import os total_path = '/data2/liudan/ocr/' # 删除已存在文件路径 path_data = os.path.join(total_path, 'data') # 备份total_data路径 old_file_path = os.path.join(total_path, 'field_data') new_file_path = os.path.join(total_path, 'data/total_data') # 划分数据集路径 dataset_path = os.path.join(total_path, 'data/total_data') train_set_save_path = os.path.join(total_path, 'data/train') val_set_save_path = os.path.join(total_path, 'data/val') # batch_process路径 dir = os.path.join(total_path, 'data') # multigpu_train.py路径 train_path = '/data2/liudan/ocr/model_saved/cscs/' # pretrained_model_path = os.path.join(train_path, 'pretrain_model/model.ckpt-103336') train_save_path = os.path.join(train_path, '09-01') # train得到的数据位置(.index, .meta, .data),这里表示save_pb_model的输入 pretrained_model_path1 = os.path.join(train_path, '09-01') save_pb_path = os.path.join(train_path, '0902/') # .pb文件位置 save_str_hegd_path = os.path.join(train_path, '/evalsave/0902') # score_the_ocr_model中测试数据位置 testdat_msg = os.path.join(total_path, 'data/ocr_txt/') eval_saved = os.path.join(train_path, '/evalsave/0902')