text: # -*- coding:utf-8 -*-
  # power by Mr.Li
  # 设置默认参数
  class DefaultConfig():
      env = 'YOLOv1'  # visdom 环境的名字
      # model = 'NetWork'  # 使用的模型，名字必须与models/__init__.py中的名字一致
      file_root = '/home/zhuhui/data/VOCdevkit/VOC2012/JPEGImages/'  #VOC2012的训练集
      test_root = '/home/zhuhui/data/VOCdevkit/VOC2007/JPEGImages/'   #VOC2007的测试集
      train_Annotations = '/home/zhuhui/data/VOCdevkit/VOC2012/Annotations/'
      voc_2007test='/home/bobo/PycharmProjects/torchProjectss/YOLOv1ByBobo/data/voc2007test.txt'
      voc_2012train='/home/bobo/PycharmProjects/torchProjectss/YOLOv1ByBobo/data/voc2012train.txt'
  
      test_img_dir='/home/bobo/PycharmProjects/torchProjectss/YOLOv1ByBobo/testImgs/a.jpg'
      result_img_dir='/home/bobo/PycharmProjects/torchProjectss/YOLOv1ByBobo/testImgs/result_a.jpg'
  
  
  
      batch_size = 32  # batch size
      use_gpu = True  # user GPU or not
      num_workers = 4  # how many workers for loading data  加载数据时的线程
      print_freq = 20  # print info every N batch
  
      # load_model_path =None  # 加载预训练的模型的路径，为None代表不加载
      best_test_loss_model_path= '/home/bobo/PycharmProjects/torchProjectss/YOLOv1ByBobo/checkpoint/yolo_val_best.pth'
      current_epoch_model_path='/home/bobo/PycharmProjects/torchProjectss/YOLOv1ByBobo/checkpoint/yolo_bobo.pth'
      load_model_path = None  # 加载预训练的模型的路径，为None代表不加载
      num_epochs = 120   #训练的epoch次数
      learning_rate = 0.001  # initial learning rate
      lr_decay = 0.5  # when val_loss increase, lr = lr*lr_decay
      momentum=0.95
      weight_decay =5e-4  # 损失函数
      # VOC的类别
      VOC_CLASSES = (  # always index 0
          'aeroplane', 'bicycle', 'bird', 'boat',
          'bottle', 'bus', 'car', 'cat', 'chair',
          'cow', 'diningtable', 'dog', 'horse',
          'motorbike', 'person', 'pottedplant',
          'sheep', 'sofa', 'train', 'tvmonitor')
  
  
   #初始化该类的一个对象
  opt=DefaultConfig()