# Copyright (c) OpenMMLab. All rights reserved. import copy from mmocr.datasets import UniformConcatDataset from mmocr.utils import list_from_file def test_dataset_warpper(): pipeline1 = [dict(type='LoadImageFromFile')] pipeline2 = [dict(type='LoadImageFromFile'), dict(type='ColorJitter')] img_prefix = 'tests/data/ocr_toy_dataset/imgs' ann_file = 'tests/data/ocr_toy_dataset/label.txt' train1 = dict( type='OCRDataset', img_prefix=img_prefix, ann_file=ann_file, loader=dict( type='HardDiskLoader', repeat=1, parser=dict( type='LineStrParser', keys=['filename', 'text'], keys_idx=[0, 1], separator=' ')), pipeline=None, test_mode=False) train2 = {key: value for key, value in train1.items()} train2['pipeline'] = pipeline2 # pipeline is 1d list copy_train1 = copy.deepcopy(train1) copy_train2 = copy.deepcopy(train2) tmp_dataset = UniformConcatDataset( datasets=[copy_train1, copy_train2], pipeline=pipeline1, force_apply=True) assert len(tmp_dataset) == 2 * len(list_from_file(ann_file)) assert len(tmp_dataset.datasets[0].pipeline.transforms) == len( tmp_dataset.datasets[1].pipeline.transforms) # pipeline is None copy_train2 = copy.deepcopy(train2) tmp_dataset = UniformConcatDataset(datasets=[copy_train2], pipeline=None) assert len(tmp_dataset.datasets[0].pipeline.transforms) == len(pipeline2) copy_train2 = copy.deepcopy(train2) tmp_dataset = UniformConcatDataset( datasets=[[copy_train2], [copy_train2]], pipeline=None) assert len(tmp_dataset.datasets[0].pipeline.transforms) == len(pipeline2) # pipeline is 2d list copy_train1 = copy.deepcopy(train1) copy_train2 = copy.deepcopy(train2) tmp_dataset = UniformConcatDataset( datasets=[[copy_train1], [copy_train2]], pipeline=[pipeline1, pipeline2]) assert len(tmp_dataset.datasets[0].pipeline.transforms) == len(pipeline1)