def test_video_dataset(self):
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
data_prefix=self.data_prefix,
start_index=3)
assert len(video_dataset) == 2
assert video_dataset.start_index == 3
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
data_prefix=self.data_prefix)
video_infos = video_dataset.video_infos
video_filename = osp.join(self.data_prefix, 'test.mp4')
assert video_infos == [dict(filename=video_filename, label=0)] * 2
assert video_dataset.start_index == 0
def test_base_dataset(self):
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
data_prefix=self.data_prefix,
start_index=3)
assert len(video_dataset) == 2
assert video_dataset.start_index == 3
def test_video_pipeline(self):
target_keys = ['filename', 'label']
# VideoDataset not in test mode
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
self.data_prefix,
test_mode=False)
result = video_dataset[0]
assert self.check_keys_contain(result.keys(), target_keys)
# VideoDataset in test mode
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
self.data_prefix,
test_mode=True)
result = video_dataset[0]
assert self.check_keys_contain(result.keys(), target_keys)
def test_video_pipeline(self):
target_keys = ['filename', 'label', 'start_index', 'modality']
# VideoDataset not in test mode
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
data_prefix=self.data_prefix,
test_mode=False)
result = video_dataset[0]
assert assert_dict_has_keys(result, target_keys)
# VideoDataset in test mode
video_dataset = VideoDataset(self.video_ann_file,
self.video_pipeline,
data_prefix=self.data_prefix,
test_mode=True)
result = video_dataset[0]
assert assert_dict_has_keys(result, target_keys)
def test_video_dataset_multi_label(self):
video_dataset = VideoDataset(self.video_ann_file_multi_label,
self.video_pipeline,
data_prefix=self.data_prefix,
multi_class=True,
num_classes=100)
video_infos = video_dataset.video_infos
video_filename = osp.join(self.data_prefix, 'test.mp4')
label0 = [0, 3]
label1 = [0, 2, 4]
labels = [label0, label1]
for info, label in zip(video_infos, labels):
print(info, video_filename)
assert info['filename'] == video_filename
assert set(info['label']) == set(label)
assert video_dataset.start_index == 0
def test_video_dataset(self):
video_dataset = VideoDataset(self.video_ann_file, self.video_pipeline,
self.data_prefix)
video_infos = video_dataset.video_infos
video_filename = osp.join(self.data_prefix, 'test.mp4')
assert video_infos == [dict(filename=video_filename, label=0)] * 2
def test_base_dataset(self):
video_dataset = VideoDataset(self.video_ann_file, self.video_pipeline,
self.data_prefix)
assert len(video_dataset) == 2
assert type(video_dataset[0]) == dict
def test_video_evaluate(self):
video_dataset = VideoDataset(self.video_ann_file, self.video_pipeline,
self.data_prefix)
with pytest.raises(TypeError):
# results must be a list
video_dataset.evaluate('0.5')
with pytest.raises(AssertionError):
# The length of results must be equal to the dataset len
video_dataset.evaluate([0] * 5)
with pytest.raises(TypeError):
# topk must be int or tuple of int
video_dataset.evaluate([0] * len(video_dataset), topk=1.0)
with pytest.raises(KeyError):
# unsupported metric
video_dataset.evaluate([0] * len(video_dataset), metrics='iou')
# evaluate top_k_accuracy and mean_class_accuracy metric
results = [np.array([0.1, 0.5, 0.4])] * 2
eval_result = video_dataset.evaluate(
results, metrics=['top_k_accuracy', 'mean_class_accuracy'])
assert set(eval_result.keys()) == set(
['top1_acc', 'top5_acc', 'mean_class_accuracy'])
