def test_dataset_realpath(self):
dataset = RawframeDataset(self.frame_ann_file, self.frame_pipeline,
'.')
assert dataset.data_prefix == osp.realpath('.')
dataset = RawframeDataset(self.frame_ann_file, self.frame_pipeline,
's3://good')
assert dataset.data_prefix == 's3://good'
def test_dataset_realpath(self):
dataset = RawframeDataset(self.frame_ann_file, self.frame_pipeline,
'.')
assert dataset.data_prefix == osp.realpath('.')
dataset = RawframeDataset(self.frame_ann_file, self.frame_pipeline,
's3://good')
assert dataset.data_prefix == 's3://good'
dataset = RawframeDataset(self.frame_ann_file, self.frame_pipeline)
assert dataset.data_prefix is None
assert dataset.video_infos[0]['frame_dir'] == 'imgs'
def test_rawframe_dataset(self):
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix)
rawframe_infos = rawframe_dataset.video_infos
frame_dir = osp.join(self.data_prefix, 'test_imgs')
assert rawframe_infos == [
dict(frame_dir=frame_dir, total_frames=5, label=127)
] * 2
def test_rawframe_dataset_with_offset(self):
rawframe_dataset = RawframeDataset(self.frame_ann_file_with_offset,
self.frame_pipeline,
self.data_prefix,
with_offset=True)
rawframe_infos = rawframe_dataset.records
frame_dir = osp.join(self.data_prefix, 'test_imgs')
assert rawframe_infos == [
dict(frame_dir=frame_dir, offset=2, total_frames=5, label=127)
] * 2
assert rawframe_dataset.start_index == 1
def test_rawframe_pipeline(self):
target_keys = ['frame_dir', 'total_frames', 'label', 'filename_tmpl']
# RawframeDataset not in test mode
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
test_mode=False)
result = rawframe_dataset[0]
assert self.check_keys_contain(result.keys(), target_keys)
# RawframeDataset in multi-class tasks
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
multi_class=True,
num_classes=400,
test_mode=False)
result = rawframe_dataset[0]
assert self.check_keys_contain(result.keys(), target_keys)
# RawframeDataset in test mode
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
test_mode=True)
result = rawframe_dataset[0]
assert self.check_keys_contain(result.keys(), target_keys)
# RawframeDataset in multi-class tasks in test mode
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
multi_class=True,
num_classes=400,
test_mode=True)
result = rawframe_dataset[0]
assert self.check_keys_contain(result.keys(), target_keys)
def test_rawframe_dataset_multi_label(self):
rawframe_dataset = RawframeDataset(self.frame_ann_file_multi_label,
self.frame_pipeline,
self.data_prefix,
multi_class=True,
num_classes=100)
rawframe_infos = rawframe_dataset.video_infos
frame_dir = osp.join(self.data_prefix, 'test_imgs')
label0 = [1]
label1 = [3, 5]
labels = [label0, label1]
for info, label in zip(rawframe_infos, labels):
assert info['frame_dir'] == frame_dir
assert info['total_frames'] == 5
assert set(info['label']) == set(label)
assert rawframe_dataset.start_index == 1
def test_repeat_dataset(self):
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix)
repeat_dataset = RepeatDataset(rawframe_dataset, 5)
assert len(repeat_dataset) == 10
result_a = repeat_dataset[0]
result_b = repeat_dataset[2]
assert set(result_a.keys()) == set(result_b.keys())
for key in result_a:
if isinstance(result_a[key], np.ndarray):
assert np.equal(result_a[key], result_b[key]).all()
elif isinstance(result_a[key], list):
assert all(
np.array_equal(a, b)
for (a, b) in zip(result_a[key], result_b[key]))
else:
assert result_a[key] == result_b[key]
def test_rawframe_dataset_multi_label(self):
rawframe_dataset = RawframeDataset(self.frame_ann_file_multi_label,
self.frame_pipeline,
self.data_prefix,
multi_class=True,
num_classes=100)
rawframe_infos = rawframe_dataset.records
frame_dir = osp.join(self.data_prefix, 'test_imgs')
label0 = torch.zeros(100)
label0[[1]] = 1.0
label1 = torch.zeros(100)
label1[[3, 5]] = 1.0
labels = [label0, label1]
for info, label in zip(rawframe_infos, labels):
assert info['frame_dir'] == frame_dir
assert info['total_frames'] == 5
assert torch.all(info['label'] == label)
assert rawframe_dataset.start_index == 1
def test_rawframe_evaluate(self):
rawframe_dataset = RawframeDataset(self.frame_ann_file,
self.frame_pipeline,
self.data_prefix)
with pytest.raises(TypeError):
# results must be a list
rawframe_dataset.evaluate('0.5')
with pytest.raises(AssertionError):
# The length of results must be equal to the dataset len
rawframe_dataset.evaluate([0] * 5)
with pytest.raises(TypeError):
# topk must be int or tuple of int
rawframe_dataset.evaluate([0] * len(rawframe_dataset), topk=1.0)
with pytest.raises(KeyError):
# unsupported metric
rawframe_dataset.evaluate([0] * len(rawframe_dataset),
metrics='iou')
# evaluate top_k_accuracy and mean_class_accuracy metric
results = [np.array([0.1, 0.5, 0.4])] * 2
eval_result = rawframe_dataset.evaluate(
results, metrics=['top_k_accuracy', 'mean_class_accuracy'])
assert set(eval_result.keys()) == set(
['top1_acc', 'top5_acc', 'mean_class_accuracy'])
def test_rawframe_pipeline(self):
target_keys = [
'frame_dir', 'total_frames', 'label', 'filename_tmpl',
'start_index', 'modality'
]
# RawframeDataset not in test mode
rawframe_dataset = RawframeDataset(
self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
test_mode=False)
result = rawframe_dataset[0]
assert assert_dict_has_keys(result, target_keys)
# RawframeDataset in multi-class tasks
rawframe_dataset = RawframeDataset(
self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
multi_class=True,
num_classes=400,
test_mode=False)
result = rawframe_dataset[0]
assert assert_dict_has_keys(result, target_keys)
# RawframeDataset with offset
rawframe_dataset = RawframeDataset(
self.frame_ann_file_with_offset,
self.frame_pipeline,
self.data_prefix,
with_offset=True,
num_classes=400,
test_mode=False)
result = rawframe_dataset[0]
assert assert_dict_has_keys(result, target_keys + ['offset'])
# RawframeDataset in test mode
rawframe_dataset = RawframeDataset(
self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
test_mode=True)
result = rawframe_dataset[0]
assert assert_dict_has_keys(result, target_keys)
# RawframeDataset in multi-class tasks in test mode
rawframe_dataset = RawframeDataset(
self.frame_ann_file,
self.frame_pipeline,
self.data_prefix,
multi_class=True,
num_classes=400,
test_mode=True)
result = rawframe_dataset[0]
assert assert_dict_has_keys(result, target_keys)
# RawframeDataset with offset
rawframe_dataset = RawframeDataset(
self.frame_ann_file_with_offset,
self.frame_pipeline,
self.data_prefix,
with_offset=True,
num_classes=400,
test_mode=True)
result = rawframe_dataset[0]
assert assert_dict_has_keys(result, target_keys + ['offset'])
