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51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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import unittest
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import torch
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from tests.ut_config import SMALL_OCR_CLS_DATA
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from easycv.datasets.builder import build_dataset
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class OCRClsDatasetTest(unittest.TestCase):
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def setUp(self):
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print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
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def _get_dataset(self):
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data_root = SMALL_OCR_CLS_DATA
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data_train_list = os.path.join(data_root, 'label.txt')
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pipeline = [
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dict(type='RecAug', use_tia=False),
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dict(type='ClsResizeImg', img_shape=(3, 48, 192)),
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dict(type='MMToTensor'),
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dict(
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type='Collect', keys=['img', 'label'], meta_keys=['img_path'])
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]
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data = dict(
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train=dict(
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type='OCRClsDataset',
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data_source=dict(
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type='OCRClsSource',
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label_file=data_train_list,
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data_dir=SMALL_OCR_CLS_DATA + '/img',
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label_list=['0', '180'],
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),
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pipeline=pipeline))
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dataset = build_dataset(data['train'])
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return dataset
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def test_default(self):
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dataset = self._get_dataset()
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for _, batch in enumerate(dataset):
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img, target = batch['img'], batch['label']
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self.assertEqual(img.shape, torch.Size([3, 48, 192]))
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self.assertIn(target, list(range(2)))
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break
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if __name__ == '__main__':
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unittest.main()
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