cls_mv3.yml

Global:
  algorithm: CLS
  use_gpu: False
  epoch_num: 100
  log_smooth_window: 20
  print_batch_step: 100
  save_model_dir: output/cls_mv3
  save_epoch_step: 3
  eval_batch_step: 500
  train_batch_size_per_card: 512
  test_batch_size_per_card: 512
  image_shape: [3, 48, 192]
  label_list: ['0','180']
  distort: True
  reader_yml: ./configs/cls/cls_reader.yml
  pretrain_weights:
  checkpoints:
  save_inference_dir:
  infer_img:
  
Architecture:
  function: ppocr.modeling.architectures.cls_model,ClsModel

Backbone:
  function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3
  scale: 0.35
  model_name: small
 
Head:
  function: ppocr.modeling.heads.cls_head,ClsHead
  class_dim: 2

Loss:
  function: ppocr.modeling.losses.cls_loss,ClsLoss

Optimizer:
  function: ppocr.optimizer,AdamDecay
  base_lr: 0.001
  beta1: 0.9
  beta2: 0.999
  decay:
    function: cosine_decay
    step_each_epoch: 1169
    total_epoch: 100