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# Text Recognition Training set, including: | |
# Synthetic Datasets: SynthText, Syn90k | |
# Both annotations are filtered so that | |
# only alphanumeric terms are left | |
train_root = 'data/mixture' | |
train_img_prefix1 = f'{train_root}/Syn90k/mnt/ramdisk/max/90kDICT32px' | |
train_ann_file1 = f'{train_root}/Syn90k/label.lmdb' | |
train1 = dict( | |
type='OCRDataset', | |
img_prefix=train_img_prefix1, | |
ann_file=train_ann_file1, | |
loader=dict( | |
type='AnnFileLoader', | |
repeat=1, | |
file_format='lmdb', | |
parser=dict(type='LineJsonParser', keys=['filename', 'text'])), | |
pipeline=None, | |
test_mode=False) | |
train_img_prefix2 = f'{train_root}/SynthText/' + \ | |
'synthtext/SynthText_patch_horizontal' | |
train_ann_file2 = f'{train_root}/SynthText/alphanumeric_label.lmdb' | |
train2 = {key: value for key, value in train1.items()} | |
train2['img_prefix'] = train_img_prefix2 | |
train2['ann_file'] = train_ann_file2 | |
train_list = [train1, train2] | |