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# The transcription of NAF dataset is annotated from Tessaract OCR, which is | |
# not accurate. The test/valid set ones were hand corrected, but the train set | |
# was only hand corrected a little. They aren't very good results. Better | |
# not to use them for recognition and text spotting. | |
_base_ = ['textdet.py'] | |
_base_.train_preparer.parser.update(dict(ignore=['¿', '§'], det=False)) | |
_base_.test_preparer.parser.update(dict(ignore=['¿', '§'], det=False)) | |
_base_.val_preparer.parser.update(dict(ignore=['¿', '§'], det=False)) | |
_base_.train_preparer.packer.type = 'TextRecogCropPacker' | |
_base_.test_preparer.packer.type = 'TextRecogCropPacker' | |
_base_.val_preparer.packer.type = 'TextRecogCropPacker' | |
_base_.train_preparer.gatherer.img_dir = 'textdet_imgs/train' | |
_base_.test_preparer.gatherer.img_dir = 'textdet_imgs/test' | |
_base_.val_preparer.gatherer.img_dir = 'textdet_imgs/val' | |
config_generator = dict( | |
type='TextRecogConfigGenerator', | |
val_anns=[dict(ann_file='textrecog_val.json', dataset_postfix='')]) | |