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