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# 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 os
import unittest
from pytorch3d.implicitron.dataset.data_source import ImplicitronDataSource
from pytorch3d.implicitron.tools.config import get_default_args
from pytorch3d.renderer import PerspectiveCameras
from tests.common_testing import TestCaseMixin
# These tests are only run internally, where the data is available.
internal = os.environ.get("FB_TEST", False)
inside_re_worker = os.environ.get("INSIDE_RE_WORKER", False)
skip_tests = not internal or inside_re_worker
@unittest.skipIf(skip_tests, "no data")
class TestDataJsonIndex(TestCaseMixin, unittest.TestCase):
def test_loaders(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "JsonIndexDatasetMapProvider"
dataset_args = args.dataset_map_provider_JsonIndexDatasetMapProvider_args
dataset_args.category = "skateboard"
dataset_args.dataset_root = "manifold://co3d/tree/extracted"
dataset_args.test_restrict_sequence_id = 0
dataset_args.dataset_JsonIndexDataset_args.limit_sequences_to = 1
data_source = ImplicitronDataSource(**args)
cameras = data_source.all_train_cameras
self.assertIsInstance(cameras, PerspectiveCameras)
self.assertEqual(len(cameras), 81)
data_sets, data_loaders = data_source.get_datasets_and_dataloaders()
self.assertEqual(len(data_sets.train), 81)
self.assertEqual(len(data_sets.val), 102)
self.assertEqual(len(data_sets.test), 102)
def test_visitor_subsets(self):
args = get_default_args(ImplicitronDataSource)
args.dataset_map_provider_class_type = "JsonIndexDatasetMapProvider"
dataset_args = args.dataset_map_provider_JsonIndexDatasetMapProvider_args
dataset_args.category = "skateboard"
dataset_args.dataset_root = "manifold://co3d/tree/extracted"
dataset_args.test_restrict_sequence_id = 0
dataset_args.dataset_JsonIndexDataset_args.limit_sequences_to = 1
data_source = ImplicitronDataSource(**args)
datasets, _ = data_source.get_datasets_and_dataloaders()
dataset = datasets.test
sequences = list(dataset.sequence_names())
self.assertEqual(len(sequences), 1)
i = 0
for seq in sequences:
last_ts = float("-Inf")
seq_frames = list(dataset.sequence_frames_in_order(seq))
self.assertEqual(len(seq_frames), 102)
for ts, _, idx in seq_frames:
self.assertEqual(i, idx)
i += 1
self.assertGreaterEqual(ts, last_ts)
last_ts = ts
last_ts = float("-Inf")
known_frames = list(dataset.sequence_frames_in_order(seq, "test_known"))
self.assertEqual(len(known_frames), 81)
for ts, _, _ in known_frames:
self.assertGreaterEqual(ts, last_ts)
last_ts = ts
known_indices = list(dataset.sequence_indices_in_order(seq, "test_known"))
self.assertEqual(len(known_indices), 81)
break # testing only the first sequence
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