def mock_encoded_video_dataset_file():
"""
Creates a temporary mock encoded video dataset with 4 videos labeled from 0 - 4.
Returns a labeled video file which points to this mock encoded video dataset, the
ordered label and videos tuples and the video duration in seconds.
"""
num_frames = 10
fps = 5
with temp_encoded_video(num_frames=num_frames, fps=fps) as (
video_file_name_1,
data_1,
):
with temp_encoded_video(num_frames=num_frames, fps=fps) as (
video_file_name_2,
data_2,
):
with tempfile.NamedTemporaryFile(delete=False, suffix=".txt") as f:
f.write(f"{video_file_name_1} 0\n".encode())
f.write(f"{video_file_name_2} 1\n".encode())
f.write(f"{video_file_name_1} 2\n".encode())
f.write(f"{video_file_name_2} 3\n".encode())
label_videos = [
(0, data_1),
(1, data_2),
(2, data_1),
(3, data_2),
]
video_duration = num_frames / fps
yield f.name, label_videos, video_duration
def test_video_name_with_whitespace_works(self, decoder):
num_frames = 10
fps = 5
with temp_encoded_video(num_frames=num_frames,
fps=fps,
prefix="pre fix") as (
video_file_name,
data,
):
with tempfile.NamedTemporaryFile(delete=False, suffix=".txt") as f:
f.write(f"{video_file_name} 0\n".encode())
f.write(f"{video_file_name} 1\n".encode())
total_duration = num_frames / fps
clip_sampler = make_clip_sampler("uniform", total_duration)
labeled_video_paths = LabeledVideoPaths.from_path(f.name)
dataset = LabeledVideoDataset(
labeled_video_paths,
clip_sampler=clip_sampler,
video_sampler=SequentialSampler,
decode_audio=False,
decoder=decoder,
)
expected = [(0, data), (1, data)]
for i, sample in enumerate(dataset):
self.assertTrue(sample["video"].equal(expected[i][1]))
self.assertEqual(sample["label"], expected[i][0])
def test_video_works(self):
num_frames = 11
fps = 5
with temp_encoded_video(num_frames=num_frames,
fps=fps) as (file_name, data):
test_video = EncodedVideo.from_path(file_name)
self.assertAlmostEqual(test_video.duration, num_frames / fps)
# All frames (0 - test_video.duration seconds)
clip = test_video.get_clip(0, test_video.duration)
frames, audio_samples = clip["video"], clip["audio"]
self.assertTrue(frames.equal(data))
self.assertEqual(audio_samples, None)
# Half frames
clip = test_video.get_clip(0, test_video.duration / 2)
frames, audio_samples = clip["video"], clip["audio"]
self.assertTrue(frames.equal(data[:, :round(num_frames / 2)]))
self.assertEqual(audio_samples, None)
# No frames
clip = test_video.get_clip(test_video.duration + 1,
test_video.duration + 3)
frames, audio_samples = clip["video"], clip["audio"]
self.assertEqual(frames, None)
self.assertEqual(audio_samples, None)
test_video.close()
def test_sampling_with_non_divisible_processes_by_clips(self, decoder):
# Make one video with 15 frames and one with 10 frames, producing 3 clips and 2
# clips respectively.
num_frames = 10
fps = 5
with temp_encoded_video(num_frames=int(num_frames * 1.5), fps=fps) as (
video_file_name_1,
data_1,
):
with temp_encoded_video(num_frames=num_frames, fps=fps) as (
video_file_name_2,
data_2,
):
with tempfile.NamedTemporaryFile(delete=False,
suffix=".txt") as f:
f.write(f"{video_file_name_1} 0\n".encode())
f.write(f"{video_file_name_2} 1\n".encode())
total_duration = num_frames / fps
half_duration = total_duration / 2 - self._EPS
clip_sampler = make_clip_sampler("uniform", half_duration)
labeled_video_paths = LabeledVideoPaths.from_path(f.name)
dataset = LabeledVideoDataset(
labeled_video_paths,
clip_sampler=clip_sampler,
video_sampler=SequentialSampler,
decode_audio=False,
decoder=decoder,
)
half_frames = num_frames // 2
expected = {
(0, data_1[:, half_frames * 2:]), # 1/3 clip
(0, data_1[:, half_frames:half_frames * 2]), # 2/3 clip
(0, data_1[:, :half_frames]), # 3/3/ clip
(1, data_2[:, :half_frames]), # First half
(1, data_2[:, half_frames:]), # Second half
}
test_dataloader = DataLoader(dataset,
batch_size=None,
num_workers=2)
actual = [(sample["label"], sample["video"])
for sample in test_dataloader]
assert_unordered_list_compare_true(self, expected, actual)
def test_constant_clips_per_video_sampling_works(self, decoder):
# Make one video with 15 frames and one with 10 frames, producing 3 clips and 2
# clips respectively.
num_frames = 10
fps = 5
with temp_encoded_video(num_frames=int(num_frames * 1.5), fps=fps) as (
video_file_name_1,
data_1,
):
with temp_encoded_video(num_frames=num_frames, fps=fps) as (
video_file_name_2,
data_2,
):
with tempfile.NamedTemporaryFile(delete=False,
suffix=".txt") as f:
f.write(f"{video_file_name_1} 0\n".encode())
f.write(f"{video_file_name_2} 1\n".encode())
clip_frames = 2
duration_for_frames = clip_frames / fps - self._EPS
clip_sampler = make_clip_sampler("constant_clips_per_video",
duration_for_frames, 2)
labeled_video_paths = LabeledVideoPaths.from_path(f.name)
dataset = LabeledVideoDataset(
labeled_video_paths,
clip_sampler=clip_sampler,
video_sampler=SequentialSampler,
decode_audio=False,
decoder=decoder,
)
# Dataset has 2 videos. Each video has two evenly spaced clips of size
# clip_frames sampled. The first clip of each video will always be
# sampled at second 0. The second clip of the video is the next frame
# from time: (total_duration - clip_duration) / 2
half_frames_1 = math.ceil((data_1.shape[1] - clip_frames) / 2)
half_frames_2 = math.ceil((data_2.shape[1] - clip_frames) / 2)
expected = [
(0, data_1[:, :clip_frames]),
(0, data_1[:, half_frames_1:half_frames_1 + clip_frames]),
(1, data_2[:, :clip_frames]),
(1, data_2[:, half_frames_2:half_frames_2 + clip_frames]),
]
for i, sample in enumerate(dataset):
self.assertTrue(sample["video"].equal(expected[i][1]))
self.assertEqual(sample["label"], expected[i][0])
def test_file_api(self):
num_frames = 11
fps = 5
with temp_encoded_video(num_frames=num_frames,
fps=fps) as (file_name, data):
with open(file_name, "rb") as f:
test_video = EncodedVideoPyAV(f)
self.assertAlmostEqual(test_video.duration, num_frames / fps)
clip = test_video.get_clip(0, test_video.duration)
frames, audio_samples = clip["video"], clip["audio"]
self.assertTrue(frames.equal(data))
self.assertEqual(audio_samples, None)
def test_sampling_with_distributed_sampler(self, decoder):
# Make one video with 15 frames and one with 10 frames, producing 3 clips and 2
# clips respectively.
num_frames = 10
fps = 5
with temp_encoded_video(num_frames=int(num_frames * 1.5), fps=fps) as (
video_file_name_1,
data_1,
):
with temp_encoded_video(num_frames=num_frames, fps=fps) as (
video_file_name_2,
data_2,
):
with tempfile.NamedTemporaryFile(delete=False,
suffix=".txt") as f:
f.write(f"{video_file_name_1} 0\n".encode())
f.write(f"{video_file_name_2} 1\n".encode())
total_duration = num_frames / fps
half_duration = total_duration / 2 - self._EPS
# Create several processes initialized in a PyTorch distributed process
# group so that distributed sampler is setup correctly when dataset is
# constructed.
num_processes = 2
processes = []
return_dict = multiprocessing.Manager().dict()
for rank in range(num_processes):
p = Process(
target=run_distributed,
args=(
rank,
num_processes,
decoder,
half_duration,
f.name,
return_dict,
),
)
p.start()
processes.append(p)
for p in processes:
p.join()
# After joining all distributed processes we expect all these label,
# video pairs to be returned in random order.
half_frames = num_frames // 2
expected = {
(0, data_1[:, :half_frames]), # 1/3 clip
(0, data_1[:, half_frames:half_frames * 2]), # 2/3 clip
(0, data_1[:, half_frames * 2:]), # 3/3 clip
(1, data_2[:, :half_frames]), # First half
(1, data_2[:, half_frames:]), # Second half
}
epoch_results = collections.defaultdict(list)
for v in return_dict.values():
for k_2, v_2 in v.items():
epoch_results[k_2].extend(v_2)
assert_unordered_list_compare_true(self, expected,
epoch_results["epoch_1"])
assert_unordered_list_compare_true(self, expected,
epoch_results["epoch_2"])
