def METHOD_NAME(self):
    init_default_scope('mmocr')
    dataset = OCRDataset
    # create dataset_a
    data_info = dict(filename='img_1.jpg', height=720, width=1280)
    dataset.parse_data_info = MagicMock(return_value=data_info)
    self.dataset_a = dataset(
        data_root=osp.join(
            osp.dirname(__file__), '../data/det_toy_dataset'),
        data_prefix=dict(img_path='imgs'),
        ann_file='textdet_test.json')
    self.dataset_a_with_pipeline = dataset(
        data_root=osp.join(
            osp.dirname(__file__), '../data/det_toy_dataset'),
        data_prefix=dict(img_path='imgs'),
        ann_file='textdet_test.json',
        pipeline=[dict(type='MockTransform', return_value=1)])
    # create dataset_b
    data_info = dict(filename='img_2.jpg', height=720, width=1280)
    dataset.parse_data_info = MagicMock(return_value=data_info)
    self.dataset_b = dataset(
        data_root=osp.join(
            osp.dirname(__file__), '../data/det_toy_dataset'),
        data_prefix=dict(img_path='imgs'),
        ann_file='textdet_test.json')
    self.dataset_b_with_pipeline = dataset(
        data_root=osp.join(
            osp.dirname(__file__), '../data/det_toy_dataset'),
        data_prefix=dict(img_path='imgs'),
        ann_file='textdet_test.json',
        pipeline=[dict(type='MockTransform', return_value=2)])