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a4237ad568
* support multi pipelines * support different pipelines * fix * fix replace_image_to_tensor * remove redundant check * update * add copyright * not in-place modify
61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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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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# pipeline is 1d list
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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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# pipeline is None
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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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# pipeline is 2d list
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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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