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rec_r31_robustscanner.yml
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rec_r31_robustscanner.yml
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Global:
use_gpu: true
epoch_num: 5
log_smooth_window: 20
print_batch_step: 20
save_model_dir: ./output/rec/rec_r31_robustscanner/
save_epoch_step: 1
# evaluation is run every 2000 iterations
eval_batch_step: [0, 2000]
cal_metric_during_train: True
pretrained_model:
checkpoints:
save_inference_dir:
use_visualdl: False
infer_img: ./inference/rec_inference
# for data or label process
character_dict_path: ppocr/utils/dict90.txt
max_text_length: &max_text_length 40
infer_mode: False
use_space_char: False
rm_symbol: True
save_res_path: ./output/rec/predicts_robustscanner.txt
Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
name: Piecewise
decay_epochs: [3, 4]
values: [0.001, 0.0001, 0.00001]
regularizer:
name: 'L2'
factor: 0
Architecture:
model_type: rec
algorithm: RobustScanner
Transform:
Backbone:
name: ResNet31
init_type: KaimingNormal
Head:
name: RobustScannerHead
enc_outchannles: 128
hybrid_dec_rnn_layers: 2
hybrid_dec_dropout: 0
position_dec_rnn_layers: 2
start_idx: 91
mask: True
padding_idx: 92
encode_value: False
max_text_length: *max_text_length
Loss:
name: SARLoss
PostProcess:
name: SARLabelDecode
Metric:
name: RecMetric
is_filter: True
Train:
dataset:
name: LMDBDataSet
data_dir: ./train_data/data_lmdb_release/training/
transforms:
- DecodeImage: # load image
img_mode: BGR
channel_first: False
- SARLabelEncode: # Class handling label
- RobustScannerRecResizeImg:
image_shape: [3, 48, 48, 160] # h:48 w:[48,160]
width_downsample_ratio: 0.25
max_text_length: *max_text_length
- KeepKeys:
keep_keys: ['image', 'label', 'valid_ratio', 'word_positons'] # dataloader will return list in this order
loader:
shuffle: True
batch_size_per_card: 64
drop_last: True
num_workers: 8
use_shared_memory: False
Eval:
dataset:
name: LMDBDataSet
data_dir: ./train_data/data_lmdb_release/evaluation/
transforms:
- DecodeImage: # load image
img_mode: BGR
channel_first: False
- SARLabelEncode: # Class handling label
- RobustScannerRecResizeImg:
image_shape: [3, 48, 48, 160]
max_text_length: *max_text_length
width_downsample_ratio: 0.25
- KeepKeys:
keep_keys: ['image', 'label', 'valid_ratio', 'word_positons'] # dataloader will return list in this order
loader:
shuffle: False
drop_last: False
batch_size_per_card: 64
num_workers: 4
use_shared_memory: False