Spaces:
Running
Running
File size: 11,712 Bytes
7088d16 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 |
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import unittest
import torch
from pytorch3d.implicitron.dataset.data_loader_map_provider import ( # noqa
SequenceDataLoaderMapProvider,
SimpleDataLoaderMapProvider,
)
from pytorch3d.implicitron.dataset.data_source import ImplicitronDataSource
from pytorch3d.implicitron.dataset.sql_dataset import SqlIndexDataset # noqa
from pytorch3d.implicitron.dataset.sql_dataset_provider import ( # noqa
SqlIndexDatasetMapProvider,
)
from pytorch3d.implicitron.dataset.train_eval_data_loader_provider import (
TrainEvalDataLoaderMapProvider,
)
from pytorch3d.implicitron.tools.config import get_default_args
logger = logging.getLogger("pytorch3d.implicitron.dataset.sql_dataset")
sh = logging.StreamHandler()
logger.addHandler(sh)
logger.setLevel(logging.DEBUG)
_CO3D_SQL_DATASET_ROOT: str = os.getenv("CO3D_SQL_DATASET_ROOT", "")
@unittest.skipUnless(_CO3D_SQL_DATASET_ROOT, "Run only if CO3D is available")
class TestCo3dSqlDataSource(unittest.TestCase):
def test_no_subsets(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.ignore_subsets = True
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.pick_categories = ["skateboard"]
dataset_args.limit_sequences_to = 1
data_source = ImplicitronDataSource(**args)
self.assertIsInstance(
data_source.data_loader_map_provider, TrainEvalDataLoaderMapProvider
)
_, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertEqual(len(data_loaders.train), 202)
for frame in data_loaders.train:
self.assertIsNone(frame.frame_type)
self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
break
def test_subsets(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_lists_path = (
"skateboard/set_lists/set_lists_manyview_dev_0.json"
)
# this will naturally limit to one sequence (no need to limit by cat/sequence)
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.remove_empty_masks = True
for sampler_type in [
"SimpleDataLoaderMapProvider",
"SequenceDataLoaderMapProvider",
"TrainEvalDataLoaderMapProvider",
]:
args.data_loader_map_provider_class_type = sampler_type
data_source = ImplicitronDataSource(**args)
_, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertEqual(len(data_loaders.train), 102)
self.assertEqual(len(data_loaders.val), 100)
self.assertEqual(len(data_loaders.test), 100)
for split in ["train", "val", "test"]:
for frame in data_loaders[split]:
self.assertEqual(frame.frame_type, [split])
# check loading blobs
self.assertEqual(frame.image_rgb.shape[-1], 800)
break
def test_sql_subsets(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_lists_path = "set_lists/set_lists_manyview_dev_0.sqlite"
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.remove_empty_masks = True
dataset_args.pick_categories = ["skateboard"]
for sampler_type in [
"SimpleDataLoaderMapProvider",
"SequenceDataLoaderMapProvider",
"TrainEvalDataLoaderMapProvider",
]:
args.data_loader_map_provider_class_type = sampler_type
data_source = ImplicitronDataSource(**args)
_, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertEqual(len(data_loaders.train), 102)
self.assertEqual(len(data_loaders.val), 100)
self.assertEqual(len(data_loaders.test), 100)
for split in ["train", "val", "test"]:
for frame in data_loaders[split]:
self.assertEqual(frame.frame_type, [split])
self.assertEqual(
frame.image_rgb.shape[-1], 800
) # check loading blobs
break
@unittest.skip("It takes 75 seconds; skipping by default")
def test_huge_subsets(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_lists_path = "set_lists/set_lists_fewview_dev.sqlite"
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.remove_empty_masks = True
data_source = ImplicitronDataSource(**args)
_, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertEqual(len(data_loaders.train), 3158974)
self.assertEqual(len(data_loaders.val), 518417)
self.assertEqual(len(data_loaders.test), 518417)
for split in ["train", "val", "test"]:
for frame in data_loaders[split]:
self.assertEqual(frame.frame_type, [split])
self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
break
def test_broken_subsets(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_lists_path = "et_non_est"
provider_args.dataset_SqlIndexDataset_args.pick_categories = ["skateboard"]
with self.assertRaises(FileNotFoundError) as err:
ImplicitronDataSource(**args)
# check the hint text
self.assertIn("Subset lists path given but not found", str(err.exception))
def test_eval_batches(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_lists_path = "set_lists/set_lists_manyview_dev_0.sqlite"
provider_args.eval_batches_path = (
"skateboard/eval_batches/eval_batches_manyview_dev_0.json"
)
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.remove_empty_masks = True
dataset_args.pick_categories = ["skateboard"]
data_source = ImplicitronDataSource(**args)
_, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertEqual(len(data_loaders.train), 102)
self.assertEqual(len(data_loaders.val), 100)
self.assertEqual(len(data_loaders.test), 50)
for split in ["train", "val", "test"]:
for frame in data_loaders[split]:
self.assertEqual(frame.frame_type, [split])
self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
break
def test_eval_batches_from_subset_list_name(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_list_name = "manyview_dev_0"
provider_args.category = "skateboard"
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.remove_empty_masks = True
data_source = ImplicitronDataSource(**args)
dataset, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertListEqual(list(dataset.train.pick_categories), ["skateboard"])
self.assertEqual(len(data_loaders.train), 102)
self.assertEqual(len(data_loaders.val), 100)
self.assertEqual(len(data_loaders.test), 50)
for split in ["train", "val", "test"]:
for frame in data_loaders[split]:
self.assertEqual(frame.frame_type, [split])
self.assertEqual(frame.image_rgb.shape[-1], 800) # check loading blobs
break
def test_frame_access(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "SqlIndexDatasetMapProvider"
args.data_loader_map_provider_class_type = "TrainEvalDataLoaderMapProvider"
provider_args = args.dataset_map_provider_SqlIndexDatasetMapProvider_args
provider_args.subset_lists_path = "set_lists/set_lists_manyview_dev_0.sqlite"
dataset_args = provider_args.dataset_SqlIndexDataset_args
dataset_args.remove_empty_masks = True
dataset_args.pick_categories = ["skateboard"]
frame_builder_args = dataset_args.frame_data_builder_FrameDataBuilder_args
frame_builder_args.load_point_clouds = True
frame_builder_args.box_crop = False # required for .meta
data_source = ImplicitronDataSource(**args)
dataset_map, _ = data_source.get_datasets_and_dataloaders()
dataset = dataset_map["train"]
for idx in [10, ("245_26182_52130", 22)]:
example_meta = dataset.meta[idx]
example = dataset[idx]
self.assertIsNone(example_meta.image_rgb)
self.assertIsNone(example_meta.fg_probability)
self.assertIsNone(example_meta.depth_map)
self.assertIsNone(example_meta.sequence_point_cloud)
self.assertIsNotNone(example_meta.camera)
self.assertIsNotNone(example.image_rgb)
self.assertIsNotNone(example.fg_probability)
self.assertIsNotNone(example.depth_map)
self.assertIsNotNone(example.sequence_point_cloud)
self.assertIsNotNone(example.camera)
self.assertEqual(example_meta.sequence_name, example.sequence_name)
self.assertEqual(example_meta.frame_number, example.frame_number)
self.assertEqual(example_meta.frame_timestamp, example.frame_timestamp)
self.assertEqual(example_meta.sequence_category, example.sequence_category)
torch.testing.assert_close(example_meta.camera.R, example.camera.R)
torch.testing.assert_close(example_meta.camera.T, example.camera.T)
torch.testing.assert_close(
example_meta.camera.focal_length, example.camera.focal_length
)
torch.testing.assert_close(
example_meta.camera.principal_point, example.camera.principal_point
)
|