage)
def close(self):
self.__frame_changed_sub = None
if self._visualize_window:
self._visualize_window.visible = False
self._visualize_window = None
if self._render_product_combo_model:
self._render_product_combo_model = None
if self._render_var_combo_model:
self._render_var_combo_model = None
self._visualization_activation = set()
self._activated_visualization_data = {}
@property
def render_product_combo_model(self):
return self._render_product_combo_model
@property
def render_var_combo_model(self):
return self._render_var_combo_model
@property
def visualization_activation(self):
return self._visualization_activation
# callback function for handling sensor selection
def on_sensor_item_clicked(self, checked, sensor):
if checked:
self._visualization_activation.add(sensor)
else:
self._visualization_activation.remove(sensor)
# visualization callback
def toggle_enable_visualization(self):
if self._visualize_window:
self._visualize_window.visible = not self._visualize_window.visible
def update(self, render_product_path: str, stage):
sdg_iface = SyntheticData.Get()
if render_product_path != self._render_product_path:
for sensor in self._activated_visualization_data:
sdg_iface.deactivate_node_template(sensor,0,[render_product_path])
self._visualization_activation = set()
self._activated_visualization_data = {}
self._render_product_path = render_product_path
self._render_var_combo_model.set_default_item()
# update the activated sensors
visualization_activation = self._visualization_activation.copy() # NB this is not threadsafe
to_activate = visualization_activation.difference(set(self._activated_visualization_data.keys()))
to_deactivate = set(self._activated_visualization_data.keys()).difference(visualization_activation)
self._activated_visualization_data = {}
for sensor in visualization_activation:
self._activated_visualization_data[sensor] = None
for sensor in to_activate:
sdg_iface.activate_node_template(sensor, 0, [render_product_path], None, stage)
for sensor in to_deactivate:
sdg_iface.deactivate_node_template(sensor, 0, [render_product_path], stage)
# update the visualization window
if self._visualize_window.visible:
for sensor in self._activated_visualization_data:
# create image provider from the sensor texture data
self._activated_visualization_data[sensor] = ui.ImageProvider()
display_output_names = ["outputs:handlePtr", "outputs:width", "outputs:height", "outputs:format"]
display_outputs = sdg_iface.get_node_attributes(sensor, display_output_names, render_product_path)
if display_outputs and all(o in display_outputs for o in display_output_names):
self._activated_visualization_data[sensor].set_image_data(
display_outputs["outputs:handlePtr"],
display_outputs["outputs:width"],
display_outputs["outputs:height"],
ui.TextureFormat(display_outputs["outputs:format"])
)
self._update_visualization_ui()
def _update_visualization_ui(self):
num_sensors = len(self._activated_visualization_data)
if num_sensors == 0:
rows, columns = 0, 0
else:
# Attempt a responsive layout to the number of enabled sensors
columns = math.ceil(math.sqrt(num_sensors))
rows = math.ceil(num_sensors / columns)
if self._visualize_window.height > self._visualize_window.width:
columns, rows = rows, columns
enabled_sensors = list(self._activated_visualization_data.keys())
with self._visualize_window.frame:
with ui.VStack():
idx = 0
for _ in range(rows):
with ui.HStack():
for col in range(columns):
sensor = enabled_sensors[idx]
with ui.VStack():
ui.Label(sensor, alignment=ui.Alignment.CENTER, height=20)
ui.ImageWithProvider(
self._activated_visualization_data[sensor], alignment=ui.Alignment.CENTER_TOP
)
ui.Spacer(height=20)
idx += 1
if col < columns - 1:
# Add a spacer if inner grid edge
ui.Spacer(width=3)
if idx >= len(enabled_sensors):
break
| 7,055 | Python | 44.52258 | 114 | 0.619277 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/__init__.py | """
Presence of this file allows the tests directory to be imported as a module so that all of its contents
can be scanned to automatically add tests that are placed into this directory.
"""
scan_for_test_modules = True
from .sensors.test_bbox3d import *
from .sensors.test_bbox2d_loose import *
from .sensors.test_bbox2d_tight import *
from .sensors.test_distance_to_camera import *
from .sensors.test_distance_to_image_plane import *
from .sensors.test_depth import * # *** DEPRECATED ***
from .sensors.test_depth_linear import * # *** DEPRECATED ***
from .sensors.test_motion_vector import *
from .sensors.test_normals import *
from .sensors.test_occlusion import *
from .sensors.test_rgb import *
from .sensors.test_instance_seg import *
from .sensors.test_semantic_seg import *
from .sensors.test_cross_correspondence import *
from .sensors.test_swh_frame_number import *
from .sensors.test_renderproduct_camera import *
from .sensors.test_rendervar_buff_host_ptr import *
from .sensors.test_semantic_filter import *
from .helpers.test_instance_mapping import *
from .helpers.test_projection import *
from .helpers.test_bboxes import *
from .visualize.test_semantic_seg import *
from .visualize.test_flattener import *
from .pipeline.test_instance_mapping import *
from .pipeline.test_swh_frame_number import *
from .pipeline.test_renderproduct_camera import *
from .graph.test_graph_manipulation import * | 1,417 | Python | 37.324323 | 103 | 0.774876 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/utils.py | import random
import numpy as np
from pxr import Gf, Semantics
def add_semantics(prim, semantic_label, semantic_type="class"):
if not prim.HasAPI(Semantics.SemanticsAPI):
sem = Semantics.SemanticsAPI.Apply(prim, "Semantics")
sem.CreateSemanticTypeAttr()
sem.CreateSemanticDataAttr()
sem.GetSemanticTypeAttr().Set(semantic_type)
sem.GetSemanticDataAttr().Set(semantic_label)
def get_random_transform():
camera_tf = np.eye(4)
camera_tf[:3, :3] = Gf.Matrix3d(Gf.Rotation(np.random.rand(3).tolist(), np.random.rand(3).tolist()))
camera_tf[3, :3] = np.random.rand(3).tolist()
return Gf.Matrix4d(camera_tf)
| 666 | Python | 30.761903 | 104 | 0.689189 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/pipeline/test_renderproduct_camera.py | import carb
from pxr import Gf, UsdGeom, UsdLux, Sdf
import omni.hydratexture
import omni.kit.test
from omni.syntheticdata import SyntheticData, SyntheticDataStage
# Test the instance mapping pipeline
class TestRenderProductCamera(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
def render_product_path(self, hydra_texture) -> str:
'''Return a string to the UsdRender.Product used by the texture'''
render_product = hydra_texture.get_render_product_path()
if render_product and (not render_product.startswith('/')):
render_product = '/Render/RenderProduct_' + render_product
return render_product
def register_test_rp_cam_pipeline(self):
sdg_iface = SyntheticData.Get()
if not sdg_iface.is_node_template_registered("TestSimRpCam"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdTestRenderProductCamera",
attributes={"inputs:stage":"simulation"}
),
template_name="TestSimRpCam"
)
if not sdg_iface.is_node_template_registered("TestPostRpCam"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdTestRenderProductCamera",
[SyntheticData.NodeConnectionTemplate("PostRenderProductCamera")],
attributes={"inputs:stage":"postRender"}
),
template_name="TestPostRpCam"
)
if not sdg_iface.is_node_template_registered("TestOnDemandRpCam"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdTestRenderProductCamera",
[SyntheticData.NodeConnectionTemplate("PostProcessRenderProductCamera")],
attributes={"inputs:stage":"onDemand"}
),
template_name="TestOnDemandRpCam"
)
def activate_test_rp_cam_pipeline(self, test_case_index):
sdg_iface = SyntheticData.Get()
attributes = {
"inputs:renderProductCameraPath": self._camera_path,
"inputs:width": self._resolution[0],
"inputs:height": self._resolution[1],
"inputs:traceError": True
}
sdg_iface.activate_node_template("TestSimRpCam", 0, [self.render_product_path(self._hydra_texture_0)], attributes)
sdg_iface.activate_node_template("TestPostRpCam", 0, [self.render_product_path(self._hydra_texture_0)], attributes)
sdg_iface.activate_node_template("TestOnDemandRpCam", 0, [self.render_product_path(self._hydra_texture_0)],attributes)
async def wait_for_num_frames(self, num_frames, max_num_frames=5000):
self._hydra_texture_rendered_counter = 0
wait_frames_left = max_num_frames
while (self._hydra_texture_rendered_counter < num_frames) and (wait_frames_left > 0):
await omni.kit.app.get_app().next_update_async()
wait_frames_left -= 1
async def setUp(self):
self._settings = carb.settings.acquire_settings_interface()
self._hydra_texture_factory = omni.hydratexture.acquire_hydra_texture_factory_interface()
self._usd_context_name = ''
self._usd_context = omni.usd.get_context(self._usd_context_name)
await self._usd_context.new_stage_async()
# camera
self._camera_path = "/TestRPCamera"
UsdGeom.Camera.Define(omni.usd.get_context().get_stage(), self._camera_path)
self._resolution = [980,540]
# renderer
renderer = "rtx"
if renderer not in self._usd_context.get_attached_hydra_engine_names():
omni.usd.add_hydra_engine(renderer, self._usd_context)
# create the hydra textures
self._hydra_texture_0 = self._hydra_texture_factory.create_hydra_texture(
"TEX0",
width=self._resolution[0],
height=self._resolution[1],
usd_context_name=self._usd_context_name,
usd_camera_path=self._camera_path,
hydra_engine_name=renderer,
is_async=self._settings.get("/app/asyncRendering")
)
self._hydra_texture_rendered_counter = 0
def on_hydra_texture_0(event: carb.events.IEvent):
self._hydra_texture_rendered_counter += 1
self._hydra_texture_rendered_counter_sub = self._hydra_texture_0.get_event_stream().create_subscription_to_push_by_type(
omni.hydratexture.EVENT_TYPE_DRAWABLE_CHANGED,
on_hydra_texture_0,
name='async rendering test drawable update',
)
self.register_test_rp_cam_pipeline()
async def tearDown(self):
self._hydra_texture_rendered_counter_sub = None
self._hydra_texture_0 = None
self._usd_context.close_stage()
omni.usd.release_all_hydra_engines(self._usd_context)
self._hydra_texture_factory = None
self._settings = None
wait_iterations = 6
for _ in range(wait_iterations):
await omni.kit.app.get_app().next_update_async()
async def test_case_0(self):
print("test actual camera pipeline here.")
self.activate_test_rp_cam_pipeline(0)
await self.wait_for_num_frames(33)
| 5,694 | Python | 41.819549 | 128 | 0.612048 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/pipeline/test_swh_frame_number.py | import carb
from pxr import Gf, UsdGeom, UsdLux, Sdf
import omni.hydratexture
import omni.kit.test
from omni.syntheticdata import SyntheticData, SyntheticDataStage
# Test the Fabric frame number synchronization
class TestSWHFrameNumber(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
def render_product_path(self, hydra_texture) -> str:
'''Return a string to the UsdRender.Product used by the texture'''
render_product = hydra_texture.get_render_product_path()
if render_product and (not render_product.startswith('/')):
render_product = '/Render/RenderProduct_' + render_product
return render_product
async def wait_for_num_sims(self, num_sims, max_num_sims=5000):
self._hydra_texture_rendered_counter = 0
wait_sims_left = max_num_sims
while (self._hydra_texture_rendered_counter < num_sims) and (wait_sims_left > 0):
await omni.kit.app.get_app().next_update_async()
wait_sims_left -= 1
async def setUp(self):
self._settings = carb.settings.acquire_settings_interface()
self._hydra_texture_factory = omni.hydratexture.acquire_hydra_texture_factory_interface()
self._usd_context_name = ''
self._usd_context = omni.usd.get_context(self._usd_context_name)
await self._usd_context.new_stage_async()
# Setup the scene
stage = omni.usd.get_context().get_stage()
world_prim = UsdGeom.Xform.Define(stage,"/World")
UsdGeom.Xformable(world_prim).AddTranslateOp().Set((0, 0, 0))
UsdGeom.Xformable(world_prim).AddRotateXYZOp().Set((0, 0, 0))
capsule0_prim = stage.DefinePrim("/World/Capsule0", "Capsule")
UsdGeom.Xformable(capsule0_prim).AddTranslateOp().Set((100, 0, 0))
UsdGeom.Xformable(capsule0_prim).AddScaleOp().Set((30, 30, 30))
UsdGeom.Xformable(capsule0_prim).AddRotateXYZOp().Set((-90, 0, 0))
capsule0_prim.GetAttribute("primvars:displayColor").Set([(0.3, 1, 0)])
capsule1_prim = stage.DefinePrim("/World/Capsule1", "Capsule")
UsdGeom.Xformable(capsule1_prim).AddTranslateOp().Set((-100, 0, 0))
UsdGeom.Xformable(capsule1_prim).AddScaleOp().Set((30, 30, 30))
UsdGeom.Xformable(capsule1_prim).AddRotateXYZOp().Set((-90, 0, 0))
capsule1_prim.GetAttribute("primvars:displayColor").Set([(0, 1, 0.3)])
spherelight = UsdLux.SphereLight.Define(stage, "/SphereLight")
spherelight.GetIntensityAttr().Set(30000)
spherelight.GetRadiusAttr().Set(30)
camera_1 = stage.DefinePrim("/Camera1", "Camera")
camera_1.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
UsdGeom.Xformable(camera_1).AddTranslateOp().Set((0, 250, 0))
UsdGeom.Xformable(camera_1).AddRotateXYZOp().Set((-90, 0, 0))
# renderer
renderer = "rtx"
if renderer not in self._usd_context.get_attached_hydra_engine_names():
omni.usd.add_hydra_engine(renderer, self._usd_context)
# create the hydra textures
self._hydra_texture_0 = self._hydra_texture_factory.create_hydra_texture(
"TEX0",
1920,
1080,
self._usd_context_name,
hydra_engine_name=renderer,
is_async=self._settings.get("/app/asyncRendering")
)
render_product_path_0 = self.render_product_path(self._hydra_texture_0)
self._hydra_texture_rendered_counter = 0
def on_hydra_texture_0(event: carb.events.IEvent):
self._hydra_texture_rendered_counter += 1
self._hydra_texture_rendered_counter_sub = self._hydra_texture_0.get_event_stream().create_subscription_to_push_by_type(
omni.hydratexture.EVENT_TYPE_DRAWABLE_CHANGED,
on_hydra_texture_0,
name='async rendering test drawable update',
)
self._hydra_texture_1 = self._hydra_texture_factory.create_hydra_texture(
"TEX1",
512,
512,
self._usd_context_name,
str(camera_1.GetPath()),
hydra_engine_name=renderer,
is_async=self._settings.get("/app/asyncRendering")
)
render_product_path_1 = self.render_product_path(self._hydra_texture_1)
# SyntheticData singleton interface
sdg_iface = SyntheticData.Get()
# Register node templates in the SyntheticData register
# (a node template is a template for creating a node specified by its type and its connections)
#
# to illustrate we are using the generic omni.syntheticdata.SdTestStageSynchronization node type which supports every stage of the SyntheticData pipeline. When executed it logs the fabric frame number.
#
# register a node template in the simulation stage
# NB : this node template has no connections
if not sdg_iface.is_node_template_registered("TestSyncSim"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION, # node tempalte stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
attributes={
"inputs:tag":"0",
"inputs:randomSeed": 13,
"inputs:randomMaxProcessingTimeUs": 33333,
"inputs:traceError": True
}
), # node template default attribute values (when differs from the default value specified in the .ogn)
template_name="TestSyncSim" # node template name
)
# register a node template in the postrender stage
# NB : this template may be activated for several different renderproducts
if not sdg_iface.is_node_template_registered("TestSyncPost"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER, # node template stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
# node template connections
[
# connected to a TestSyncSim node (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("TestSyncSim", (), None),
# connected to a LdrColorSD rendervar (the renderVar will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("LdrColorSD"),
# connected to a BoundingBox3DSD rendervar (the renderVar will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("BoundingBox3DSD")
],
attributes={
"inputs:randomSeed": 27,
"inputs:randomMaxProcessingTimeUs": 33333,
"inputs:traceError": True
}
),
template_name="TestSyncPost" # node template name
)
# register a node template in the postprocess stage
# NB : this template may be activated for several different renderproducts
if not sdg_iface.is_node_template_registered("TestSyncOnDemand"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND, # node template stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
# node template connections
[
# connected to a TestSyncSim node (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("TestSyncSim", (), None),
# connected to a PostProcessDispatch node : the PostProcessDispatch node trigger the execution of its downstream connections for every rendered frame
# (a PostProcessDispatch node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("PostProcessDispatch")
],
attributes={
"inputs:randomSeed": 51,
"inputs:randomMaxProcessingTimeUs": 33333,
"inputs:traceError": True
} # node template default attribute values (when differs from the default value specified in the .ogn)
),
template_name="TestSyncOnDemand" # node template name
)
# register a node template in the postprocess stage
# NB : this template may be activated for any combination of renderproduct pairs
if not sdg_iface.is_node_template_registered("TestSyncCross"):
# register an accumulator which trigger once when all its upstream connections have triggered
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND, # node template stage
"omni.graph.action.SyncGate", # node template type
# node template connections
[
# connected to the PostProcessDispatcher for the synchronization value
SyntheticData.NodeConnectionTemplate(
"PostProcessDispatcher",
(),
{"outputs:swhFrameNumber":"inputs:syncValue"}
),
# connected to a TestSyncOnDemand node for the first renderproduct (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate(
"TestSyncOnDemand",
(0,),
{"outputs:exec":"inputs:execIn"}
),
# connected to a TestSyncOnDemand node for the second renderproduct (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate(
"TestSyncOnDemand",
(1,),
{"outputs:exec":"inputs:execIn"}
),
]
),
template_name="TestSyncAccum" # node template name
)
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND, # node template stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
# node template connections
[
# connected to a TestSyncAccum node (a TestSyncAccum node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate(
"TestSyncAccum",
(0,1),
{
"outputs:execOut":"inputs:exec",
"outputs:syncValue":"inputs:swhFrameNumber"
}
),
],
attributes={
"inputs:randomSeed": 62,
"inputs:randomMaxProcessingTimeUs": 33333,
"inputs:traceError": True
}
),
template_name="TestSyncCross" # node template name
)
# Activate the node templates for the renderproducts
# this will create the node (and all their missing dependencies) within the associated graphs
#
# activate the TestSyncSim
sdg_iface.activate_node_template("TestSyncSim")
# wait for the next update to make sure the simulation node is activated when activating the post-render and post-process nodes
# activate the TestSyncPost for the renderpoduct renderpoduct_0
# this will also activate the LdrColorSD and BoundingBox3DSD renderVars for the renderpoduct renderpoduct_0
# this will set the tag node attribute to "1"
sdg_iface.activate_node_template("TestSyncPost", 0, [render_product_path_0],{"inputs:tag":"1"})
# activate the TestSyncPost for the renderpoduct renderpoduct_1
# this will also activate the LdrColorSD and BoundingBox3DSD renderVars for the renderpoduct renderpoduct_1
# NB TestSyncSim has already been activated
# this will set the tag node attribute to "2"
sdg_iface.activate_node_template("TestSyncPost", 0, [render_product_path_1],{"inputs:tag":"2"})
# FIXME : wait a couple of simulation updates as a workaround of an issue with the first
# syncGate not being activated
await self.wait_for_num_sims(3)
# activate the TestSyncCross for the renderpoducts [renderproduct_0, renderproduct_1]
# this will also activate :
# - TestSyncAccum for the renderpoducts [renderproduct_0, renderproduct_1]
# - PostProcessDispatch for the renderpoduct renderproduct_0
# - TestSyncOnDemand for the renderproduct renderproduct_0
# - TestSyncOnDemand for the renderproduct renderproduct_1
# - PostProcessDispatch for the renderpoduct renderproduct_1
# this will set the tag node attribute to "5" and processingTime to 30000
sdg_iface.activate_node_template("TestSyncCross", 0, [render_product_path_0,render_product_path_1],{"inputs:tag":"5"})
# Set some specific attributes to nodes that have been automatically activated
# set the tag to the TestSyncOnDemand for renderproduct renderproduct_0
sdg_iface.set_node_attributes("TestSyncOnDemand",{"inputs:tag":"3"},render_product_path_0)
# set the tag to the TestSyncOnDemand for renderproduct renderproduct_1
sdg_iface.set_node_attributes("TestSyncOnDemand",{"inputs:tag":"4"},render_product_path_1)
# setup members
self._num_sims = 555
async def tearDown(self):
self._hydra_texture_rendered_counter_sub = None
self._hydra_texture_0 = None
self._hydra_texture_1 = None
self._usd_context.close_stage()
omni.usd.release_all_hydra_engines(self._usd_context)
self._hydra_texture_factory = None
self._settings = None
wait_iterations = 6
for _ in range(wait_iterations):
await omni.kit.app.get_app().next_update_async()
async def test_pipline(self):
""" Test swh frame synhronization
"""
await self.wait_for_num_sims(self._num_sims)
| 15,183 | Python | 51.178694 | 209 | 0.595534 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/pipeline/test_instance_mapping.py | import carb
from pxr import Gf, UsdGeom, UsdLux, Sdf
import omni.hydratexture
import omni.kit.test
from omni.syntheticdata import SyntheticData, SyntheticDataStage
# Test the instance mapping pipeline
class TestInstanceMapping(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
def render_product_path(self, hydra_texture) -> str:
'''Return a string to the UsdRender.Product used by the texture'''
render_product = hydra_texture.get_render_product_path()
if render_product and (not render_product.startswith('/')):
render_product = '/Render/RenderProduct_' + render_product
return render_product
def register_test_instance_mapping_pipeline(self):
sdg_iface = SyntheticData.Get()
if not sdg_iface.is_node_template_registered("TestSimSWHFrameNumber"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdUpdateSwFrameNumber"
),
template_name="TestSimSWHFrameNumber"
)
if not sdg_iface.is_node_template_registered("TestSimInstanceMapping"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdTestInstanceMapping",
[
SyntheticData.NodeConnectionTemplate("TestSimSWHFrameNumber", ())
],
{"inputs:stage":"simulation"}
),
template_name="TestSimInstanceMapping"
)
if not sdg_iface.is_node_template_registered("TestOnDemandInstanceMapping"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdTestInstanceMapping",
[
SyntheticData.NodeConnectionTemplate("InstanceMappingPtrWithTransforms"),
SyntheticData.NodeConnectionTemplate("TestSimInstanceMapping", (), attributes_mapping={"outputs:exec": "inputs:exec"})
],
{"inputs:stage":"ondemand"}
),
template_name="TestOnDemandInstanceMapping"
)
def activate_test_instance_mapping_pipeline(self, case_index):
sdg_iface = SyntheticData.Get()
sdg_iface.activate_node_template("TestSimInstanceMapping", attributes={"inputs:testCaseIndex":case_index})
sdg_iface.activate_node_template("TestOnDemandInstanceMapping", 0,
[self.render_product_path(self._hydra_texture_0)],
{"inputs:testCaseIndex":case_index})
sdg_iface.connect_node_template("TestSimInstanceMapping",
"InstanceMappingPre", None,
{"outputs:semanticFilterPredicate":"inputs:semanticFilterPredicate"})
async def wait_for_num_frames(self, num_frames, max_num_frames=5000):
self._hydra_texture_rendered_counter = 0
wait_frames_left = max_num_frames
while (self._hydra_texture_rendered_counter < num_frames) and (wait_frames_left > 0):
await omni.kit.app.get_app().next_update_async()
wait_frames_left -= 1
async def setUp(self):
self._settings = carb.settings.acquire_settings_interface()
self._hydra_texture_factory = omni.hydratexture.acquire_hydra_texture_factory_interface()
self._usd_context_name = ''
self._usd_context = omni.usd.get_context(self._usd_context_name)
await self._usd_context.new_stage_async()
# renderer
renderer = "rtx"
if renderer not in self._usd_context.get_attached_hydra_engine_names():
omni.usd.add_hydra_engine(renderer, self._usd_context)
# create the hydra textures
self._hydra_texture_0 = self._hydra_texture_factory.create_hydra_texture(
"TEX0",
1920,
1080,
self._usd_context_name,
hydra_engine_name=renderer,
is_async=self._settings.get("/app/asyncRendering")
)
self._hydra_texture_rendered_counter = 0
def on_hydra_texture_0(event: carb.events.IEvent):
self._hydra_texture_rendered_counter += 1
self._hydra_texture_rendered_counter_sub = self._hydra_texture_0.get_event_stream().create_subscription_to_push_by_type(
omni.hydratexture.EVENT_TYPE_DRAWABLE_CHANGED,
on_hydra_texture_0,
name='async rendering test drawable update',
)
self.register_test_instance_mapping_pipeline()
async def tearDown(self):
self._hydra_texture_rendered_counter_sub = None
self._hydra_texture_0 = None
self._usd_context.close_stage()
omni.usd.release_all_hydra_engines(self._usd_context)
self._hydra_texture_factory = None
self._settings = None
wait_iterations = 6
for _ in range(wait_iterations):
await omni.kit.app.get_app().next_update_async()
async def test_case_0(self):
self.activate_test_instance_mapping_pipeline(0)
await self.wait_for_num_frames(11)
async def test_case_1(self):
self.activate_test_instance_mapping_pipeline(1)
await self.wait_for_num_frames(11)
async def test_case_2(self):
self.activate_test_instance_mapping_pipeline(2)
await self.wait_for_num_frames(11)
async def test_case_3(self):
self.activate_test_instance_mapping_pipeline(3)
await self.wait_for_num_frames(11)
async def test_case_4(self):
self.activate_test_instance_mapping_pipeline(4)
await self.wait_for_num_frames(11)
| 6,115 | Python | 40.605442 | 142 | 0.601962 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_motion_vector.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from PIL import Image
from time import time
from pathlib import Path
import carb
import numpy as np
from numpy.lib.arraysetops import unique
import unittest
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestMotionVector(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
self.output_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "output"
def writeDataToImage(self, data, name):
if not os.path.isdir(self.output_image_path):
os.mkdir(self.output_image_path)
data = ((data + 1.0) / 2) * 255
outputPath = str(self.output_image_path) + "/" + name + ".png"
print("Writing data to " + outputPath)
Image.fromarray(data.astype(np.uint8), "RGBA").save(outputPath)
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.MotionVector)
async def test_empty(self):
""" Test motion vector sensor on empty stage.
"""
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_motion_vector(self.viewport)
allChannelsAreZero = np.allclose(data, 0, atol=0.001)
if not allChannelsAreZero:
self.writeDataToImage(data, "test_empty")
assert allChannelsAreZero
async def test_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_motion_vector(self.viewport)
assert data.dtype == np.float32
async def test_unmoving_cube(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
cube.GetAttribute("primvars:displayColor").Set([(0, 0, 1)])
UsdGeom.Xformable(cube).AddTranslateOp()
cube.GetAttribute("xformOp:translate").Set((350, 365, 350), time=0)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_motion_vector(self.viewport)
# 4th channel will wary based on geo hit, so we ignore checking it here
rgbChannelsAreZero = np.allclose(data[:, [0, 1, 2]], 0, atol=0.001)
if not rgbChannelsAreZero:
self.writeDataToImage(data, "test_unmoving_cube")
assert rgbChannelsAreZero
@unittest.skip("OM-44310")
async def test_partially_disoccluding_cube(self):
# disabling temporarly the test for OMNI-GRAPH support : OM-44310
stage = omni.usd.get_context().get_stage()
stage.SetStartTimeCode(0)
stage.SetEndTimeCode(100)
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(10)
cube.GetAttribute("primvars:displayColor").Set([(0, 0, 1)])
# add translation down to create disocclusion due to fetching from out of screen bounds
UsdGeom.Xformable(cube).AddTranslateOp()
cube.GetAttribute("xformOp:translate").Set((480, 487, 480), time=0)
cube.GetAttribute("xformOp:translate").Set((480, 480, 480), time=0.001)
# add rotation around up vector to create disocclusion due to fetching from an incompatible surface
UsdGeom.Xformable(cube).AddRotateYOp()
cube.GetAttribute("xformOp:rotateY").Set(40, time=0)
cube.GetAttribute("xformOp:rotateY").Set(70, time=0.001)
await omni.kit.app.get_app().next_update_async()
# Render one frame
itl = omni.timeline.get_timeline_interface()
itl.play()
await syn.sensors.next_sensor_data_async(self.viewport, True)
data = syn.sensors.get_motion_vector(self.viewport)
golden_image = np.load(self.golden_image_path / "motion_partially_disoccluding_cube.npz")["array"]
# normalize xy (mvec) to zw channels' value range
# x100 seems like a good number to bring mvecs to ~1
data[:, [0, 1]] *= 100
golden_image[:, [0, 1]] *= 100
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
# OM-41605 - using higher std dev here to make linux run succeed
std_dev_tolerance = 0.12
print("Calculated std.dev: " + str(std_dev), " Std dev tolerance: " + str(std_dev_tolerance))
if std_dev >= std_dev_tolerance:
self.writeDataToImage(golden_image, "test_partially_disoccluding_cube_golden")
self.writeDataToImage(data, "test_partially_disoccluding_cube")
np.savez_compressed(self.output_image_path / "motion_partially_disoccluding_cube.npz", array=data)
assert std_dev < std_dev_tolerance
# After running each test
async def tearDown(self):
pass
| 6,086 | Python | 41.566433 | 141 | 0.661847 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_occlusion.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
from time import time
from pathlib import Path
import carb
import numpy as np
import unittest
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import UsdGeom, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestOcclusion(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
# Before running each test
async def setUp(self):
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
self.viewport = get_active_viewport()
# Initialize Sensors
syn.sensors.enable_sensors(
self.viewport,
[
syn._syntheticdata.SensorType.BoundingBox2DLoose,
syn._syntheticdata.SensorType.BoundingBox2DTight,
syn._syntheticdata.SensorType.Occlusion,
],
)
await syn.sensors.next_sensor_data_async(self.viewport,True)
async def test_fields_exist(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_occlusion(self.viewport)
valid_dtype = [("instanceId", "<u4"), ("semanticId", "<u4"), ("occlusionRatio", "<f4")]
assert data.dtype == np.dtype(valid_dtype)
async def test_fields_exist_parsed(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_occlusion(self.viewport, parsed=True)
valid_dtype = [
("uniqueId", "<i4"),
("name", "O"),
("semanticLabel", "O"),
("metadata", "O"),
("instanceIds", "O"),
("semanticId", "<u4"),
("occlusionRatio", "<f4"),
]
assert data.dtype == np.dtype(valid_dtype)
async def test_occlusion(self):
path = os.path.join(FILE_DIR, "../data/scenes/occlusion.usda")
await omni.usd.get_context().open_stage_async(path)
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
occlusion_out = syn.sensors.get_occlusion(self.viewport, parsed=True)
for row in occlusion_out:
gt = float(row["semanticLabel"]) / 100.0
assert math.isclose(gt, row["occlusionRatio"], abs_tol=0.015), f"Expected {gt}, got {row['occlusionRatio']}"
async def test_self_occlusion(self):
path = os.path.join(FILE_DIR, "../data/scenes/torus_sphere.usda")
await omni.usd.get_context().open_stage_async(path)
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
occlusion_out = syn.sensors.get_occlusion(self.viewport)
occlusion_out_ratios = np.sort(occlusion_out["occlusionRatio"])
assert np.allclose(occlusion_out_ratios, [0.0, 0.6709], atol=0.05)
async def test_full_occlusion(self):
path = os.path.join(FILE_DIR, "../data/scenes/cube_full_occlusion.usda")
await omni.usd.get_context().open_stage_async(path)
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
occlusion_out = syn.sensors.get_occlusion(self.viewport)
occlusion_out_ratios = np.sort(occlusion_out["occlusionRatio"])
assert np.allclose(occlusion_out_ratios, [0.0, 1.0], atol=0.05)
async def test_occlusion_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
path = os.path.join(FILE_DIR, "../data/scenes/occlusion.usda")
await omni.usd.get_context().open_stage_async(path)
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
occlusion_out = syn.sensors.get_occlusion(self.viewport, parsed=True)
for row in occlusion_out:
gt = float(row["semanticLabel"]) / 100.0
assert math.isclose(gt, row["occlusionRatio"], abs_tol=0.015), f"Expected {gt}, got {row['occlusionRatio']}"
async def test_occlusion_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
# Set the rendering mode to be ray traced lighting.
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
path = os.path.join(FILE_DIR, "../data/scenes/occlusion.usda")
await omni.usd.get_context().open_stage_async(path)
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
occlusion_out = syn.sensors.get_occlusion(self.viewport, parsed=True)
for row in occlusion_out:
gt = float(row["semanticLabel"]) / 100.0
assert math.isclose(gt, row["occlusionRatio"], abs_tol=0.015), f"Expected {gt}, got {row['occlusionRatio']}"
async def test_occlusion_ftheta(self):
""" Basic funtionality test of the sensor under ftheta camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
path = os.path.join(FILE_DIR, "../data/scenes/occlusion.usda")
await omni.usd.get_context().open_stage_async(path)
await omni.kit.app.get_app().next_update_async()
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((100, 200, 300))
self.viewport.camera_path = camera.GetPath()
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
# Camera type should not affect occlusion.
occlusion_out = syn.sensors.get_occlusion(self.viewport, parsed=True)
data = np.array([row['occlusionRatio'] for row in occlusion_out])
# np.savez_compressed(self.golden_image_path / 'occlusion_ftheta.npz', array=data)
golden = np.load(self.golden_image_path / "occlusion_ftheta.npz")["array"]
assert np.isclose(data, golden, atol=1e-3).all()
async def test_occlusion_spherical(self):
""" Basic funtionality test of the sensor under spherical camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
path = os.path.join(FILE_DIR, "../data/scenes/occlusion.usda")
await omni.usd.get_context().open_stage_async(path)
await omni.kit.app.get_app().next_update_async()
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyeSpherical")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((100, 200, 300))
self.viewport.camera_path = camera.GetPath()
syn.sensors.enable_sensors(self.viewport, [syn._syntheticdata.SensorType.Occlusion])
await syn.sensors.next_sensor_data_async(self.viewport,True)
# Camera type should not affect occlusion.
occlusion_out = syn.sensors.get_occlusion(self.viewport, parsed=True)
data = np.array([row['occlusionRatio'] for row in occlusion_out])
# np.savez_compressed(self.golden_image_path / 'occlusion_spherical.npz', array=data)
golden = np.load(self.golden_image_path / "occlusion_spherical.npz")["array"]
assert np.isclose(data, golden, atol=1e-1).all()
@unittest.skip("OM-44310")
async def test_occlusion_quadrant(self):
# disabling temporarly the test for OMNI-GRAPH support : OM-44310
# Test quadrant sensor. It takes loose and tight bounding boxes to
# return the type of occlusion
# Expected occlusion value for time=1, 2, 3...
TESTS = [
"fully-occluded",
"left",
"right",
"bottom",
"top",
"fully-visible", # corner occlusion
"fully-visible", # corner occlusion
"bottom-right",
"bottom-left",
"top-right",
"top-left",
"fully-visible",
]
path = os.path.join(FILE_DIR, "../data/scenes/occlusion_quadrant.usda")
await omni.usd.get_context().open_stage_async(path)
await omni.kit.app.get_app().next_update_async()
syn.sensors.enable_sensors(
self.viewport,
[
syn._syntheticdata.SensorType.BoundingBox2DLoose,
syn._syntheticdata.SensorType.BoundingBox2DTight,
syn._syntheticdata.SensorType.Occlusion,
],
)
await syn.sensors.next_sensor_data_async(self.viewport,True)
timeline_iface = omni.timeline.acquire_timeline_interface()
timeline_iface.set_time_codes_per_second(1)
for time, gt in enumerate(TESTS):
timeline_iface.set_current_time(time)
await omni.kit.app.get_app().next_update_async()
# Investigate these in OM-31155
sensor_out = syn.sensors.get_occlusion_quadrant(self.viewport)
result = sensor_out["occlusion_quadrant"][0]
assert result == gt, f"Got {result}, expected {gt}"
# After running each test
async def tearDown(self):
pass
| 11,419 | Python | 43.784314 | 141 | 0.644715 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_renderproduct_camera.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import carb
from pxr import Gf, UsdGeom, Sdf, UsdLux
from omni.kit.viewport.utility import get_active_viewport, create_viewport_window
import omni.kit.test
from omni.syntheticdata import SyntheticData, SyntheticDataStage
# Test the RenderProductCamera nodes
class TestRenderProductCamera(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
async def setUp(self):
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
self.numLoops = 7
self.multiViewport = False
# Setup the scene
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
# Setup viewports / renderproduct
# first default viewport with the default perspective camera
viewport_0 = get_active_viewport()
resolution_0 = viewport_0.resolution
camera_0 = UsdGeom.Camera.Define(stage, "/Camera0").GetPrim()
viewport_0.camera_path = camera_0.GetPath()
render_product_path_0 = viewport_0.render_product_path
self.render_product_path_0 = render_product_path_0
# second viewport with a ftheta camera
if self.multiViewport:
resolution_1 = (512, 512)
viewport_window = create_viewport_window(width=resolution_1[0], height=resolution_1[1])
viewport_1 = viewport_window.viewport_api
viewport_1.resolution = resolution_1
camera_1 = UsdGeom.Camera.Define(stage, "/Camera1").GetPrim()
viewport_1.camera_path = camera_1.GetPath()
render_product_path_1 = viewport_1.render_product_path
self.render_product_path_1 = render_product_path_1
# SyntheticData singleton interface
sdg_iface = SyntheticData.Get()
if not sdg_iface.is_node_template_registered("TestSimRpCam"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdTestRenderProductCamera",
attributes={"inputs:stage":"simulation"}
),
template_name="TestSimRpCam"
)
if not sdg_iface.is_node_template_registered("TestPostRpCam"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER,
"omni.syntheticdata.SdTestRenderProductCamera",
[SyntheticData.NodeConnectionTemplate("PostRenderProductCamera")],
attributes={"inputs:stage":"postRender"}
),
template_name="TestPostRpCam"
)
if not sdg_iface.is_node_template_registered("TestOnDemandRpCam"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdTestRenderProductCamera",
[SyntheticData.NodeConnectionTemplate("PostProcessRenderProductCamera")],
attributes={"inputs:stage":"onDemand"}
),
template_name="TestOnDemandRpCam"
)
attributes_0 = {
"inputs:renderProductCameraPath":camera_0.GetPath().pathString,
"inputs:width":resolution_0[0],
"inputs:height":resolution_0[1]
}
sdg_iface.activate_node_template("TestSimRpCam", 0, [render_product_path_0], attributes_0)
sdg_iface.activate_node_template("TestPostRpCam", 0, [render_product_path_0], attributes_0)
sdg_iface.activate_node_template("TestOnDemandRpCam", 0, [render_product_path_0],attributes_0)
if self.multiViewport:
attributes_1 = {
"inputs:renderProductCameraPath":camera_1.GetPath().pathString,
"inputs:width":resolution_1[0],
"inputs:height":resolution_1[1]
}
sdg_iface.activate_node_template("TestSimRpCam", 0, [render_product_path_1], attributes_1)
sdg_iface.activate_node_template("TestPostRpCam", 0, [render_product_path_1], attributes_1)
sdg_iface.activate_node_template("TestOnDemandRpCam", 0, [render_product_path_1],attributes_1)
async def test_renderproduct_camera(self):
""" Test render product camera pipeline
"""
sdg_iface = SyntheticData.Get()
test_outname = "outputs:test"
test_attributes_names = [test_outname]
for _ in range(3):
await omni.kit.app.get_app().next_update_async()
for _ in range(self.numLoops):
await omni.kit.app.get_app().next_update_async()
assert sdg_iface.get_node_attributes("TestSimRpCam", test_attributes_names, self.render_product_path_0)[test_outname]
assert sdg_iface.get_node_attributes("TestPostRpCam", test_attributes_names, self.render_product_path_0)[test_outname]
assert sdg_iface.get_node_attributes("TestOnDemandRpCam", test_attributes_names, self.render_product_path_0)[test_outname]
if self.multiViewport:
assert sdg_iface.get_node_attributes("TestSimRpCam", test_attributes_names, self.render_product_path_1)[test_outname]
assert sdg_iface.get_node_attributes("TestPostRpCam", test_attributes_names, self.render_product_path_1)[test_outname]
assert sdg_iface.get_node_attributes("TestOnDemandRpCam", test_attributes_names, self.render_product_path_1)[test_outname]
async def tearDown(self):
pass
| 6,091 | Python | 46.224806 | 138 | 0.631752 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_swh_frame_number.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import carb
from pxr import Gf, UsdGeom, UsdLux, Sdf
import unittest
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport, create_viewport_window
from omni.syntheticdata import SyntheticData, SyntheticDataStage
# Test the Fabric frame number synchronization
class TestSWHFrameNumber(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
async def setUp(self):
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
# Setup the scene
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
world_prim = UsdGeom.Xform.Define(stage,"/World")
UsdGeom.Xformable(world_prim).AddTranslateOp().Set((0, 0, 0))
UsdGeom.Xformable(world_prim).AddRotateXYZOp().Set((0, 0, 0))
capsule0_prim = stage.DefinePrim("/World/Capsule0", "Capsule")
UsdGeom.Xformable(capsule0_prim).AddTranslateOp().Set((100, 0, 0))
UsdGeom.Xformable(capsule0_prim).AddScaleOp().Set((30, 30, 30))
UsdGeom.Xformable(capsule0_prim).AddRotateXYZOp().Set((-90, 0, 0))
capsule0_prim.GetAttribute("primvars:displayColor").Set([(0.3, 1, 0)])
capsule1_prim = stage.DefinePrim("/World/Capsule1", "Capsule")
UsdGeom.Xformable(capsule1_prim).AddTranslateOp().Set((-100, 0, 0))
UsdGeom.Xformable(capsule1_prim).AddScaleOp().Set((30, 30, 30))
UsdGeom.Xformable(capsule1_prim).AddRotateXYZOp().Set((-90, 0, 0))
capsule1_prim.GetAttribute("primvars:displayColor").Set([(0, 1, 0.3)])
spherelight = UsdLux.SphereLight.Define(stage, "/SphereLight")
spherelight.GetIntensityAttr().Set(30000)
spherelight.GetRadiusAttr().Set(30)
# first default viewport with the default perspective camera
viewport_0 = get_active_viewport()
render_product_path_0 = viewport_0.render_product_path
# second viewport with a ftheta camera
viewport_1_window = create_viewport_window(width=512, height=512)
viewport_1 = viewport_1_window.viewport_api
camera_1 = stage.DefinePrim("/Camera1", "Camera")
camera_1.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
UsdGeom.Xformable(camera_1).AddTranslateOp().Set((0, 250, 0))
UsdGeom.Xformable(camera_1).AddRotateXYZOp().Set((-90, 0, 0))
viewport_1.camera_path = camera_1.GetPath()
render_product_path_1 = viewport_1.render_product_path
# SyntheticData singleton interface
sdg_iface = SyntheticData.Get()
# Register node templates in the SyntheticData register
# (a node template is a template for creating a node specified by its type and its connections)
#
# to illustrate we are using the generic omni.syntheticdata.SdTestStageSynchronization node type which supports every stage of the SyntheticData pipeline. When executed it logs the fabric frame number.
#
# register a node template in the simulation stage
# NB : this node template has no connections
if not sdg_iface.is_node_template_registered("TestSyncSim"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION, # node tempalte stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
attributes={"inputs:tag":"0"}), # node template default attribute values (when differs from the default value specified in the .ogn)
template_name="TestSyncSim" # node template name
)
# register a node template in the postrender stage
# NB : this template may be activated for several different renderproducts
if not sdg_iface.is_node_template_registered("TestSyncPost"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.POST_RENDER, # node template stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
# node template connections
[
# connected to a TestSyncSim node (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("TestSyncSim", (), None),
# connected to a LdrColorSD rendervar (the renderVar will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("LdrColorSD"),
# connected to a BoundingBox3DSD rendervar (the renderVar will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("BoundingBox3DSD")
]),
template_name="TestSyncPost" # node template name
)
# register a node template in the postprocess stage
# NB : this template may be activated for several different renderproducts
if not sdg_iface.is_node_template_registered("TestSyncOnDemand"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND, # node template stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
# node template connections
[
# connected to a TestSyncSim node (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("TestSyncSim", (), None),
# connected to a PostProcessDispatch node : the PostProcessDispatch node trigger the execution of its downstream connections for every rendered frame
# (a PostProcessDispatch node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate("PostProcessDispatch")
]
),
template_name="TestSyncOnDemand" # node template name
)
# register a node template in the postprocess stage
# NB : this template may be activated for any combination of renderproduct pairs
if not sdg_iface.is_node_template_registered("TestSyncCross"):
# register an accumulator which trigger once when all its upstream connections have triggered
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND, # node template stage
"omni.graph.action.SyncGate", # node template type
# node template connections
[
# connected to the PostProcessDispatcher for the synchronization value
SyntheticData.NodeConnectionTemplate(
"PostProcessDispatcher",
(),
{"outputs:swhFrameNumber":"inputs:syncValue"}
),
# connected to a TestSyncOnDemand node for the first renderproduct (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate(
"TestSyncOnDemand",
(0,),
{"outputs:exec":"inputs:execIn"}
),
# connected to a TestSyncOnDemand node for the second renderproduct (a TestSyncSim node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate(
"TestSyncOnDemand",
(1,),
{"outputs:exec":"inputs:execIn"}
),
]
),
template_name="TestSyncAccum" # node template name
)
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND, # node template stage
"omni.syntheticdata.SdTestStageSynchronization", # node template type
# node template connections
[
# connected to a TestSyncAccum node (a TestSyncAccum node will be activated when activating this template)
SyntheticData.NodeConnectionTemplate(
"TestSyncAccum",
(0,1),
{
"outputs:execOut":"inputs:exec",
"outputs:syncValue":"inputs:swhFrameNumber"
}
),
]
),
template_name="TestSyncCross" # node template name
)
# Activate the node templates for the renderproducts
# this will create the node (and all their missing dependencies) within the associated graphs
#
# activate the TestSyncPost for the renderpoduct renderpoduct_0
# this will also activate the TestSyncSim node and the LdrColorSD and BoundingBox3DSD renderVars for the renderpoduct renderpoduct_0
# this will set the tag node attribute to "1"
sdg_iface.activate_node_template("TestSyncPost", 0, [render_product_path_0],{"inputs:tag":"1"})
# activate the TestSyncPost for the renderpoduct renderpoduct_1
# this will also activate the LdrColorSD and BoundingBox3DSD renderVars for the renderpoduct renderpoduct_1
# NB TestSyncSim has already been activated
# this will set the tag node attribute to "2"
sdg_iface.activate_node_template("TestSyncPost", 0, [render_product_path_1],{"inputs:tag":"2"})
# activate the TestSyncCross for the renderpoducts [renderproduct_0, renderproduct_1]
# this will also activate :
# - TestSyncAccum for the renderpoducts [renderproduct_0, renderproduct_1]
# - PostProcessDispatch for the renderpoduct renderproduct_0
# - TestSyncOnDemand for the renderproduct renderproduct_0
# - TestSyncOnDemand for the renderproduct renderproduct_1
# - PostProcessDispatch for the renderpoduct renderproduct_1
# this will set the tag node attribute to "5"
sdg_iface.activate_node_template("TestSyncCross", 0, [render_product_path_0,render_product_path_1],{"inputs:tag":"5"})
# Set some specific attributes to nodes that have been automatically activated
# set the tag to the TestSyncOnDemand for renderproduct renderproduct_0
sdg_iface.set_node_attributes("TestSyncOnDemand",{"inputs:tag":"3"},render_product_path_0)
# set the tag to the TestSyncOnDemand for renderproduct renderproduct_1
sdg_iface.set_node_attributes("TestSyncOnDemand",{"inputs:tag":"4"},render_product_path_1)
# setup members
self.render_product_path_0 = render_product_path_0
self.render_product_path_1 = render_product_path_1
self.numLoops = 33
async def run_loop(self):
sdg_iface = SyntheticData.Get()
render_product_path_0 = self.render_product_path_0
render_product_path_1 = self.render_product_path_1
test_attributes_names = ["outputs:swhFrameNumber","outputs:fabricSWHFrameNumber"]
# ensuring that the setup is taken into account
for _ in range(5):
await omni.kit.app.get_app().next_update_async()
for _ in range(self.numLoops):
await omni.kit.app.get_app().next_update_async()
# test the post-render pipeline synchronization
sync_post_attributes = sdg_iface.get_node_attributes(
"TestSyncPost",test_attributes_names,render_product_path_0)
assert sync_post_attributes and all(attr in sync_post_attributes for attr in test_attributes_names)
assert sync_post_attributes["outputs:swhFrameNumber"] == sync_post_attributes["outputs:fabricSWHFrameNumber"]
# test the on-demand pipeline synchronization
sync_ondemand_attributes = sdg_iface.get_node_attributes(
"TestSyncOnDemand",test_attributes_names,render_product_path_1)
assert sync_ondemand_attributes and all(attr in sync_ondemand_attributes for attr in test_attributes_names)
assert sync_ondemand_attributes["outputs:swhFrameNumber"] == sync_ondemand_attributes["outputs:fabricSWHFrameNumber"]
# test the on-demand cross renderproduct synchronization
sync_cross_ondemand_attributes = sdg_iface.get_node_attributes(
"TestSyncCross",test_attributes_names,render_product_path_0)
assert sync_cross_ondemand_attributes and all(attr in sync_cross_ondemand_attributes for attr in test_attributes_names)
assert sync_cross_ondemand_attributes["outputs:swhFrameNumber"] == sync_cross_ondemand_attributes["outputs:fabricSWHFrameNumber"]
async def test_sync_idle(self):
""" Test swh frame synhronization with :
- asyncRendering Off
- waitIdle On
"""
settings = carb.settings.get_settings()
settings.set_bool("/app/asyncRendering",False)
settings.set_int("/app/settings/flatCacheStageFrameHistoryCount",3)
settings.set_bool("/app/renderer/waitIdle",True)
settings.set_bool("/app/hydraEngine/waitIdle",True)
await self.run_loop()
@unittest.skip("DRIVE-3247 : SyntheticData does not support async rendering.")
async def test_sync(self):
""" Test swh frame synhronization with :
- asyncRendering Off
- waitIdle Off
"""
settings = carb.settings.get_settings()
settings.set_bool("/app/asyncRendering",False)
settings.set_int("/app/settings/flatCacheStageFrameHistoryCount",3)
settings.set_bool("/app/renderer/waitIdle",False)
settings.set_bool("/app/hydraEngine/waitIdle",False)
await self.run_loop()
@unittest.skip("DRIVE-3247 : SyntheticData does not support async rendering.")
async def test_async(self):
""" Test swh frame synhronization with :
- asyncRendering On
- waitIdle Off
"""
settings = carb.settings.get_settings()
settings.set_bool("/app/asyncRendering",True)
settings.set_int("/app/settings/flatCacheStageFrameHistoryCount",3)
settings.set_bool("/app/renderer/waitIdle",False)
settings.set_bool("/app/hydraEngine/waitIdle",False)
await self.run_loop()
async def tearDown(self):
# reset to the default params
settings = carb.settings.get_settings()
settings.set_bool("/app/asyncRendering",False)
settings.set_bool("/app/renderer/waitIdle",True)
settings.set_bool("/app/hydraEngine/waitIdle",True)
| 15,648 | Python | 53.908772 | 209 | 0.62647 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_distance_to_image_plane.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
import carb
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestDistanceToImagePlane(omni.kit.test.AsyncTestCase):
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(
self.viewport, syn._syntheticdata.SensorType.DistanceToImagePlane
)
async def test_parsed_empty(self):
""" Test distance-to-image-plane sensor on empty stage.
"""
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_image_plane(self.viewport)
assert np.all(data > 1000)
async def test_parsed_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_image_plane(self.viewport)
assert data.dtype == np.float32
async def test_distances(self):
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_image_plane(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-5)
async def test_distances_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
# Set the rendering mode to be pathtracing
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_image_plane(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-5)
async def test_distances_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
# Set the rendering mode to be pathtracing
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_image_plane(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-5)
# After running each test
async def tearDown(self):
pass
| 5,548 | Python | 38.635714 | 141 | 0.628875 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_semantic_filter.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import unittest
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from omni.syntheticdata import SyntheticData
from ..utils import add_semantics
import numpy as np
# Test the semantic filter
class TestSemanticFilter(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
async def setUp(self):
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
# scene
# /World [belong_to:world]
# /Cube [class:cube]
# /Sphere [class:sphere]
# /Sphere [class:sphere]
# /Capsule [class:capsule]
# /Cube [class:cube]
# /Capsule [class:capsule]
# /Nothing [belong_to:nothing]
world_prim = stage.DefinePrim("/World", "Plane")
add_semantics(world_prim, "world", "belong_to")
world_cube_prim = stage.DefinePrim("/World/Cube", "Cube")
add_semantics(world_cube_prim, "cube", "class")
world_cube_sphere_prim = stage.DefinePrim("/World/Cube/Sphere", "Sphere")
add_semantics(world_cube_sphere_prim, "sphere", "class")
world_sphere_prim = stage.DefinePrim("/World/Sphere", "Sphere")
add_semantics(world_sphere_prim, "sphere", "class")
world_capsule_prim = stage.DefinePrim("/World/Capsule", "Capsule")
add_semantics(world_capsule_prim, "capsule", "class")
cube_prim = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube_prim, "cube", "class")
capsule_prim = stage.DefinePrim("/Capsule", "Capsule")
add_semantics(capsule_prim, "capsule", "class")
nothing_prim = stage.DefinePrim("/Nothing", "Plane")
add_semantics(nothing_prim, "nothing", "belong_to")
self.render_product_path = get_active_viewport().render_product_path
SyntheticData.Get().activate_node_template("SemanticLabelTokenSDExportRawArray", 0, [self.render_product_path])
await omni.kit.app.get_app().next_update_async()
def fetch_semantic_label_tokens(self):
output_names = ["outputs:data","outputs:bufferSize"]
outputs = SyntheticData.Get().get_node_attributes("SemanticLabelTokenSDExportRawArray", output_names, self.render_product_path)
assert outputs
return outputs["outputs:data"].view(np.uint64)
async def check_num_valid_labels(self, expected_num_valid_labels):
wait_iterations = 6
for _ in range(wait_iterations):
await omni.kit.app.get_app().next_update_async()
num_valid_labels = np.count_nonzero(self.fetch_semantic_label_tokens())
assert num_valid_labels == expected_num_valid_labels
async def test_semantic_filter_all(self):
SyntheticData.Get().set_default_semantic_filter("*:*", True)
await self.check_num_valid_labels(8)
async def test_semantic_filter_no_world(self):
SyntheticData.Get().set_default_semantic_filter("!belong_to:world", True)
# /Cube /Capsule /Nothing
await self.check_num_valid_labels(3)
async def test_semantic_filter_all_class_test(self):
SyntheticData.Get().set_default_semantic_filter("class:*", True)
await self.check_num_valid_labels(6)
async def test_semantic_filter_all_class_no_cube_test(self):
SyntheticData.Get().set_default_semantic_filter("class:!cube&*", True)
await self.check_num_valid_labels(3)
async def test_semantic_filter_only_sphere_or_cube_test(self):
SyntheticData.Get().set_default_semantic_filter("class:cube|sphere", True)
await self.check_num_valid_labels(4)
async def test_semantic_filter_sphere_and_cube_test(self):
SyntheticData.Get().set_default_semantic_filter("class:cube&sphere", True)
# /World/Cube/Sphere
await self.check_num_valid_labels(1)
async def test_semantic_filter_world_and_sphere_test(self):
SyntheticData.Get().set_default_semantic_filter("class:sphere,belong_to:world", True)
await self.check_num_valid_labels(2)
async def test_semantic_filter_no_belong_test(self):
SyntheticData.Get().set_default_semantic_filter("belong_to:!*", True)
# /Cube /Capsule
await self.check_num_valid_labels(2)
async def test_semantic_filter_world_or_capsule_test(self):
SyntheticData.Get().set_default_semantic_filter("belong_to:world;class:capsule", True)
await self.check_num_valid_labels(6)
async def test_semantic_filter_belong_to_nohierarchy(self):
SyntheticData.Get().set_default_semantic_filter("belong_to:*", False)
await self.check_num_valid_labels(2)
async def tearDown(self):
SyntheticData.Get().set_default_semantic_filter("*:*")
| 5,054 | Python | 39.766129 | 135 | 0.661061 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_depth_linear.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
import carb
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestDepthLinear(omni.kit.test.AsyncTestCase):
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.DepthLinear)
async def test_parsed_empty(self):
""" Test depth sensor on empty stage.
"""
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth_linear(self.viewport)
assert np.all(data > 1000)
async def test_parsed_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth_linear(self.viewport)
assert data.dtype == np.float32
async def test_distances(self):
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth_linear(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-5)
async def test_distances_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
# Set the rendering mode to be pathtracing
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth_linear(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-5)
async def test_distances_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
# Set the rendering mode to be pathtracing
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth_linear(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-5)
# After running each test
async def tearDown(self):
pass
| 5,485 | Python | 39.043795 | 141 | 0.627894 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_cross_correspondence.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from PIL import Image
from time import time
from pathlib import Path
import carb
import numpy as np
from numpy.lib.arraysetops import unique
import omni.kit.test
from pxr import Gf, UsdGeom
from omni.kit.viewport.utility import get_active_viewport, next_viewport_frame_async, create_viewport_window
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
cameras = ["/World/Cameras/CameraFisheyeLeft", "/World/Cameras/CameraPinhole", "/World/Cameras/CameraFisheyeRight"]
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
# This test has to run last and thus it's prefixed as such to force that:
# - This is because it has to create additional viewports which makes the test
# get stuck if it's not the last one in the OV process session
class ZZHasToRunLast_TestCrossCorrespondence(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
self.output_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "output"
self.StdDevTolerance = 0.1
self.sensorViewport = None
# Before running each test
async def setUp(self):
global cameras
np.random.seed(1234)
# Load the scene
scenePath = os.path.join(FILE_DIR, "../data/scenes/cross_correspondence.usda")
await omni.usd.get_context().open_stage_async(scenePath)
await omni.kit.app.get_app().next_update_async()
# Get the main-viewport as the sensor-viewport
self.sensorViewport = get_active_viewport()
await next_viewport_frame_async(self.sensorViewport)
# Setup viewports
resolution = self.sensorViewport.resolution
viewport_windows = [None] * 2
x_pos, y_pos = 12, 75
for i in range(len(viewport_windows)):
viewport_windows[i] = create_viewport_window(width=resolution[0], height=resolution[1], position_x=x_pos, position_y=y_pos)
viewport_windows[i].width = 500
viewport_windows[i].height = 500
x_pos += 500
# Setup cameras
self.sensorViewport.camera_path = cameras[0]
for i in range(len(viewport_windows)):
viewport_windows[i].viewport_api.camera_path = cameras[i + 1]
# Use default viewport for sensor target as otherwise sensor enablement doesn't work
# also the test will get stuck
# Initialize Sensor
await syn.sensors.create_or_retrieve_sensor_async(
self.sensorViewport, syn._syntheticdata.SensorType.CrossCorrespondence
)
async def test_golden_image(self):
# Render one frame
await syn.sensors.next_sensor_data_async(self.sensorViewport,True)
data = syn.sensors.get_cross_correspondence(self.sensorViewport)
golden_image = np.load(self.golden_image_path / "cross_correspondence.npz")["array"]
# normalize xy (uv offset) to zw channels' value range
# x100 seems like a good number to bring uv offset to ~1
data[:, [0, 1]] *= 100
golden_image[:, [0, 1]] *= 100
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
if std_dev >= self.StdDevTolerance:
if not os.path.isdir(self.output_image_path):
os.mkdir(self.output_image_path)
np.savez_compressed(self.output_image_path / "cross_correspondence.npz", array=data)
golden_image = ((golden_image + 1.0) / 2) * 255
data = ((data + 1.0) / 2) * 255
Image.fromarray(golden_image.astype(np.uint8), "RGBA").save(
self.output_image_path / "cross_correspondence_golden.png"
)
Image.fromarray(data.astype(np.uint8), "RGBA").save(self.output_image_path / "cross_correspondence.png")
self.assertTrue(std_dev < self.StdDevTolerance)
# After running each test
async def tearDown(self):
pass
| 4,577 | Python | 41.785046 | 141 | 0.668779 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_stage_manipulation.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import carb
import random
from pxr import Gf, UsdGeom, UsdLux, Sdf
import unittest
import omni.kit.test
from omni.syntheticdata import SyntheticData, SyntheticDataStage
from omni.kit.viewport.utility import get_active_viewport
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
# Test the ogn node repeatability under stage manipulation
class TestStageManipulation(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
async def setUp(self):
path = os.path.join(FILE_DIR, "../data/scenes/scene_instance_test.usda")
await omni.usd.get_context().open_stage_async(path)
#await omni.usd.get_context().new_stage_async()
viewport = get_active_viewport()
self.render_product_path = viewport.render_product_path
# SyntheticData singleton interface
sdg_iface = SyntheticData.Get()
if not sdg_iface.is_node_template_registered("TestStageManipulationScenarii"):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.SIMULATION,
"omni.syntheticdata.SdTestStageManipulationScenarii",
attributes={"inputs:worldPrimPath":"/World"}
),
template_name="TestStageManipulationScenarii" # node template name
)
render_vars = [
#"SemanticMapSD",
#"SemanticPrimTokenSD",
#"InstanceMapSD",
#"InstancePrimTokenSD",
#"SemanticLabelTokenSD",
#"SemanticLocalTransformSD",
#"SemanticWorldTransformSD",
"SemanticBoundingBox2DExtentTightSD",
#"SemanticBoundingBox2DInfosTightSD",
"SemanticBoundingBox2DExtentLooseSD",
#"SemanticBoundingBox2DInfosLooseSD",
"SemanticBoundingBox3DExtentSD",
"SemanticBoundingBox3DInfosSD"
]
for rv in render_vars:
template_name = "TestRawArray" + rv
if not sdg_iface.is_node_template_registered(template_name):
sdg_iface.register_node_template(
SyntheticData.NodeTemplate(
SyntheticDataStage.ON_DEMAND,
"omni.syntheticdata.SdTestPrintRawArray",
[SyntheticData.NodeConnectionTemplate(rv + "ExportRawArray")]
),
template_name=template_name
)
self.num_loops = 37
async def render_var_test(self, render_var, ref_values, num_references_values, element_type, rand_seed=0, mode="printReferences"):
sdg_iface = SyntheticData.Get()
sdg_iface.activate_node_template("TestStageManipulationScenarii")
sdg_iface.activate_node_template("TestRawArray" + render_var, 0, [self.render_product_path],
{"inputs:elementType": element_type, "inputs:referenceValues": ref_values, "inputs:randomSeed": rand_seed, "inputs:mode": mode,
"inputs:referenceNumUniqueRandomValues": num_references_values})
for _ in range(self.num_loops):
await omni.kit.app.get_app().next_update_async()
sdg_iface.deactivate_node_template("TestRawArray" + render_var, 0, [self.render_product_path])
sdg_iface.deactivate_node_template("TestStageManipulationScenarii")
@unittest.skip("Unimplemented")
async def test_semantic_map(self):
await self.render_var_test("SemanticMapSD", [], "uint16", 2)
async def test_semantic_bbox3d_extent(self):
await self.render_var_test("SemanticBoundingBox3DExtentSD",
[
87.556404, 223.83577, -129.42677, -155.79227, -49.999996, 421.41083, 88.13742, -50.000004, 49.999905, 39.782856, -50.000004, -155.52794, -16.202198,
-50.0, 136.29709, -104.94976, -155.52792, 87.556404, -50.000008, 223.83577, 49.99991, -87.8103, -50.0, -50.00001, 276.29846, 50.000004,
421.41083, -50.0, 60.42457, 223.83574, -129.42676, 312.2204, 277.44424, -50.000004, -37.84166, 87.556404, 188.92877, 136.2971, 50.000004
], 13, "float32", 3, mode="testReferences")
# async def test_semantic_bbox3d_infos(self):
# await self.render_var_test("SemanticBoundingBox3DInfosSD",
# [
# -50.000008, 57.119793, 49.9999, -50.000004, -50.000015, -50.000004, 62.03122,
# -50.000008, -50.000004, -50.000004, -50.0, 50.0, -50.0, 57.119793,
# 9.5100141e-01, -4.7552836e-01, 6.1506079e+02, 1.0000000e+00, -1.0000000e+00, 1.3421423e+03, 4.9999901e+01
# ], 11, "int32", 4, mode="printReferences")
async def test_semantic_bbox2d_extent_loose(self):
await self.render_var_test("SemanticBoundingBox2DExtentLooseSD",
[
733, 479, 532, 507, 460, 611, 763, 309, 17, 827, 789,
698, 554, 947, 789, 581, 534, 156, 582, 323, 825, 298,
562, 959, 595, 299, 117, 445, 572, 31, 622, 609, 228
], 11, "int32", 5, mode="testReferences")
async def test_semantic_bbox2d_extent_tight(self):
await self.render_var_test("SemanticBoundingBox2DExtentTightSD",
[
0.0000000e+00, 5.0700000e+02, 1.1600000e+02, 7.4600000e+02, 5.9500000e+02, 2.1474836e+09, 2.1474836e+09, 2.5300000e+02, 3.6100000e+02, 1.7000000e+01, 0.0000000e+00,
2.1474836e+09, 2.1474836e+09, 2.1474836e+09, 2.1474836e+09, 2.1474836e+09, 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, 2.1474836e+09, 0.0000000e+00, 2.1474836e+09,
0.0000000e+00, 3.1000000e+01, 5.3900000e+02, 2.3600000e+02, 2.1474836e+09, 5.7200000e+02, 8.9200000e+02, 9.0500000e+02, 5.6200000e+02, 5.1300000e+02, 0.0000000e+00
], 11, "int32", 9, mode="testReferences")
async def tearDown(self):
pass
| 6,181 | Python | 48.456 | 177 | 0.621582 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_bbox3d.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import unittest
import uuid
import math
import shutil
import asyncio
from time import time
import carb.tokens
import carb.settings
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Usd, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from .. import utils
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
TMP = carb.tokens.get_tokens_interface().resolve("${temp}")
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestBBox3D(omni.kit.test.AsyncTestCase):
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.BoundingBox3D)
async def test_parsed_empty(self):
""" Test 3D bounding box on empty stage.
"""
bbox3d_data = syn.sensors.get_bounding_box_3d(self.viewport, parsed=True, return_corners=True)
assert not bool(bbox3d_data)
async def test_fields_exist(self):
""" Test the correctness of the output dtype.
"""
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
utils.add_semantics(cube, "cube")
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport, True)
bbox3d_data_raw = syn.sensors.get_bounding_box_3d(self.viewport, parsed=False, return_corners=False)
bbox3d_data_parsed = syn.sensors.get_bounding_box_3d(self.viewport, parsed=True, return_corners=True)
raw_dtype = np.dtype(
[
("instanceId", "<u4"),
("semanticId", "<u4"),
("x_min", "<f4"),
("y_min", "<f4"),
("z_min", "<f4"),
("x_max", "<f4"),
("y_max", "<f4"),
("z_max", "<f4"),
("transform", "<f4", (4, 4)),
]
)
parsed_dtype = np.dtype(
[
("uniqueId", "<i4"),
("name", "O"),
("semanticLabel", "O"),
("metadata", "O"),
("instanceIds", "O"),
("semanticId", "<u4"),
("x_min", "<f4"),
("y_min", "<f4"),
("z_min", "<f4"),
("x_max", "<f4"),
("y_max", "<f4"),
("z_max", "<f4"),
("transform", "<f4", (4, 4)),
("corners", "<f4", (8, 3)),
]
)
assert bbox3d_data_raw.dtype == raw_dtype
assert bbox3d_data_parsed.dtype == parsed_dtype
async def test_parsed_nested_Y_pathtracing(self):
""" Test 3D bounding box with nested semantics and transforms, Y-Up, in pathtracing mode.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
# Create 2 cubes (size=1) under a parent prim
stage = omni.usd.get_context().get_stage()
UsdGeom.SetStageUpAxis(stage, "Y")
parent = stage.DefinePrim("/World/Parent", "Xform")
child1 = stage.DefinePrim("/World/Parent/Child1", "Cube")
child2 = stage.DefinePrim("/World/Parent/Child2", "Cube")
child1.GetAttribute("size").Set(1.0)
child2.GetAttribute("size").Set(1.0)
utils.add_semantics(parent, "parent")
utils.add_semantics(child1, "child1")
utils.add_semantics(child2, "child2")
UsdGeom.Xformable(parent).ClearXformOpOrder()
UsdGeom.Xformable(child1).ClearXformOpOrder()
UsdGeom.Xformable(child2).ClearXformOpOrder()
UsdGeom.Xformable(parent).AddRotateYOp().Set(45)
UsdGeom.Xformable(child1).AddTranslateOp().Set((-0.5, 0.5, 0.0))
UsdGeom.Xformable(child1).AddRotateYOp().Set(45)
UsdGeom.Xformable(child2).AddTranslateOp().Set((0.5, -0.5, 0.0))
await omni.kit.app.get_app().next_update_async()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(self.viewport, parsed=True, return_corners=True)
parent_bbox = [row for row in bbox3d_data if row["name"] == parent.GetPath()][0]
child1_bbox = [row for row in bbox3d_data if row["name"] == child1.GetPath()][0]
child2_bbox = [row for row in bbox3d_data if row["name"] == child2.GetPath()][0]
# Only takes into account child transforms
a = math.cos(math.pi / 4)
parent_bounds = [[-a - 0.5, -1.0, -a], [1.0, 1.0, a]]
child1_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]
child2_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]] # Doesn't take into account transforms
for bbox, bounds in zip([parent_bbox, child1_bbox, child2_bbox], [parent_bounds, child1_bounds, child2_bounds]):
self.assertAlmostEqual(bbox["x_min"], bounds[0][0], places=5)
self.assertAlmostEqual(bbox["y_min"], bounds[0][1], places=5)
self.assertAlmostEqual(bbox["z_min"], bounds[0][2], places=5)
self.assertAlmostEqual(bbox["x_max"], bounds[1][0], places=5)
self.assertAlmostEqual(bbox["y_max"], bounds[1][1], places=5)
self.assertAlmostEqual(bbox["z_max"], bounds[1][2], places=5)
prim = stage.GetPrimAtPath(bbox["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(0.0))
gf_range = Gf.Range3f(*bounds)
gf_corners = np.array([gf_range.GetCorner(i) for i in range(8)])
gf_corners = np.pad(gf_corners, ((0, 0), (0, 1)), constant_values=1.0)
gf_corners = np.dot(gf_corners, tf)[:, :3]
assert np.allclose(bbox["corners"], gf_corners, atol=1e-5)
async def test_parsed_nested_Y_ray_traced_lighting(self):
""" Test 3D bounding box with nested semantics and transforms, Y-Up, in ray traced lighting mode.
"""
# Set the rendering mode to be ray traced lighting.
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
# Create 2 cubes (size=1) under a parent prim
stage = omni.usd.get_context().get_stage()
UsdGeom.SetStageUpAxis(stage, "Y")
parent = stage.DefinePrim("/World/Parent", "Xform")
child1 = stage.DefinePrim("/World/Parent/Child1", "Cube")
child2 = stage.DefinePrim("/World/Parent/Child2", "Cube")
child1.GetAttribute("size").Set(1.0)
child2.GetAttribute("size").Set(1.0)
utils.add_semantics(parent, "parent")
utils.add_semantics(child1, "child1")
utils.add_semantics(child2, "child2")
UsdGeom.Xformable(parent).ClearXformOpOrder()
UsdGeom.Xformable(child1).ClearXformOpOrder()
UsdGeom.Xformable(child2).ClearXformOpOrder()
UsdGeom.Xformable(parent).AddRotateYOp().Set(45)
UsdGeom.Xformable(child1).AddTranslateOp().Set((-0.5, 0.5, 0.0))
UsdGeom.Xformable(child1).AddRotateYOp().Set(45)
UsdGeom.Xformable(child2).AddTranslateOp().Set((0.5, -0.5, 0.0))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(self.viewport, parsed=True, return_corners=True)
parent_bbox = [row for row in bbox3d_data if row["name"] == parent.GetPath()][0]
child1_bbox = [row for row in bbox3d_data if row["name"] == child1.GetPath()][0]
child2_bbox = [row for row in bbox3d_data if row["name"] == child2.GetPath()][0]
# Only takes into account child transforms
a = math.cos(math.pi / 4)
parent_bounds = [[-a - 0.5, -1.0, -a], [1.0, 1.0, a]]
child1_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]
child2_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]] # Doesn't take into account transforms
for bbox, bounds in zip([parent_bbox, child1_bbox, child2_bbox], [parent_bounds, child1_bounds, child2_bounds]):
self.assertAlmostEqual(bbox["x_min"], bounds[0][0], places=5)
self.assertAlmostEqual(bbox["y_min"], bounds[0][1], places=5)
self.assertAlmostEqual(bbox["z_min"], bounds[0][2], places=5)
self.assertAlmostEqual(bbox["x_max"], bounds[1][0], places=5)
self.assertAlmostEqual(bbox["y_max"], bounds[1][1], places=5)
self.assertAlmostEqual(bbox["z_max"], bounds[1][2], places=5)
prim = stage.GetPrimAtPath(bbox["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(0.0))
gf_range = Gf.Range3f(*bounds)
gf_corners = np.array([gf_range.GetCorner(i) for i in range(8)])
gf_corners = np.pad(gf_corners, ((0, 0), (0, 1)), constant_values=1.0)
gf_corners = np.dot(gf_corners, tf)[:, :3]
assert np.allclose(bbox["corners"], gf_corners, atol=1e-5)
async def test_parsed_nested_Y(self):
""" Test 3D bounding box with nested semantics and transforms, Y-Up.
"""
# Create 2 cubes (size=1) under a parent prim
stage = omni.usd.get_context().get_stage()
UsdGeom.SetStageUpAxis(stage, "Y")
parent = stage.DefinePrim("/World/Parent", "Xform")
child1 = stage.DefinePrim("/World/Parent/Child1", "Cube")
child2 = stage.DefinePrim("/World/Parent/Child2", "Cube")
child1.GetAttribute("size").Set(1.0)
child2.GetAttribute("size").Set(1.0)
utils.add_semantics(parent, "parent")
utils.add_semantics(child1, "child1")
utils.add_semantics(child2, "child2")
UsdGeom.Xformable(parent).ClearXformOpOrder()
UsdGeom.Xformable(child1).ClearXformOpOrder()
UsdGeom.Xformable(child2).ClearXformOpOrder()
UsdGeom.Xformable(parent).AddRotateYOp().Set(45)
UsdGeom.Xformable(child1).AddTranslateOp().Set((-0.5, 0.5, 0.0))
UsdGeom.Xformable(child1).AddRotateYOp().Set(45)
UsdGeom.Xformable(child2).AddTranslateOp().Set((0.5, -0.5, 0.0))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(self.viewport, parsed=True, return_corners=True)
parent_bbox = [row for row in bbox3d_data if row["name"] == parent.GetPath()][0]
child1_bbox = [row for row in bbox3d_data if row["name"] == child1.GetPath()][0]
child2_bbox = [row for row in bbox3d_data if row["name"] == child2.GetPath()][0]
# Only takes into account child transforms
a = math.cos(math.pi / 4)
parent_bounds = [[-a - 0.5, -1.0, -a], [1.0, 1.0, a]]
child1_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]
child2_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]] # Doesn't take into account transforms
for bbox, bounds in zip([parent_bbox, child1_bbox, child2_bbox], [parent_bounds, child1_bounds, child2_bounds]):
self.assertAlmostEqual(bbox["x_min"], bounds[0][0], places=5)
self.assertAlmostEqual(bbox["y_min"], bounds[0][1], places=5)
self.assertAlmostEqual(bbox["z_min"], bounds[0][2], places=5)
self.assertAlmostEqual(bbox["x_max"], bounds[1][0], places=5)
self.assertAlmostEqual(bbox["y_max"], bounds[1][1], places=5)
self.assertAlmostEqual(bbox["z_max"], bounds[1][2], places=5)
prim = stage.GetPrimAtPath(bbox["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(0.0))
gf_range = Gf.Range3f(*bounds)
gf_corners = np.array([gf_range.GetCorner(i) for i in range(8)])
gf_corners = np.pad(gf_corners, ((0, 0), (0, 1)), constant_values=1.0)
gf_corners = np.dot(gf_corners, tf)[:, :3]
assert np.allclose(bbox["corners"], gf_corners, atol=1e-5)
async def test_parsed_nested_Z(self):
""" Test 3D bounding box with nested semantics and transforms, Z-Up.
"""
# Create 2 cubes (size=1) under a parent prim
stage = omni.usd.get_context().get_stage()
UsdGeom.SetStageUpAxis(stage, "Z")
parent = stage.DefinePrim("/World/Parent", "Xform")
child1 = stage.DefinePrim("/World/Parent/Child1", "Cube")
child2 = stage.DefinePrim("/World/Parent/Child2", "Cube")
child1.GetAttribute("size").Set(1.0)
child2.GetAttribute("size").Set(1.0)
utils.add_semantics(parent, "parent")
utils.add_semantics(child1, "child1")
utils.add_semantics(child2, "child2")
UsdGeom.Xformable(parent).ClearXformOpOrder()
UsdGeom.Xformable(child1).ClearXformOpOrder()
UsdGeom.Xformable(child2).ClearXformOpOrder()
UsdGeom.Xformable(parent).AddRotateYOp().Set(45)
UsdGeom.Xformable(child1).AddTranslateOp().Set((-0.5, 0.5, 0.0))
UsdGeom.Xformable(child1).AddRotateYOp().Set(45)
UsdGeom.Xformable(child2).AddTranslateOp().Set((0.5, -0.5, 0.0))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(self.viewport, parsed=True, return_corners=True)
parent_bbox = [row for row in bbox3d_data if row["name"] == parent.GetPath()][0]
child1_bbox = [row for row in bbox3d_data if row["name"] == child1.GetPath()][0]
child2_bbox = [row for row in bbox3d_data if row["name"] == child2.GetPath()][0]
# Only takes into account child transforms
a = math.cos(math.pi / 4)
parent_bounds = [[-a - 0.5, -1.0, -a], [1.0, 1.0, a]]
child1_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]
child2_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]] # Doesn't take into account transforms
for bbox, bounds in zip([parent_bbox, child1_bbox, child2_bbox], [parent_bounds, child1_bounds, child2_bounds]):
self.assertAlmostEqual(bbox["x_min"], bounds[0][0], places=5)
self.assertAlmostEqual(bbox["y_min"], bounds[0][1], places=5)
self.assertAlmostEqual(bbox["z_min"], bounds[0][2], places=5)
self.assertAlmostEqual(bbox["x_max"], bounds[1][0], places=5)
self.assertAlmostEqual(bbox["y_max"], bounds[1][1], places=5)
self.assertAlmostEqual(bbox["z_max"], bounds[1][2], places=5)
prim = stage.GetPrimAtPath(bbox["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(0.0))
gf_range = Gf.Range3f(*bounds)
gf_corners = np.array([gf_range.GetCorner(i) for i in range(8)])
gf_corners = np.pad(gf_corners, ((0, 0), (0, 1)), constant_values=1.0)
gf_corners = np.dot(gf_corners, tf)[:, :3]
assert np.allclose(bbox["corners"], gf_corners, atol=1e-5)
@unittest.skip("OM-45008")
async def test_camera_frame_simple_ftheta(self):
""" Test 3D bounding box in a simple scene under ftheta camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
# TEST SIMPLE SCENE
cube = stage.DefinePrim("/Cube", "Cube")
cube.GetAttribute("size").Set(2.0)
UsdGeom.Xformable(cube).AddTranslateOp().Set((10.0, 1.0, 2))
utils.add_semantics(cube, "cube")
camera = stage.DefinePrim("/Camera", "Camera")
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
UsdGeom.Xformable(camera).AddTranslateOp().Set((10.0, 0.0, 0.0))
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=True
)
# TODO: find the correct value of distorted result.
# The f theta will distort the result.
extents = Gf.Range3d([-1.0, 0, 1], [1.0, 2.0, 3])
corners = np.array([[extents.GetCorner(i) for i in range(8)]])
assert not np.allclose(bbox3d_data[0]["corners"], corners)
@unittest.skip("OM-45008")
async def test_camera_frame_simple_spherical(self):
""" Test 3D bounding box in a simple scene under fisheye spherical camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
# TEST SIMPLE SCENE
cube = stage.DefinePrim("/Cube", "Cube")
cube.GetAttribute("size").Set(2.0)
UsdGeom.Xformable(cube).AddTranslateOp().Set((10.0, 1.0, 2))
utils.add_semantics(cube, "cube")
camera = stage.DefinePrim("/Camera", "Camera")
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyeSpherical")
UsdGeom.Xformable(camera).AddTranslateOp().Set((10.0, 0.0, 0.0))
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=True
)
# TODO: find the correct value of distorted result.
# The spherical camera will distort the result.
extents = Gf.Range3d([-1.0, 0, 1], [1.0, 2.0, 3])
corners = np.array([[extents.GetCorner(i) for i in range(8)]])
assert not np.allclose(bbox3d_data[0]["corners"], corners)
async def test_camera_frame_simple(self):
""" Test 3D bounding box in a simple scene.
"""
stage = omni.usd.get_context().get_stage()
# TEST SIMPLE SCENE
cube = stage.DefinePrim("/Cube", "Cube")
cube.GetAttribute("size").Set(2.0)
UsdGeom.Xformable(cube).AddTranslateOp().Set((10.0, 0.0, 10.0))
utils.add_semantics(cube, "cube")
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((10.0, 0.0, 0.0))
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=True
)
extents = Gf.Range3d([-1.0, -1.0, 9.0], [1.0, 1.0, 11.0])
corners = np.array([[extents.GetCorner(i) for i in range(8)]])
assert np.allclose(bbox3d_data[0]["corners"], corners)
tf = np.eye(4)
tf[3, 2] = 10.0
assert np.allclose(bbox3d_data[0]["transform"], tf)
async def test_camera_frame_reference(self):
""" Test 3D bounding box in a simple scene.
"""
ref_path = os.path.join(TMP, f"ref_stage{uuid.uuid1()}.usd")
ref_stage = Usd.Stage.CreateNew(ref_path)
world = ref_stage.DefinePrim("/World", "Xform")
world_tf = utils.get_random_transform()
UsdGeom.Xformable(world).AddTransformOp().Set(world_tf)
cube = ref_stage.DefinePrim("/World/Cube", "Cube")
cube.GetAttribute("size").Set(2.0)
cube_tf = Gf.Matrix4d().SetTranslateOnly((10.0, 0.0, 10.0))
UsdGeom.Xformable(cube).AddTransformOp().Set(cube_tf)
utils.add_semantics(cube, "cube")
camera = ref_stage.DefinePrim("/World/Camera", "Camera")
camera_tf = cube_tf
UsdGeom.Xformable(camera).AddTransformOp().Set(camera_tf)
ref_stage.Save()
# omni.usd.get_context().new_stage()
# await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
rig = stage.DefinePrim("/Rig", "Xform")
rig_tf = utils.get_random_transform()
UsdGeom.Xformable(rig).AddTransformOp().Set(rig_tf)
ref = stage.DefinePrim("/Rig/Ref")
ref.GetReferences().AddReference(ref_path, "/World")
self.viewport.camera_path = "/Rig/Ref/Camera"
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data_world = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=False
)
bbox3d_data_camera = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=True
)
extents = Gf.Range3d([-1.0, -1.0, -1.0], [1.0, 1.0, 1.0])
corners = np.array([[extents.GetCorner(i) for i in range(8)]])
assert np.allclose(bbox3d_data_camera[0]["corners"], corners)
combined_tf = np.matmul(cube_tf, np.matmul(world_tf, rig_tf))
corners_tf = np.matmul(np.pad(corners.reshape(-1, 3), ((0, 0), (0, 1)), constant_values=1), combined_tf)
corners_tf = corners_tf[:, :3].reshape(-1, 8, 3)
assert np.allclose(bbox3d_data_world[0]["corners"], corners_tf)
# tf = np.eye(4)
# tf[3, 2] = 10.0
assert np.allclose(bbox3d_data_world[0]["transform"], combined_tf)
pt_camera_min = [bbox3d_data_camera[0][f"{a}_min"] for a in ["x", "y", "z"]]
pt_camera_min = np.array([*pt_camera_min, 1.0])
pt_camera_max = [bbox3d_data_camera[0][f"{a}_max"] for a in ["x", "y", "z"]]
pt_camera_max = np.array([*pt_camera_max, 1.0])
assert np.allclose(np.matmul(pt_camera_min, bbox3d_data_camera[0]["transform"])[:3], corners[0, 0])
assert np.allclose(np.matmul(pt_camera_max, bbox3d_data_camera[0]["transform"])[:3], corners[0, 7])
async def test_camera_frame_Y(self):
# TEST NESTED TRANSFORMS, UP AXIS
# Create 2 cubes (size=1) under a parent prim
stage = omni.usd.get_context().get_stage()
UsdGeom.SetStageUpAxis(stage, "Y")
parent = stage.DefinePrim("/World/Parent", "Xform")
child1 = stage.DefinePrim("/World/Parent/Child1", "Cube")
child2 = stage.DefinePrim("/World/Parent/Child2", "Cube")
camera = stage.DefinePrim("/World/Camera", "Camera")
child1.GetAttribute("size").Set(1.0)
child2.GetAttribute("size").Set(1.0)
utils.add_semantics(parent, "parent")
utils.add_semantics(child1, "child1")
utils.add_semantics(child2, "child2")
UsdGeom.Xformable(parent).ClearXformOpOrder()
UsdGeom.Xformable(child1).ClearXformOpOrder()
UsdGeom.Xformable(child2).ClearXformOpOrder()
UsdGeom.Xformable(camera).ClearXformOpOrder()
UsdGeom.Xformable(parent).AddRotateYOp().Set(45)
UsdGeom.Xformable(child1).AddTranslateOp().Set((-0.5, 0.5, 0.0))
UsdGeom.Xformable(child1).AddRotateYOp().Set(45)
UsdGeom.Xformable(child2).AddTranslateOp().Set((0.5, -0.5, 0.0))
# Move camera with random transform
camera_tf = utils.get_random_transform()
UsdGeom.Xformable(camera).AddTransformOp().Set(Gf.Matrix4d(camera_tf))
camera_tf_inv = np.linalg.inv(camera_tf)
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=True
)
parent_bbox = [row for row in bbox3d_data if row["name"] == parent.GetPath()][0]
child1_bbox = [row for row in bbox3d_data if row["name"] == child1.GetPath()][0]
child2_bbox = [row for row in bbox3d_data if row["name"] == child2.GetPath()][0]
# Only takes into account child transforms
a = math.cos(math.pi / 4)
parent_bounds = [[-a - 0.5, -1.0, -a], [1.0, 1.0, a]]
child1_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]
child2_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]] # Doesn't take into account transforms
for bbox, bounds in zip([parent_bbox, child1_bbox, child2_bbox], [parent_bounds, child1_bounds, child2_bounds]):
self.assertAlmostEqual(bbox["x_min"], bounds[0][0], places=5)
self.assertAlmostEqual(bbox["y_min"], bounds[0][1], places=5)
self.assertAlmostEqual(bbox["z_min"], bounds[0][2], places=5)
self.assertAlmostEqual(bbox["x_max"], bounds[1][0], places=5)
self.assertAlmostEqual(bbox["y_max"], bounds[1][1], places=5)
self.assertAlmostEqual(bbox["z_max"], bounds[1][2], places=5)
prim = stage.GetPrimAtPath(bbox["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(0.0))
gf_range = Gf.Range3f(*bounds)
gf_corners = np.array([gf_range.GetCorner(i) for i in range(8)])
gf_corners = np.pad(gf_corners, ((0, 0), (0, 1)), constant_values=1.0)
gf_corners = np.dot(gf_corners, tf)
gf_corners = np.dot(gf_corners, camera_tf_inv)[:, :3]
assert np.allclose(bbox["corners"], gf_corners, atol=1e-5)
async def test_camera_frame_Z(self):
# TEST NESTED TRANSFORMS, UP AXIS
# Create 2 cubes (size=1) under a parent prim
stage = omni.usd.get_context().get_stage()
UsdGeom.SetStageUpAxis(stage, "Z")
parent = stage.DefinePrim("/World/Parent", "Xform")
child1 = stage.DefinePrim("/World/Parent/Child1", "Cube")
child2 = stage.DefinePrim("/World/Parent/Child2", "Cube")
camera = stage.DefinePrim("/World/Camera", "Camera")
child1.GetAttribute("size").Set(1.0)
child2.GetAttribute("size").Set(1.0)
utils.add_semantics(parent, "parent")
utils.add_semantics(child1, "child1")
utils.add_semantics(child2, "child2")
UsdGeom.Xformable(parent).ClearXformOpOrder()
UsdGeom.Xformable(child1).ClearXformOpOrder()
UsdGeom.Xformable(child2).ClearXformOpOrder()
UsdGeom.Xformable(camera).ClearXformOpOrder()
UsdGeom.Xformable(parent).AddRotateYOp().Set(45)
UsdGeom.Xformable(child1).AddTranslateOp().Set((-0.5, 0.5, 0.0))
UsdGeom.Xformable(child1).AddRotateYOp().Set(45)
UsdGeom.Xformable(child2).AddTranslateOp().Set((0.5, -0.5, 0.0))
# Move camera with random transform
camera_tf = np.eye(4)
camera_tf[:3, :3] = Gf.Matrix3d(Gf.Rotation(np.random.rand(3).tolist(), np.random.rand(3).tolist()))
camera_tf[3, :3] = np.random.rand(1, 3)
UsdGeom.Xformable(camera).AddTransformOp().Set(Gf.Matrix4d(camera_tf))
camera_tf_inv = np.linalg.inv(camera_tf)
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox3d_data = syn.sensors.get_bounding_box_3d(
self.viewport, parsed=True, return_corners=True, camera_frame=True
)
parent_bbox = [row for row in bbox3d_data if row["name"] == parent.GetPath()][0]
child1_bbox = [row for row in bbox3d_data if row["name"] == child1.GetPath()][0]
child2_bbox = [row for row in bbox3d_data if row["name"] == child2.GetPath()][0]
# Only takes into account child transforms
a = math.cos(math.pi / 4)
parent_bounds = [[-a - 0.5, -1.0, -a], [1.0, 1.0, a]]
child1_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]]
child2_bounds = [[-0.5, -0.5, -0.5], [0.5, 0.5, 0.5]] # Doesn't take into account transforms
for bbox, bounds in zip([parent_bbox, child1_bbox, child2_bbox], [parent_bounds, child1_bounds, child2_bounds]):
self.assertAlmostEqual(bbox["x_min"], bounds[0][0], places=5)
self.assertAlmostEqual(bbox["y_min"], bounds[0][1], places=5)
self.assertAlmostEqual(bbox["z_min"], bounds[0][2], places=5)
self.assertAlmostEqual(bbox["x_max"], bounds[1][0], places=5)
self.assertAlmostEqual(bbox["y_max"], bounds[1][1], places=5)
self.assertAlmostEqual(bbox["z_max"], bounds[1][2], places=5)
prim = stage.GetPrimAtPath(bbox["name"])
tf = np.array(UsdGeom.Imageable(prim).ComputeLocalToWorldTransform(0.0))
gf_range = Gf.Range3f(*bounds)
gf_corners = np.array([gf_range.GetCorner(i) for i in range(8)])
gf_corners = np.pad(gf_corners, ((0, 0), (0, 1)), constant_values=1.0)
gf_corners = np.dot(gf_corners, tf)
gf_corners = np.dot(gf_corners, camera_tf_inv)[:, :3]
assert np.allclose(bbox["corners"], gf_corners, atol=1e-5)
@unittest.skip("OM-46398")
async def test_bbox_3d_scene_instance(self):
""" Test sensor on scene instance.
"""
path = os.path.join(FILE_DIR, "../data/scenes/scene_instance_test.usda")
await omni.usd.get_context().open_stage_async(path)
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_bounding_box_3d_(self.viewport)
# should be 3 prims in the scene
# TODO: add more complicated test
assert len(data) == 3
# After running each test
async def tearDown(self):
pass
| 30,376 | Python | 46.169255 | 141 | 0.604655 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_depth.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
import carb
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestDepth(omni.kit.test.AsyncTestCase):
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.Depth)
async def test_parsed_empty(self):
""" Test depth sensor on empty stage.
"""
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth(self.viewport)
assert data.sum() == 0
async def test_parsed_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth(self.viewport)
assert data.dtype == np.float32
async def test_distances(self):
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth(self.viewport)
assert np.isclose(data.min(), 0, atol=1e-5)
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.max(), 1 / (n - 1), atol=1e-5)
async def test_distances_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
# Set the rendering mode to be pathtracing
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth(self.viewport)
assert np.isclose(data.min(), 0, atol=1e-5)
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.max(), 1 / (n - 1), atol=1e-5)
async def test_distances_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
# Set the rendering mode to be pathtracing
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth(self.viewport)
assert np.isclose(data.min(), 0, atol=1e-5)
# The front of the cube is 1 ahead of its center position
assert np.isclose(data.max(), 1 / (n - 1), atol=1e-5)
async def test_ftheta_camera(self):
""" Test the functionality of the sensor under f-theta camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
# Add a cube at the centre of the scene
cube_prim = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube_prim, "cube")
cube = UsdGeom.Cube(cube_prim)
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_depth(self.viewport)
await omni.kit.app.get_app().next_update_async()
# Centre of the data should be half of the cube edge's length, adjusted to correct scale.
edge_length = cube.GetSizeAttr().Get()
assert np.isclose(1 / (edge_length - 1), data.max(), atol=1e-3)
assert np.isclose(1 / (np.sqrt(((edge_length) ** 2)*2) - 1), data[data > 0].min(), atol=1e-1)
# After running each test
async def tearDown(self):
pass
| 7,003 | Python | 39.252873 | 141 | 0.625875 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_semantic_seg.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
from pathlib import Path
import carb
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
import unittest
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestSemanticSeg(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
await syn.sensors.initialize_async(
self.viewport,
[
syn._syntheticdata.SensorType.SemanticSegmentation,
syn._syntheticdata.SensorType.InstanceSegmentation
]
)
async def test_empty(self):
""" Test semantic segmentation on empty stage.
"""
data = syn.sensors.get_semantic_segmentation(self.viewport)
assert data.sum() == 0
async def test_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
assert data.dtype == np.uint32
async def test_cube(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
# np.savez_compressed(self.golden_image_path / 'semantic_seg_cube.npz', array=data)
golden_image = np.load(self.golden_image_path / "semantic_seg_cube.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 0.1
async def test_cube_sphere(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
sphere_prim = stage.DefinePrim("/Sphere", "Sphere")
UsdGeom.XformCommonAPI(sphere_prim).SetTranslate((300, 0, 0))
add_semantics(sphere_prim, "sphere")
sphere = UsdGeom.Sphere(sphere_prim)
sphere.GetRadiusAttr().Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_instance_segmentation(self.viewport)
# np.savez_compressed(self.golden_image_path / 'instance_seg_cube.npz', array=data)
assert len(data) != 0
async def test_cube_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
golden_image = np.load(self.golden_image_path / "semantic_seg_cube.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 0.1
async def test_cube_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
golden_image = np.load(self.golden_image_path / "semantic_seg_cube.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 0.1
async def test_cube_ftheta(self):
""" Basic funtionality test of the sensor under f theta camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await omni.kit.app.get_app().next_update_async()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((100, 100, 100))
self.viewport.camera_path = camera.GetPath()
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
# np.savez_compressed(self.golden_image_path / 'semantic_seg_cube_ftheta.npz', array=data)
golden_image = np.load(self.golden_image_path / "semantic_seg_cube_ftheta.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 0.1
async def test_cube_spherical(self):
""" Basic funtionality test of the sensor under spherical camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await omni.kit.app.get_app().next_update_async()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be spherical fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyeSpherical")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((100, 100, 100))
self.viewport.camera_path = camera.GetPath()
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
# np.savez_compressed(self.golden_image_path / 'semantic_seg_cube_spherical.npz', array=data)
golden_image = np.load(self.golden_image_path / "semantic_seg_cube_spherical.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 0.1
@unittest.skip("OM-46393")
async def test_geom_subset(self):
""" Test sensor on GeomSubset.
"""
path = os.path.join(FILE_DIR, "../data/scenes/streetlamp_03_golden.usd")
await omni.usd.get_context().open_stage_async(path)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
assert len(data) != 0
@unittest.skip("OM-46394")
async def test_sem_seg_scene_instance(self):
""" Test sensor on scene instance.
"""
path = os.path.join(FILE_DIR, "../data/scenes/scene_instance_test.usda")
await omni.usd.get_context().open_stage_async(path)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_semantic_segmentation(self.viewport)
# TODO add more complicated test
assert len(data) != 0
# After running each test
async def tearDown(self):
pass
| 9,115 | Python | 39.878924 | 141 | 0.64531 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_bbox2d_tight.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
import unittest
import carb
import numpy as np
import omni.kit.test
from pxr import Gf, UsdGeom
from omni.kit.viewport.utility import get_active_viewport
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestBBox2DTight(omni.kit.test.AsyncTestCase):
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(
self.viewport, syn._syntheticdata.SensorType.BoundingBox2DTight
)
async def test_parsed_empty(self):
""" Test 2D bounding box on empty stage.
"""
bbox2d_data = syn.sensors.get_bounding_box_2d_tight(self.viewport)
assert not bool(bbox2d_data)
async def test_fields_exist(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox2d_data = syn.sensors.get_bounding_box_2d_tight(self.viewport)
valid_dtype = [
("uniqueId", "<i4"),
("name", "O"),
("semanticLabel", "O"),
("metadata", "O"),
("instanceIds", "O"),
("semanticId", "<u4"),
("x_min", "<i4"),
("y_min", "<i4"),
("x_max", "<i4"),
("y_max", "<i4"),
]
assert bbox2d_data.dtype == np.dtype(valid_dtype)
async def test_cube(self):
""" Basic test for the sensor.
"""
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -10))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox2d_data = syn.sensors.get_bounding_box_2d_tight(self.viewport)
assert bbox2d_data[0]
x_min, y_min, x_max, y_max = bbox2d_data[0][6], bbox2d_data[0][7], bbox2d_data[0][8], bbox2d_data[0][9]
assert x_min == 301
assert y_min == 21
assert x_max == 978
assert y_max == 698
@unittest.skip("OM-46398")
async def test_bbox_2d_tight_scene_instance(self):
""" Test sensor on scene instance.
"""
settings = carb.settings.get_settings()
if settings.get("/rtx/hydra/enableSemanticSchema"):
path = os.path.join(FILE_DIR, "../data/scenes/scene_instance_test.usda")
await omni.usd.get_context().open_stage_async(path)
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_bounding_box_2d_tight(self.viewport)
# should be 3 prims in the scene.
# TODO: Add more complicated test
assert len(data) == 3
async def test_cube_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -10))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox2d_data = syn.sensors.get_bounding_box_2d_tight(self.viewport)
x_min, y_min, x_max, y_max = bbox2d_data[0][6], bbox2d_data[0][7], bbox2d_data[0][8], bbox2d_data[0][9]
assert x_min == 301
assert y_min == 21
assert x_max == 978
assert y_max == 698
async def test_cube_ray_traced_lighting(self):
""" Basic test for the sensor, but in ray traced lighting mode.
"""
# Set the rendering mode to be ray traced lighting.
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -10))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
bbox2d_data = syn.sensors.get_bounding_box_2d_tight(self.viewport)
x_min, y_min, x_max, y_max = bbox2d_data[0][6], bbox2d_data[0][7], bbox2d_data[0][8], bbox2d_data[0][9]
assert x_min == 301
assert y_min == 21
assert x_max == 978
assert y_max == 698
# After running each test
async def tearDown(self):
pass
| 6,495 | Python | 35.088889 | 141 | 0.610162 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_distance_to_camera.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
from time import time
from pathlib import Path
import carb
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestDistanceToCamera(omni.kit.test.AsyncTestCase):
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.DistanceToCamera)
async def test_parsed_empty(self):
""" Test distance-to-camera sensor on empty stage.
"""
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
assert np.all(data > 1000)
async def test_parsed_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
assert data.dtype == np.float32
async def test_distances(self):
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
# TODO get a more precise calculation of eye distance
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-1)
async def test_distances_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
# Set the rendering mode to be pathtracing
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
# TODO get a more precise calculation of eye distance
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-1)
async def test_distances_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
# Set the rendering mode to be pathtracing
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
for n in range(10, 100, 10):
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
# n = 5
UsdGeom.XformCommonAPI(cube).SetTranslate((0, 0, -n))
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
assert data.max() > 1000
# The front of the cube is 1 ahead of its center position
# TODO get a more precise calculation of eye distance
assert np.isclose(data.min(), (n - 1) / 100, atol=1e-1)
async def test_ftheta_camera(self):
""" Test the functionality of the sensor under f-theta camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
# Add a cube at the centre of the scene
cube_prim = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube_prim, "cube")
cube = UsdGeom.Cube(cube_prim)
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
await omni.kit.app.get_app().next_update_async()
# Centre of the data should be half of the cube edge's length, adjusted to correct scale.
edge_length = (cube.GetSizeAttr().Get() - 1) / 100
# The max should be sqrt(((edge_length / 2) ** 2) * 2), which a pinhole camera won't see.
assert np.isclose(np.sqrt(((edge_length / 2) ** 2)*2), data[data != np.inf].max(), atol=1e-3)
async def test_spherical_camera(self):
""" Test the functionality of the sensor under fisheye spherical camera.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be spherical camera
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyeSpherical")
# Set the Camera at the centre of the stage.
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
sphere_prim = stage.DefinePrim("/Sphere", "Sphere")
add_semantics(sphere_prim, "sphere")
sphere = UsdGeom.Sphere(sphere_prim)
sphere.GetRadiusAttr().Set(20)
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_distance_to_camera(self.viewport)
# np.savez_compressed(self.golden_image_path / 'distance_to_camera_spherical.npz', array=data)
golden_image = np.load(self.golden_image_path / "distance_to_camera_spherical.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
# After running each test
async def tearDown(self):
pass
| 8,962 | Python | 40.688372 | 141 | 0.632113 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_normals.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
from pathlib import Path
import carb
import numpy as np
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Sdf
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestNormals(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
# Before running each test
async def setUp(self):
np.random.seed(1234)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.Normal)
async def test_parsed_empty(self):
""" Test normals sensor on empty stage.
"""
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
assert np.allclose(data, 0, 1e-3)
async def test_parsed_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
assert data.dtype == np.float32
async def test_neg_z(self):
""" Test that negative z faces are distinct from background
"""
stage = omni.usd.get_context().get_stage()
camera = stage.DefinePrim("/Camera", "Camera")
UsdGeom.Xformable(camera).AddRotateYOp().Set(180)
UsdGeom.Xformable(camera).AddTranslateOp().Set((0.0, 0.0, 20.0))
self.viewport.camera_path = camera.GetPath()
await omni.kit.app.get_app().next_update_async()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
assert len(np.unique(data)) == 2
async def test_rotated_cube(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
# np.savez_compressed(self.golden_image_path / 'normals_cube.npz', array=data)
golden_image = np.load(self.golden_image_path / "normals_cube.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
async def test_rotated_cube_pathtracing(self):
""" Basic funtionality test of the sensor, but in path tracing mode.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
# np.savez_compressed(self.golden_image_path / 'normals_cube.npz', array=data)
golden_image = np.load(self.golden_image_path / "normals_cube.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
async def test_rotated_cube_ray_traced_lighting(self):
""" Basic funtionality test of the sensor, but in ray traced lighting.
"""
# Set the rendering mode to be ray traced lighting.
settings_interface = carb.settings.get_settings()
settings_interface.set_string("/rtx/rendermode", "RayTracedLighting")
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
# np.savez_compressed(self.golden_image_path / 'normals_cube.npz', array=data)
golden_image = np.load(self.golden_image_path / "normals_cube.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
async def test_rotated_cube_ftheta(self):
""" Basic funtionality test of the sensor in f theta camera.
"""
# Set the mode to path traced for f theta camera.
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
await omni.kit.app.get_app().next_update_async()
# Setting up camera.
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((200, 200, 200))
self.viewport.camera_path = camera.GetPath()
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
# np.savez_compressed(self.golden_image_path / 'normals_cube_ftheta.npz', array=data)
golden_image = np.load(self.golden_image_path / "normals_cube_ftheta.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
async def test_rotated_cube_spherical(self):
""" Basic funtionality test of the sensor in fisheye spherical camera.
"""
# Set the mode to path traced.
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
# Setting up camera.
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be polynomial fish eye camera.
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyeSpherical")
# Set the Camera's position
UsdGeom.Xformable(camera).AddTranslateOp().Set((200, 200, 200))
self.viewport.camera_path = camera.GetPath()
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_normals(self.viewport)
# np.savez_compressed(self.golden_image_path / 'normals_cube_spherical.npz', array=data)
golden_image = np.load(self.golden_image_path / "normals_cube_spherical.npz")["array"]
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
# After running each test
async def tearDown(self):
pass
| 8,401 | Python | 40.800995 | 141 | 0.653256 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_rgb.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import os
import math
import asyncio
from time import time
from pathlib import Path
import unittest
from PIL import Image
import carb
import numpy as np
from numpy.lib.arraysetops import unique
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import Gf, UsdGeom, Sdf, UsdLux
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
FILE_DIR = os.path.dirname(os.path.realpath(__file__))
TIMEOUT = 200
# Having a test class derived from omni.kit.test.AsyncTestCase declared on the root of module will make it auto-discoverable by omni.kit.test
class TestRGB(omni.kit.test.AsyncTestCase):
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
self.golden_image_path = Path(os.path.dirname(os.path.abspath(__file__))) / ".." / "data" / "golden"
# Before running each test
async def setUp(self):
np.random.seed(1234)
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
# Setup viewport
self.viewport = get_active_viewport()
# Initialize Sensor
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
await omni.kit.app.get_app().next_update_async()
await syn.sensors.create_or_retrieve_sensor_async(self.viewport, syn._syntheticdata.SensorType.Rgb)
async def test_empty(self):
""" Test RGB sensor on empty stage.
"""
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_rgb(self.viewport)
std_dev = np.sqrt(np.square(data - np.zeros_like(data)).astype(float).mean())
assert std_dev < 2
async def test_cube(self):
""" Test RGB sensor on stage with cube.
"""
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
cube.GetAttribute("primvars:displayColor").Set([(0, 0, 1)])
await omni.kit.app.get_app().next_update_async()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_rgb(self.viewport)
golden_image = np.asarray(Image.open(str(self.golden_image_path / "rgb_cube.png")))
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
async def test_dtype(self):
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_rgb(self.viewport)
assert data.dtype == np.uint8
@unittest.skip("OM-44741")
async def test_cube_polynomial(self):
""" Test RGB sensor on stage with cube.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
cube.GetAttribute("primvars:displayColor").Set([(0, 0, 1)])
await omni.kit.app.get_app().next_update_async()
# TODO: Add a light
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be spherical camera
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyePolynomial")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 200))
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_rgb(self.viewport)
# image = Image.fromarray(data)
# image.save(str(self.golden_image_path / "rgb_cube_ftheta.png"))
golden_image = np.asarray(Image.open(str(self.golden_image_path / "rgb_cube_ftheta.png")))
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
@unittest.skip("OM-44741")
async def test_cube_spherical(self):
""" Test RGB sensor on stage with cube.
"""
settings = carb.settings.get_settings()
settings.set_string("/rtx/rendermode", "PathTracing")
settings.set_int("/rtx/pathtracing/spp", 32)
settings.set_int("/persistent/app/viewport/displayOptions", 0)
stage = omni.usd.get_context().get_stage()
cube = stage.DefinePrim("/Cube", "Cube")
add_semantics(cube, "cube")
cube.GetAttribute("size").Set(100)
cube.GetAttribute("primvars:displayColor").Set([(0, 0, 1)])
await omni.kit.app.get_app().next_update_async()
# TODO: Add a light
camera = stage.DefinePrim("/Camera", "Camera")
# Set the camera to be spherical camera
camera.CreateAttribute("cameraProjectionType", Sdf.ValueTypeNames.Token).Set("fisheyeSpherical")
UsdGeom.Xformable(camera).AddTranslateOp().Set((0, 0, 200))
self.viewport.camera_path = camera.GetPath()
# Render one frame
await syn.sensors.next_sensor_data_async(self.viewport,True)
data = syn.sensors.get_rgb(self.viewport)
# image = Image.fromarray(data)
# image.save(str(self.golden_image_path / "rgb_cube_spherical.png"))
golden_image = np.asarray(Image.open(str(self.golden_image_path / "rgb_cube_spherical.png")))
std_dev = np.sqrt(np.square(data - golden_image).astype(float).mean())
assert std_dev < 2
# After running each test
async def tearDown(self):
pass
| 6,388 | Python | 38.196319 | 141 | 0.648716 |
eliabntt/GRADE-RR/isaac_internals/kit/extscore/omni.syntheticdata/omni/syntheticdata/tests/sensors/test_rendervar_buff_host_ptr.py | # NOTE:
# omni.kit.test - std python's unittest module with additional wrapping to add suport for async/await tests
# For most things refer to unittest docs: https://docs.python.org/3/library/unittest.html
import unittest
import numpy as np
import ctypes
import omni.kit.test
from omni.kit.viewport.utility import get_active_viewport
from pxr import UsdGeom, UsdLux
# Import extension python module we are testing with absolute import path, as if we are external user (other extension)
import omni.syntheticdata as syn
from ..utils import add_semantics
# Test the SyntheticData following nodes :
# - SdPostRenderVarTextureToBuffer : node to convert a texture device rendervar into a buffer device rendervar
# - SdPostRenderVarToHost : node to readback a device rendervar into a host rendervar
# - SdRenderVarPtr : node to expose in the action graph, raw device / host pointers on the renderVars
#
# the tests consists in pulling the ptr data and comparing it with the data ouputed by :
# - SdRenderVarToRawArray
#
class TestRenderVarBuffHostPtr(omni.kit.test.AsyncTestCase):
_tolerance = 1.1
_outputs_ptr = ["outputs:dataPtr","outputs:width","outputs:height","outputs:bufferSize","outputs:format"]
_outputs_arr = ["outputs:data","outputs:width","outputs:height","outputs:bufferSize","outputs:format"]
@staticmethod
def _assert_equal_tex_infos(out_a, out_b):
assert((out_a["outputs:width"] == out_b["outputs:width"]) and (out_a["outputs:height"] == out_b["outputs:height"]) and (out_a["outputs:format"] == out_b["outputs:format"]))
@staticmethod
def _assert_equal_buff_infos(out_a, out_b):
assert((out_a["outputs:bufferSize"] == out_b["outputs:bufferSize"]))
@staticmethod
def _assert_equal_data(data_a, data_b):
assert(np.amax(np.square(data_a - data_b)) < TestRenderVarBuffHostPtr._tolerance)
def _get_raw_array(self, rv):
return syn.SyntheticData.Get().get_node_attributes(rv + "ExportRawArray", TestRenderVarBuffHostPtr._outputs_arr, self.render_product)
def _get_ptr_array(self, rv, ptr_suffix):
ptr_outputs = syn.SyntheticData.Get().get_node_attributes(rv + ptr_suffix, TestRenderVarBuffHostPtr._outputs_ptr, self.render_product)
c_ptr = ctypes.cast(ptr_outputs["outputs:dataPtr"],ctypes.POINTER(ctypes.c_ubyte))
ptr_outputs["outputs:dataPtr"] = np.ctypeslib.as_array(c_ptr,shape=(ptr_outputs["outputs:bufferSize"],))
return ptr_outputs
def _assert_equal_rv_ptr(self, rv:str, ptr_suffix:str, texture=None):
arr_out = self._get_raw_array(rv)
ptr_out = self._get_ptr_array(rv,ptr_suffix)
if not texture is None:
if texture:
TestRenderVarBuffHostPtr._assert_equal_tex_infos(arr_out,ptr_out)
else:
TestRenderVarBuffHostPtr._assert_equal_buff_infos(arr_out,ptr_out)
TestRenderVarBuffHostPtr._assert_equal_data(arr_out["outputs:data"],ptr_out["outputs:dataPtr"])
def _assert_equal_rv_arr(self, rv:str, ptr_suffix:str, texture=None):
arr_out_a = self._get_raw_array(rv)
arr_out_b = self._get_raw_array(rv+ptr_suffix)
if not texture is None:
if texture:
TestRenderVarBuffHostPtr._assert_equal_tex_infos(arr_out_a,arr_out_b)
else:
TestRenderVarBuffHostPtr._assert_equal_buff_infos(arr_out_a,arr_out_b)
TestRenderVarBuffHostPtr._assert_equal_data(arr_out_a["outputs:data"],arr_out_b["outputs:data"])
def __init__(self, methodName: str) -> None:
super().__init__(methodName=methodName)
async def setUp(self):
await omni.usd.get_context().new_stage_async()
stage = omni.usd.get_context().get_stage()
world_prim = UsdGeom.Xform.Define(stage,"/World")
UsdGeom.Xformable(world_prim).AddTranslateOp().Set((0, 0, 0))
UsdGeom.Xformable(world_prim).AddRotateXYZOp().Set((0, 0, 0))
sphere_prim = stage.DefinePrim("/World/Sphere", "Sphere")
add_semantics(sphere_prim, "sphere")
UsdGeom.Xformable(sphere_prim).AddTranslateOp().Set((0, 0, 0))
UsdGeom.Xformable(sphere_prim).AddScaleOp().Set((77, 77, 77))
UsdGeom.Xformable(sphere_prim).AddRotateXYZOp().Set((-90, 0, 0))
sphere_prim.GetAttribute("primvars:displayColor").Set([(1, 0.3, 1)])
capsule0_prim = stage.DefinePrim("/World/Sphere/Capsule0", "Capsule")
add_semantics(capsule0_prim, "capsule0")
UsdGeom.Xformable(capsule0_prim).AddTranslateOp().Set((3, 0, 0))
UsdGeom.Xformable(capsule0_prim).AddRotateXYZOp().Set((0, 0, 0))
capsule0_prim.GetAttribute("primvars:displayColor").Set([(0.3, 1, 0)])
capsule1_prim = stage.DefinePrim("/World/Sphere/Capsule1", "Capsule")
add_semantics(capsule1_prim, "capsule1")
UsdGeom.Xformable(capsule1_prim).AddTranslateOp().Set((-3, 0, 0))
UsdGeom.Xformable(capsule1_prim).AddRotateXYZOp().Set((0, 0, 0))
capsule1_prim.GetAttribute("primvars:displayColor").Set([(0, 1, 0.3)])
capsule2_prim = stage.DefinePrim("/World/Sphere/Capsule2", "Capsule")
add_semantics(capsule2_prim, "capsule2")
UsdGeom.Xformable(capsule2_prim).AddTranslateOp().Set((0, 3, 0))
UsdGeom.Xformable(capsule2_prim).AddRotateXYZOp().Set((0, 0, 0))
capsule2_prim.GetAttribute("primvars:displayColor").Set([(0.7, 0.1, 0.4)])
capsule3_prim = stage.DefinePrim("/World/Sphere/Capsule3", "Capsule")
add_semantics(capsule3_prim, "capsule3")
UsdGeom.Xformable(capsule3_prim).AddTranslateOp().Set((0, -3, 0))
UsdGeom.Xformable(capsule3_prim).AddRotateXYZOp().Set((0, 0, 0))
capsule3_prim.GetAttribute("primvars:displayColor").Set([(0.1, 0.7, 0.4)])
spherelight = UsdLux.SphereLight.Define(stage, "/SphereLight")
spherelight.GetIntensityAttr().Set(30000)
spherelight.GetRadiusAttr().Set(30)
self.viewport = get_active_viewport()
self.render_product = self.viewport.render_product_path
async def test_host_arr(self):
render_vars = [
"BoundingBox2DLooseSD",
"SemanticLocalTransformSD"
]
for rv in render_vars:
syn.SyntheticData.Get().activate_node_template(rv + "ExportRawArray", 0, [self.render_product])
syn.SyntheticData.Get().activate_node_template(rv + "hostExportRawArray", 0, [self.render_product])
await syn.sensors.next_sensor_data_async(self.viewport,True)
await omni.kit.app.get_app().next_update_async()
for rv in render_vars:
self._assert_equal_rv_arr(rv,"host", False)
async def test_buff_arr(self):
render_vars = [
"Camera3dPositionSD",
"DistanceToImagePlaneSD",
]
for rv in render_vars:
syn.SyntheticData.Get().activate_node_template(rv + "ExportRawArray", 0, [self.render_product])
syn.SyntheticData.Get().activate_node_template(rv + "buffExportRawArray", 0, [self.render_product])
await syn.sensors.next_sensor_data_async(self.viewport,True)
await omni.kit.app.get_app().next_update_async()
for rv in render_vars:
self._assert_equal_rv_arr(rv, "buff")
async def test_host_ptr(self):
render_vars = [
"BoundingBox2DTightSD",
"BoundingBox3DSD",
"InstanceMapSD"
]
for rv in render_vars:
syn.SyntheticData.Get().activate_node_template(rv + "ExportRawArray", 0, [self.render_product])
syn.SyntheticData.Get().activate_node_template(rv + "hostPtr", 0, [self.render_product])
await syn.sensors.next_sensor_data_async(self.viewport,True)
await omni.kit.app.get_app().next_update_async()
for rv in render_vars:
self._assert_equal_rv_ptr(rv,"hostPtr",False)
async def test_host_ptr_tex(self):
render_vars = [
"NormalSD",
"DistanceToCameraSD"
]
for rv in render_vars:
syn.SyntheticData.Get().activate_node_template(rv + "ExportRawArray", 0, [self.render_product])
syn.SyntheticData.Get().activate_node_template(rv + "hostPtr", 0, [self.render_product])
await syn.sensors.next_sensor_data_async(self.viewport,True)
await omni.kit.app.get_app().next_update_async()
for rv in render_vars:
self._assert_equal_rv_ptr(rv,"hostPtr",True)
async def test_buff_host_ptr(self):
render_vars = [
"LdrColorSD",
"InstanceSegmentationSD",
]
for rv in render_vars:
syn.SyntheticData.Get().activate_node_template(rv + "ExportRawArray", 0, [self.render_product])
syn.SyntheticData.Get().activate_node_template(rv + "buffhostPtr", 0, [self.render_product])
await syn.sensors.next_sensor_data_async(self.viewport,True)
await syn.sensors.next_sensor_data_async(self.viewport,True)
await syn.sensors.next_sensor_data_async(self.viewport,True)
await omni.kit.app.get_app().next_update_async()
for rv in render_vars:
self._assert_equal_rv_ptr(rv, "buffhostPtr",True)
# After running each test
async def tearDown(self):
pass
| 9,320 | Python | 47.546875 | 180 | 0.652575 |
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