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dictionary = dict(
type='Dictionary',
dict_file='{{ fileDirname }}/../../../dicts/english_digits_symbols.txt',
with_start=True,
with_end=True,
same_start_end=True,
with_padding=True,
with_unknown=True)
model = dict(
type='SARNet',
data_preprocessor=dict(
type='TextRecogDataPreprocessor',
mean=[127, 127, 127],
std=[127, 127, 127]),
backbone=dict(type='ResNet31OCR'),
encoder=dict(
type='SAREncoder',
enc_bi_rnn=False,
enc_do_rnn=0.1,
enc_gru=False,
),
decoder=dict(
type='ParallelSARDecoder',
enc_bi_rnn=False,
dec_bi_rnn=False,
dec_do_rnn=0,
dec_gru=False,
pred_dropout=0.1,
d_k=512,
pred_concat=True,
postprocessor=dict(type='AttentionPostprocessor'),
module_loss=dict(
type='CEModuleLoss', ignore_first_char=True, reduction='mean'),
dictionary=dictionary,
max_seq_len=30))
train_pipeline = [
dict(type='LoadImageFromFile', ignore_empty=True, min_size=2),
dict(type='LoadOCRAnnotations', with_text=True),
dict(
type='RescaleToHeight',
height=48,
min_width=48,
max_width=160,
width_divisor=4),
dict(type='PadToWidth', width=160),
dict(
type='PackTextRecogInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='RescaleToHeight',
height=48,
min_width=48,
max_width=160,
width_divisor=4),
dict(type='PadToWidth', width=160),
# add loading annotation after ``Resize`` because ground truth
# does not need to do resize data transform
dict(type='LoadOCRAnnotations', with_text=True),
dict(
type='PackTextRecogInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio'))
]
tta_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='TestTimeAug',
transforms=[
[
dict(
type='ConditionApply',
true_transforms=[
dict(
type='ImgAugWrapper',
args=[dict(cls='Rot90', k=0, keep_size=False)])
],
condition="results['img_shape'][1]<results['img_shape'][0]"
),
dict(
type='ConditionApply',
true_transforms=[
dict(
type='ImgAugWrapper',
args=[dict(cls='Rot90', k=1, keep_size=False)])
],
condition="results['img_shape'][1]<results['img_shape'][0]"
),
dict(
type='ConditionApply',
true_transforms=[
dict(
type='ImgAugWrapper',
args=[dict(cls='Rot90', k=3, keep_size=False)])
],
condition="results['img_shape'][1]<results['img_shape'][0]"
),
],
[
dict(
type='RescaleToHeight',
height=48,
min_width=48,
max_width=160,
width_divisor=4)
],
[dict(type='PadToWidth', width=160)],
# add loading annotation after ``Resize`` because ground truth
# does not need to do resize data transform
[dict(type='LoadOCRAnnotations', with_text=True)],
[
dict(
type='PackTextRecogInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape',
'valid_ratio'))
]
])
]
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