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Global:
device: gpu
epoch_num: 20
log_smooth_window: 20
print_batch_step: 10
output_dir: ./output/rec/u14m_filter/resnet45_trans_abinet_lang/
eval_epoch_step: [0, 1]
eval_batch_step: [0, 500]
cal_metric_during_train: True
pretrained_model:
# ./openocr_nolang_abinet_lang.pth
checkpoints:
use_tensorboard: false
infer_img:
# for data or label process
character_dict_path: ./tools/utils/EN_symbol_dict.txt
max_text_length: 25
use_space_char: False
save_res_path: ./output/rec/u14m_filter/predicts_resnet45_trans_abinet_lang.txt
grad_clip_val: 20
use_amp: True
Optimizer:
name: Adam
lr: 0.000267
weight_decay: 0.0
filter_bias_and_bn: False
LRScheduler:
name: MultiStepLR
milestones: [12]
gamma: 0.1
Architecture:
model_type: rec
algorithm: ABINet
Transform:
Encoder:
name: ResNet45
in_channels: 3
strides: [2, 1, 2, 1, 1]
Decoder:
name: ABINetDecoder
iter_size: 3
Loss:
name: ABINetLoss
PostProcess:
name: ABINetLabelDecode
Metric:
name: RecMetric
main_indicator: acc
is_filter: True
Train:
dataset:
name: LMDBDataSet
data_dir: ../Union14M-L-LMDB-Filtered
transforms:
- DecodeImagePIL: # load image
img_mode: RGB
- PARSeqAugPIL:
- ABINetLabelEncode:
- RecTVResize:
image_shape: [32, 128]
padding: False
- KeepKeys:
keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
loader:
shuffle: True
batch_size_per_card: 256
drop_last: True
num_workers: 4
Eval:
dataset:
name: LMDBDataSet
data_dir: ../evaluation
transforms:
- DecodeImagePIL: # load image
img_mode: RGB
- ABINetLabelEncode:
- RecTVResize:
image_shape: [32, 128]
padding: False
- KeepKeys:
keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
loader:
shuffle: False
drop_last: False
batch_size_per_card: 256
num_workers: 2
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