rec_mv3_none_bilstm_ctc.yml

Global:
  algorithm: CRNN
  use_gpu: true
  epoch_num: 72
  log_smooth_window: 20
  print_batch_step: 10
  save_model_dir: output/rec_CRNN
  save_epoch_step: 3
  eval_batch_step: 2000
  train_batch_size_per_card: 256
  test_batch_size_per_card: 256
  image_shape: [3, 32, 100]
  max_text_length: 25
  character_type: en
  loss_type: ctc
  reader_yml: ./configs/rec/rec_benchmark_reader.yml
  pretrain_weights:
  checkpoints:
  save_inference_dir:
  infer_img:
  
Architecture:
  function: ppocr.modeling.architectures.rec_model,RecModel

Backbone:
  function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3
  scale: 0.5
  model_name: large
 
Head:
  function: ppocr.modeling.heads.rec_ctc_head,CTCPredict
  encoder_type: rnn
  SeqRNN:
    hidden_size: 96
    
Loss:
  function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss

Optimizer:
  function: ppocr.optimizer,AdamDecay
  base_lr: 0.001
  beta1: 0.9
  beta2: 0.999