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| # This configuration prepares the ICDAR13 857 and 1015 | |
| # version, and uses ICDAR13 1015 version by default. | |
| # You may uncomment the lines if you want to you the original version, | |
| # which contains 1095 samples. | |
| # You can check out the generated base config and use the 857 | |
| # version by using its corresponding config variables in your model. | |
| data_root = 'data/icdar2013' | |
| cache_path = 'data/cache' | |
| train_preparer = dict( | |
| obtainer=dict( | |
| type='NaiveDataObtainer', | |
| cache_path=cache_path, | |
| files=[ | |
| dict( | |
| url='https://rrc.cvc.uab.es/downloads/' | |
| 'Challenge2_Training_Task3_Images_GT.zip', | |
| save_name='ic13_textrecog_train_img_gt.zip', | |
| md5='6f0dbc823645968030878df7543f40a4', | |
| content=['image'], | |
| mapping=[ | |
| # ['ic13_textrecog_train_img_gt/gt.txt', | |
| # 'annotations/train.txt'], | |
| ['ic13_textrecog_train_img_gt', 'textrecog_imgs/train'] | |
| ]), | |
| dict( | |
| url='https://download.openmmlab.com/mmocr/data/1.x/recog/' | |
| 'icdar_2013/train_labels.json', | |
| save_name='ic13_train_labels.json', | |
| md5='008fcd0056e72c4cf3064fb4d1fce81b', | |
| content=['annotation'], | |
| mapping=[['ic13_train_labels.json', 'textrecog_train.json']]), | |
| ])) | |
| # Note that we offer two versions of test set annotations as follows.Please | |
| # choose one of them to download and comment the other. By default, we use the | |
| # second one. | |
| # 1. The original official annotation, which contains 1095 test | |
| # samples. | |
| # Uncomment the test_preparer if you want to use the original 1095 version. | |
| # test_preparer = dict( | |
| # obtainer=dict( | |
| # type='NaiveDataObtainer', | |
| # cache_path=cache_path, | |
| # files=[ | |
| # dict( | |
| # url='https://rrc.cvc.uab.es/downloads/' | |
| # 'Challenge2_Test_Task3_Images.zip', | |
| # save_name='ic13_textrecog_test_img.zip', | |
| # md5='3206778eebb3a5c5cc15c249010bf77f', | |
| # split=['test'], | |
| # content=['image'], | |
| # mapping=[['ic13_textrecog_test_img', | |
| # 'textrecog_imgs/test']]), | |
| # dict( | |
| # url='https://rrc.cvc.uab.es/downloads/' | |
| # 'Challenge2_Test_Task3_GT.txt', | |
| # save_name='ic13_textrecog_test_gt.txt', | |
| # md5='2634060ed8fe6e7a4a9b8d68785835a1', | |
| # split=['test'], | |
| # content=['annotation'], | |
| # mapping=[[ | |
| # 'ic13_textrecog_test_gt.txt', 'annotations/test.txt' | |
| # ]]), # noqa | |
| # # The 857 version further pruned words shorter than 3 characters. | |
| # dict( | |
| # url='https://download.openmmlab.com/mmocr/data/1.x/recog/' | |
| # 'icdar_2013/textrecog_test_857.json', | |
| # save_name='textrecog_test_857.json', | |
| # md5='3bed3985b0c51a989ad4006f6de8352b', | |
| # split=['test'], | |
| # content=['annotation'], | |
| # ), | |
| # ]), | |
| # gatherer=dict(type='MonoGatherer', ann_name='test.txt'), | |
| # parser=dict( | |
| # type='ICDARTxtTextRecogAnnParser', separator=', ', | |
| # format='img, text'), # noqa | |
| # packer=dict(type='TextRecogPacker'), | |
| # dumper=dict(type='JsonDumper'), | |
| # ) | |
| # 2. The widely-used version for academic purpose, which filters | |
| # out words with non-alphanumeric characters. This version contains | |
| # 1015 test samples. | |
| test_preparer = dict( | |
| obtainer=dict( | |
| type='NaiveDataObtainer', | |
| cache_path=cache_path, | |
| files=[ | |
| dict( | |
| url='https://rrc.cvc.uab.es/downloads/' | |
| 'Challenge2_Test_Task3_Images.zip', | |
| save_name='ic13_textrecog_test_img.zip', | |
| md5='3206778eebb3a5c5cc15c249010bf77f', | |
| split=['test'], | |
| content=['image'], | |
| mapping=[['ic13_textrecog_test_img', 'textrecog_imgs/test']]), | |
| dict( | |
| url='https://download.openmmlab.com/mmocr/data/1.x/recog/' | |
| 'icdar_2013/textrecog_test_1015.json', | |
| save_name='textrecog_test.json', | |
| md5='68fdd818f63df8b93dc952478952009a', | |
| split=['test'], | |
| content=['annotation'], | |
| ), | |
| # The 857 version further pruned words shorter than 3 characters. | |
| dict( | |
| url='https://download.openmmlab.com/mmocr/data/1.x/recog/' | |
| 'icdar_2013/textrecog_test_857.json', | |
| save_name='textrecog_test_857.json', | |
| md5='3bed3985b0c51a989ad4006f6de8352b', | |
| split=['test'], | |
| content=['annotation'], | |
| ), | |
| ])) | |
| config_generator = dict( | |
| type='TextRecogConfigGenerator', | |
| test_anns=[ | |
| dict(ann_file='textrecog_test.json'), | |
| dict(dataset_postfix='857', ann_file='textrecog_test_857.json') | |
| ]) | |