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[Config] SAR seq config (#1215)

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liukuikun 2022-07-27 20:03:02 +08:00 committed by GitHub
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2 changed files with 48 additions and 26 deletions
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2
configs/_base_/recog_datasets/ST_SA_MJ_real_train.py
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@ -6,7 +6,7 @@ data_root = 'data/rec'
train_img_prefix1 = 'icdar_2011' train_img_prefix1 = 'icdar_2011'
train_img_prefix2 = 'icdar_2013' train_img_prefix2 = 'icdar_2013'
train_img_prefix3 = 'icdar_2015' train_img_prefix3 = 'icdar_2015'
train_img_prefix4 = 'coco_text' train_img_prefix4 = 'coco_text_v1'
train_img_prefix5 = 'IIIT5K' train_img_prefix5 = 'IIIT5K'
train_img_prefix6 = 'synthtext_add' train_img_prefix6 = 'synthtext_add'
train_img_prefix7 = 'SynthText/synthtext/SynthText_patch_horizontal' train_img_prefix7 = 'SynthText/synthtext/SynthText_patch_horizontal'

72
configs/textrecog/sar/sar_r31_sequential_decoder_academic.py
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@ -7,13 +7,15 @@ _base_ = [
] ]
# dataset settings # dataset settings
train_list = {{_base_.train_list}}
test_list = {{_base_.test_list}}
file_client_args = dict(backend='disk') file_client_args = dict(backend='disk')
default_hooks = dict(logger=dict(type='LoggerHook', interval=100)) default_hooks = dict(logger=dict(type='LoggerHook', interval=100))
train_pipeline = [ train_pipeline = [
dict(type='LoadImageFromFile', file_client_args=file_client_args), dict(
type='LoadImageFromFile',
file_client_args=file_client_args,
ignore_empty=True,
min_size=5),
dict(type='LoadOCRAnnotations', with_text=True), dict(type='LoadOCRAnnotations', with_text=True),
dict(type='Resize', scale=(160, 48), keep_ratio=False), dict(type='Resize', scale=(160, 48), keep_ratio=False),
dict( dict(
@ -36,32 +38,52 @@ test_pipeline = [
'instances')) 'instances'))
] ]
# dataset settings
ic11_rec_train = _base_.ic11_rec_train
ic13_rec_train = _base_.ic13_rec_train
ic15_rec_train = _base_.ic15_rec_train
cocov1_rec_train = _base_.cocov1_rec_train
iiit5k_rec_train = _base_.iiit5k_rec_train
st_add_rec_train = _base_.st_add_rec_train
st_rec_train = _base_.st_rec_train
mj_rec_trian = _base_.mj_rec_trian
ic11_rec_train.pipeline = train_pipeline
ic13_rec_train.pipeline = train_pipeline
ic15_rec_train.pipeline = train_pipeline
cocov1_rec_train.pipeline = train_pipeline
iiit5k_rec_train.pipeline = train_pipeline
st_add_rec_train.pipeline = train_pipeline
st_rec_train.pipeline = train_pipeline
mj_rec_trian.pipeline = train_pipeline
repeat_ic11 = dict(type='RepeatDataset', dataset=ic11_rec_train, times=20)
repeat_ic13 = dict(type='RepeatDataset', dataset=ic13_rec_train, times=20)
repeat_ic15 = dict(type='RepeatDataset', dataset=ic15_rec_train, times=20)
repeat_cocov1 = dict(type='RepeatDataset', dataset=cocov1_rec_train, times=20)
repeat_iiit5k = dict(type='RepeatDataset', dataset=iiit5k_rec_train, times=20)
train_dataloader = dict( train_dataloader = dict(
batch_size=64, batch_size=64,
num_workers=8, num_workers=16,
persistent_workers=True, persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=True), sampler=dict(type='DefaultSampler', shuffle=True),
dataset=dict( dataset=dict(
type='ConcatDataset', datasets=train_list, pipeline=train_pipeline)) type='ConcatDataset',
datasets=[
repeat_ic11, repeat_ic13, repeat_ic15, repeat_cocov1,
repeat_iiit5k, st_add_rec_train, st_rec_train, mj_rec_trian
]))
val_dataloader = dict( test_cfg = dict(type='MultiTestLoop')
batch_size=1, val_cfg = dict(type='MultiValLoop')
num_workers=4, val_dataloader = _base_.val_dataloader
persistent_workers=True, test_dataloader = _base_.test_dataloader
drop_last=False, for dataloader in test_dataloader:
sampler=dict(type='DefaultSampler', shuffle=False), dataloader['dataset']['pipeline'] = test_pipeline
dataset=dict( for dataloader in val_dataloader:
type='ConcatDataset', datasets=test_list, pipeline=test_pipeline)) dataloader['dataset']['pipeline'] = test_pipeline
test_dataloader = val_dataloader
val_evaluator = [
dict(
type='WordMetric', mode=['exact', 'ignore_case',
'ignore_case_symbol']),
dict(type='CharMetric')
]
test_evaluator = val_evaluator
visualizer = dict(type='TextRecogLocalVisualizer', name='visualizer') visualizer = dict(type='TextRecogLocalVisualizer', name='visualizer')
dictionary = dict( dictionary = dict(
type='Dictionary', type='Dictionary',
dict_file='dicts/english_digits_symbols.txt', dict_file='dicts/english_digits_symbols.txt',
@ -90,6 +112,6 @@ model = dict(
pred_concat=True, pred_concat=True,
postprocessor=dict(type='AttentionPostprocessor'), postprocessor=dict(type='AttentionPostprocessor'),
module_loss=dict( module_loss=dict(
type='CEModuleLoss', ignore_first_char=True, reduction='mean')), type='CEModuleLoss', ignore_first_char=True, reduction='mean'),
dictionary=dictionary, dictionary=dictionary,
max_seq_len=30) max_seq_len=30))