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# 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)
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