mirror of https://github.com/open-mmlab/mmocr.git
162 lines
4.3 KiB
Python
162 lines
4.3 KiB
Python
_base_ = []
|
|
checkpoint_config = dict(interval=1)
|
|
# yapf:disable
|
|
log_config = dict(
|
|
interval=1,
|
|
hooks=[
|
|
dict(type='TextLoggerHook')
|
|
|
|
])
|
|
# yapf:enable
|
|
dist_params = dict(backend='nccl')
|
|
log_level = 'INFO'
|
|
load_from = None
|
|
resume_from = None
|
|
workflow = [('train', 1)]
|
|
|
|
# model
|
|
label_convertor = dict(
|
|
type='CTCConvertor', dict_type='DICT36', with_unknown=False, lower=True)
|
|
|
|
model = dict(
|
|
type='CRNNNet',
|
|
preprocessor=None,
|
|
backbone=dict(type='VeryDeepVgg', leaky_relu=False, input_channels=1),
|
|
encoder=None,
|
|
decoder=dict(type='CRNNDecoder', in_channels=512, rnn_flag=True),
|
|
loss=dict(type='CTCLoss'),
|
|
label_convertor=label_convertor,
|
|
pretrained=None)
|
|
|
|
train_cfg = None
|
|
test_cfg = None
|
|
|
|
# optimizer
|
|
optimizer = dict(type='Adadelta', lr=1.0)
|
|
optimizer_config = dict(grad_clip=None)
|
|
# learning policy
|
|
lr_config = dict(policy='step', step=[])
|
|
total_epochs = 5
|
|
|
|
# data
|
|
img_norm_cfg = dict(mean=[0.5], std=[0.5])
|
|
|
|
train_pipeline = [
|
|
dict(type='LoadImageFromFile', color_type='grayscale'),
|
|
dict(
|
|
type='ResizeOCR',
|
|
height=32,
|
|
min_width=100,
|
|
max_width=100,
|
|
keep_aspect_ratio=False),
|
|
dict(type='ToTensorOCR'),
|
|
dict(type='NormalizeOCR', **img_norm_cfg),
|
|
dict(
|
|
type='Collect',
|
|
keys=['img'],
|
|
meta_keys=[
|
|
'filename', 'ori_shape', 'img_shape', 'text', 'valid_ratio'
|
|
]),
|
|
]
|
|
test_pipeline = [
|
|
dict(type='LoadImageFromFile', color_type='grayscale'),
|
|
dict(
|
|
type='ResizeOCR',
|
|
height=32,
|
|
min_width=4,
|
|
max_width=None,
|
|
keep_aspect_ratio=True),
|
|
dict(type='ToTensorOCR'),
|
|
dict(type='NormalizeOCR', **img_norm_cfg),
|
|
dict(
|
|
type='Collect',
|
|
keys=['img'],
|
|
meta_keys=['filename', 'ori_shape', 'img_shape', 'valid_ratio']),
|
|
]
|
|
|
|
dataset_type = 'OCRDataset'
|
|
|
|
train_img_prefix = 'data/mixture/Syn90k/mnt/ramdisk/max/90kDICT32px'
|
|
train_ann_file = 'data/mixture/Syn90k/label.lmdb'
|
|
|
|
train1 = dict(
|
|
type=dataset_type,
|
|
img_prefix=train_img_prefix,
|
|
ann_file=train_ann_file,
|
|
loader=dict(
|
|
type='LmdbLoader',
|
|
repeat=1,
|
|
parser=dict(
|
|
type='LineStrParser',
|
|
keys=['filename', 'text'],
|
|
keys_idx=[0, 1],
|
|
separator=' ')),
|
|
pipeline=train_pipeline,
|
|
test_mode=False)
|
|
|
|
test_prefix = 'data/mixture/'
|
|
|
|
test_img_prefix1 = test_prefix + 'IIIT5K/'
|
|
test_img_prefix2 = test_prefix + 'svt/'
|
|
test_img_prefix3 = test_prefix + 'icdar_2013/'
|
|
test_img_prefix4 = test_prefix + 'icdar_2015/'
|
|
test_img_prefix5 = test_prefix + 'svtp/'
|
|
test_img_prefix6 = test_prefix + 'ct80/'
|
|
|
|
test_ann_file1 = test_prefix + 'IIIT5K/test_label.txt'
|
|
test_ann_file2 = test_prefix + 'svt/test_label.txt'
|
|
test_ann_file3 = test_prefix + 'icdar_2013/test_label_1015.txt'
|
|
test_ann_file4 = test_prefix + 'icdar_2015/test_label.txt'
|
|
test_ann_file5 = test_prefix + 'svtp/test_label.txt'
|
|
test_ann_file6 = test_prefix + 'ct80/test_label.txt'
|
|
|
|
test1 = dict(
|
|
type=dataset_type,
|
|
img_prefix=test_img_prefix1,
|
|
ann_file=test_ann_file1,
|
|
loader=dict(
|
|
type='HardDiskLoader',
|
|
repeat=1,
|
|
parser=dict(
|
|
type='LineStrParser',
|
|
keys=['filename', 'text'],
|
|
keys_idx=[0, 1],
|
|
separator=' ')),
|
|
pipeline=test_pipeline,
|
|
test_mode=True)
|
|
|
|
test2 = {key: value for key, value in test1.items()}
|
|
test2['img_prefix'] = test_img_prefix2
|
|
test2['ann_file'] = test_ann_file2
|
|
|
|
test3 = {key: value for key, value in test1.items()}
|
|
test3['img_prefix'] = test_img_prefix3
|
|
test3['ann_file'] = test_ann_file3
|
|
|
|
test4 = {key: value for key, value in test1.items()}
|
|
test4['img_prefix'] = test_img_prefix4
|
|
test4['ann_file'] = test_ann_file4
|
|
|
|
test5 = {key: value for key, value in test1.items()}
|
|
test5['img_prefix'] = test_img_prefix5
|
|
test5['ann_file'] = test_ann_file5
|
|
|
|
test6 = {key: value for key, value in test1.items()}
|
|
test6['img_prefix'] = test_img_prefix6
|
|
test6['ann_file'] = test_ann_file6
|
|
|
|
data = dict(
|
|
samples_per_gpu=64,
|
|
workers_per_gpu=4,
|
|
train=dict(type='ConcatDataset', datasets=[train1]),
|
|
val=dict(
|
|
type='ConcatDataset',
|
|
datasets=[test1, test2, test3, test4, test5, test6]),
|
|
test=dict(
|
|
type='ConcatDataset',
|
|
datasets=[test1, test2, test3, test4, test5, test6]))
|
|
|
|
evaluation = dict(interval=1, metric='acc')
|
|
|
|
cudnn_benchmark = True
|