|
import sys |
|
from pathlib import Path |
|
from vre.representations import Representation |
|
from vre_repository.color.rgb import RGB |
|
from vre_repository.color.hsv import HSV |
|
from vre_repository.depth import DepthRepresentation |
|
from vre_repository.normals import NormalsRepresentation |
|
from vre_repository.edges import EdgesRepresentation |
|
|
|
from vre_repository.semantic_segmentation import SemanticRepresentation |
|
|
|
def get_gt_tasks() -> dict[str, Representation]: |
|
color_map = [[0, 255, 0], [0, 127, 0], [255, 255, 0], [255, 255, 255], |
|
[255, 0, 0], [0, 0, 255], [0, 255, 255], [127, 127, 63]] |
|
classes_8 = ["land", "forest", "residential", "road", "little-objects", "water", "sky", "hill"] |
|
tasks = [ |
|
SemanticRepresentation("semantic_output", classes=classes_8, color_map=color_map, disk_data_argmax=True), |
|
DepthRepresentation("depth_output", min_depth=0, max_depth=300), |
|
NormalsRepresentation("camera_normals_output"), |
|
] |
|
return {t.name: t for t in tasks} |
|
|
|
def get_other_tasks(include_semantics_original: bool, include_ci: bool) -> dict[str, Representation]: |
|
sys.path.append(str(Path(__file__).parents[1] / "semantic_mapper")) |
|
from semantic_mapper import (m2f_mapillary, m2f_coco, m2f_r50_mapillary, |
|
BinaryMapper, mapillary_classes, coco_classes) |
|
tasks = [ |
|
rgb := RGB("rgb"), |
|
|
|
DepthRepresentation("depth_marigold", min_depth=0, max_depth=1), |
|
NormalsRepresentation("normals_svd(depth_marigold)") |
|
] |
|
|
|
if include_semantics_original: |
|
tasks.extend([m2f_mapillary, m2f_coco, m2f_r50_mapillary]) |
|
if include_ci: |
|
transportation_mapping = [ |
|
{ |
|
"others": [c for c in mapillary_classes if c not in |
|
(cls := ["Bike Lane", "Crosswalk - Plain", "Curb Cut", "Parking", "Rail Track", "Road", |
|
"Service Lane", "Sidewalk", "Bridge", "Tunnel", "Bicyclist", "Motorcyclist", |
|
"Other Rider", "Lane Marking - Crosswalk", "Lane Marking - General", |
|
"Traffic Light", "Traffic Sign (Back)", "Traffic Sign (Front)", "Bicycle", "Boat", |
|
"Bus", "Car", "Caravan", "Motorcycle", "On Rails", "Other Vehicle", "Trailer", |
|
"Truck", "Wheeled Slow", "Car Mount", "Ego Vehicle"])], |
|
"transportation": cls, |
|
}, |
|
{ |
|
"others": [c for c in coco_classes if c not in |
|
(cls := ["bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", |
|
"road", "railroad", "pavement-merged"])], |
|
"transportation": cls, |
|
}, |
|
] |
|
|
|
tasks.extend([ |
|
HSV("hsv", [rgb]), |
|
DepthRepresentation("depth_dpt", min_depth=0, max_depth=1), |
|
EdgesRepresentation("edges_dexined"), |
|
BinaryMapper("transportation_ci", [m2f_mapillary, m2f_coco], transportation_mapping, mode="at_least_one"), |
|
]) |
|
|
|
return {t.name: t for t in tasks} |
|
|
|
def get_dronescapes_task_types(include_semantics_original: bool, include_gt: bool, |
|
include_ci: bool) -> dict[str, Representation]: |
|
sys.path.append(str(Path(__file__).parents[1] / "semantic_mapper")) |
|
from semantic_mapper import get_new_semantic_mapped_tasks |
|
res = { |
|
**get_new_semantic_mapped_tasks(), |
|
**get_other_tasks(include_semantics_original, include_ci), |
|
**(get_gt_tasks() if include_gt else {}), |
|
} |
|
return res |
|
|
|
dronescapes_task_types = get_dronescapes_task_types(include_semantics_original=False, include_gt=True, include_ci=False) |
|
|
