Example #1
0
    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
Example #2
0
    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)
Example #4
0
    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))