text: # -*- coding: utf-8 -*-
  # @Time    : 2019/1/3 17:40
  # data config
  exp_name = "ICDAR15"
  trainroot = '/data/glusterfs_cv_04/11121171/data/ICDAR2015/'
  testroot = '/data/glusterfs_cv_04/11121171/data/ICDAR2015/'
  workspace_dir = '/data/glusterfs_cv_04/11121171/CVPR_Text/PSENet/workspace'
  workspace = ""
  gt_name = "icd15_gt.zip"
  data_shape = 640
  
  # train config
  gpu_id = '0,1'
  workers = 10
  start_epoch = 0
  epochs = 600
  
  train_batch_size = 16
  
  lr = 1e-4
  end_lr = 1e-7
  lr_gamma = 0.1
  lr_decay_step = [100,200]
  weight_decay = 5e-4
  warm_up_epoch = 6
  warm_up_lr = lr * lr_gamma
  
  display_input_images = False
  display_output_images = False
  display_interval = 10
  show_images_interval = 50
  save_interval=5
  
  pretrained = True
  restart_training = True
  checkpoint = ''
  
  # net config
  backbone = 'resnet50'
  Lambda = 0.7
  n = 6
  m = 0.5
  OHEM_ratio = 3
  scale = 1
  # random seed
  seed = 2
  
  
  def print():
      from pprint import pformat
      tem_d = {}
      for k, v in globals().items():
          if not k.startswith('_') and not callable(v):
              tem_d[k] = v
      return pformat(tem_d)
  