add db mv3 yml for v1.1

configs/det/det_mv3_db.yml

@@ -24,7 +24,6 @@ Backbone:
   function: ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3
   scale: 0.5
   model_name: large
-  disable_se: true
 
 Head:
   function: ppocr.modeling.heads.det_db_head,DBHead

configs/det/det_mv3_db_v1.1.yml

@@ -0,0 +1,55 @@
+Global:
+  algorithm: DB
+  use_gpu: true
+  epoch_num: 1200
+  log_smooth_window: 20
+  print_batch_step: 2
+  save_model_dir: ./output/det_db/
+  save_epoch_step: 200
+  # evaluation is run every 5000 iterations after the 4000th iteration
+  eval_batch_step: [4000, 5000]
+  train_batch_size_per_card: 16
+  test_batch_size_per_card: 16
+  image_shape: [3, 640, 640]
+  reader_yml: ./configs/det/det_db_icdar15_reader.yml
+  pretrain_weights: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/
+  checkpoints:
+  save_res_path: ./output/det_db/predicts_db.txt
+  save_inference_dir:
+  
+Architecture:
+  function: ppocr.modeling.architectures.det_model,DetModel
+
+Backbone:
+  function: ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3
+  scale: 0.5
+  model_name: large
+  disable_se: true
+
+Head:
+  function: ppocr.modeling.heads.det_db_head,DBHead
+  model_name: large
+  k: 50
+  inner_channels: 96
+  out_channels: 2
+
+Loss:
+  function: ppocr.modeling.losses.det_db_loss,DBLoss
+  balance_loss: true
+  main_loss_type: DiceLoss
+  alpha: 5
+  beta: 10
+  ohem_ratio: 3
+
+Optimizer:
+  function: ppocr.optimizer,AdamDecay
+  base_lr: 0.001
+  beta1: 0.9
+  beta2: 0.999
+
+PostProcess:
+  function: ppocr.postprocess.db_postprocess,DBPostProcess
+  thresh: 0.3
+  box_thresh: 0.6
+  max_candidates: 1000
+  unclip_ratio: 1.5