def test_transform_set_select_merge_fade_rejected(self):
with deepstar_path():
with mock.patch.dict(os.environ, {'DEBUG_LEVEL': '0'}):
route_handler = VideoCommandLineRouteHandler()
video_0001 = os.path.dirname(os.path.realpath(__file__)) + '/../../support/video_0001.mp4' # noqa
route_handler.insert_file(video_0001)
route_handler.select_extract([1])
route_handler = FrameSetCommandLineRouteHandler()
route_handler.select_extract([1], 'transform_set', {})
route_handler.select_extract([1], 'transform_set', {})
transform_model = TransformModel()
transform_model.update(1, rejected=1)
transform_model.update(10, rejected=1)
FadeTransformSetSelectMergePlugin().transform_set_select_merge([1, 2], {'frame-count': '2'}) # noqa
# db
result = TransformSetModel().select(3)
self.assertEqual(result, (3, 'fade', None, None))
result = TransformModel().list(3)
self.assertEqual(len(result), 6)
self.assertEqual(result[0], (11, 3, 2, None, 0))
self.assertEqual(result[1], (12, 3, 3, None, 0))
self.assertEqual(result[2], (13, 3, None, None, 0))
self.assertEqual(result[3], (14, 3, None, None, 0))
self.assertEqual(result[4], (15, 3, 3, None, 0))
self.assertEqual(result[5], (16, 3, 4, None, 0))
# files
p1 = TransformSetSubDir.path(3)
# transforms
self.assertIsInstance(cv2.imread(TransformFile.path(p1, 11, 'jpg')), np.ndarray) # noqa
self.assertIsInstance(cv2.imread(TransformFile.path(p1, 12, 'jpg')), np.ndarray) # noqa
self.assertIsInstance(cv2.imread(TransformFile.path(p1, 13, 'jpg')), np.ndarray) # noqa
self.assertIsInstance(cv2.imread(TransformFile.path(p1, 14, 'jpg')), np.ndarray) # noqa
self.assertIsInstance(cv2.imread(TransformFile.path(p1, 15, 'jpg')), np.ndarray) # noqa
self.assertIsInstance(cv2.imread(TransformFile.path(p1, 16, 'jpg')), np.ndarray) # noqa
def transform_set_select_curate(self, transform_set_id, opts):
"""
This method automatically curates a transform set and rejects
transforms with width or height less than 'min-size'.
:param int transform_set_id: The transform set ID.
:param dict opts: The dict of options.
:raises: ValueError
:rtype: None
"""
if 'min-size' not in opts:
raise ValueError(
'The min-size option is required but was not supplied')
min_length = int(opts['min-size'])
transform_model = TransformModel()
length = 100
offset = 0
p1 = TransformSetSubDir.path(transform_set_id)
while True:
transforms = transform_model.list(transform_set_id,
length=length,
offset=offset)
if not transforms:
break
for transform in transforms:
p2 = TransformFile.path(p1, transform[0], 'jpg')
debug(f'Curating transform with ID {transform[0]:08d} at {p2}',
4)
h, w = cv2.imread(p2).shape[:2]
if h < min_length or w < min_length:
transform_model.update(transform[0], rejected=1)
debug(f'Transform with ID {transform[0]:08d} rejected', 4)
offset += length
def put(self, transform_set_id, transform_id):
transform_model = TransformModel()
result = transform_model.update(
transform_id, rejected=request.get_json()['rejected'])
if result is False:
abort(404)
result = transform_model.select(transform_id)
if result is None:
abort(404)
return jsonify(result)
def test_update(self):
with deepstar_path():
FrameSetModel().insert(None)
FrameModel().insert(1, 0)
TransformSetModel().insert('test', 1)
transform_model = TransformModel()
transform_model.insert(1, 1, 'test1', 0)
result = transform_model.select(1)
self.assertEqual(result, (1, 1, 1, 'test1', 0))
result = transform_model.update(1, 'test2', 1)
self.assertTrue(result)
result = transform_model.select(1)
self.assertEqual(result, (1, 1, 1, 'test2', 1))