rec_mv3_tps_bilstm_attn.yml 1.1 KB
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Global:
  algorithm: RARE
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  use_gpu: true
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  epoch_num: 72
  log_smooth_window: 20
  print_batch_step: 10
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  save_model_dir: output/rec_RARE
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  save_epoch_step: 3
  eval_batch_step: 2000
  train_batch_size_per_card: 256
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  drop_last: true
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  test_batch_size_per_card: 256
  image_shape: [3, 32, 100]
  max_text_length: 25
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  character_type: en
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  loss_type: attention
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  tps: true
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  reader_yml: ./configs/rec/rec_benchmark_reader.yml
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  pretrain_weights:
  checkpoints:
  save_inference_dir:
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  infer_img:


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Architecture:
  function: ppocr.modeling.architectures.rec_model,RecModel

TPS:
  function: ppocr.modeling.stns.tps,TPS
  num_fiducial: 20
  loc_lr: 0.1
  model_name: small
  
Backbone:
  function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3
  scale: 0.5
  model_name: large
 
Head:
  function: ppocr.modeling.heads.rec_attention_head,AttentionPredict
  encoder_type: rnn
  SeqRNN:
    hidden_size: 96
  Attention:
    decoder_size: 96
    word_vector_dim: 96
  
Loss:
  function: ppocr.modeling.losses.rec_attention_loss,AttentionLoss
  
Optimizer:
  function: ppocr.optimizer,AdamDecay
  base_lr: 0.001
  beta1: 0.9
  beta2: 0.999