def test_can_save_dataset_with_no_save_images(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='0001_c2s3_000001_00',
subset='test',
image=np.ones((2, 5, 3)),
attributes={
'camera_id': 1,
'person_id': 1,
'query': True
}),
DatasetItem(id='test1',
subset='test',
image=np.ones((2, 5, 3)),
attributes={
'camera_id': 1,
'person_id': 2,
'query': False
}),
])
with TestDir() as test_dir:
Market1501Converter.convert(source_dataset,
test_dir,
save_images=False)
parsed_dataset = Dataset.import_from(test_dir, 'market1501')
compare_datasets(self, source_dataset, parsed_dataset)
def test_can_save_and_load_image_with_arbitrary_extension(self):
expected = Dataset.from_iterable([
DatasetItem(id='q/1',
image=Image(path='q/1.JPEG', data=np.zeros((4, 3, 3))),
attributes={
'camera_id': 1,
'person_id': 1,
'query': False
}),
DatasetItem(id='a/b/c/2',
image=Image(path='a/b/c/2.bmp',
data=np.zeros((3, 4, 3))),
attributes={
'camera_id': 1,
'person_id': 2,
'query': True
}),
])
with TestDir() as test_dir:
Market1501Converter.convert(expected, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'market1501')
compare_datasets(self,
expected,
parsed_dataset,
require_images=True)
def test_can_save_dataset_with_no_attributes(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='test1',
subset='test', image=np.ones((2, 5, 3)),
),
])
with TestDir() as test_dir:
Market1501Converter.convert(source_dataset, test_dir, save_images=False)
parsed_dataset = Dataset.import_from(test_dir, 'market1501')
compare_datasets(self, source_dataset, parsed_dataset)
def test_can_save_dataset_with_cyrillic_and_spaces_in_filename(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='кириллица с пробелом',
image=np.ones((2, 5, 3)),
attributes={
'camera_id': 1,
'person_id': 1,
'query': True
}),
])
with TestDir() as test_dir:
Market1501Converter.convert(source_dataset,
test_dir,
save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'market1501')
compare_datasets(self,
source_dataset,
parsed_dataset,
require_images=True)
def test_can_save_and_load(self):
source_dataset = Dataset.from_iterable([
DatasetItem(id='0001_c2s3_000001_00',
subset='query', image=np.ones((2, 5, 3)),
attributes = {'camera_id': 1, 'person_id': '0001', 'track_id': 3,
'frame_id': 1, 'bbox_id': 0, 'query': True}
),
DatasetItem(id='0002_c4s2_000002_00',
subset='test', image=np.ones((2, 5, 3)),
attributes = {'camera_id': 3, 'person_id': '0002', 'track_id': 2,
'frame_id': 2, 'bbox_id': 0, 'query': False}
),
DatasetItem(id='0001_c1s1_000003_00',
subset='test', image=np.ones((2, 5, 3)),
attributes = {'camera_id': 0, 'person_id': '0001', 'track_id': 1,
'frame_id': 3, 'bbox_id': 0, 'query': False}
),
])
with TestDir() as test_dir:
Market1501Converter.convert(source_dataset, test_dir, save_images=True)
parsed_dataset = Dataset.import_from(test_dir, 'market1501')
compare_datasets(self, source_dataset, parsed_dataset)