compatible with python3

README.md

@@ -87,59 +87,59 @@ MTCNN主要有三个网络，叫做**PNet**, **RNet** 和 **ONet**。因此我
 * 生成PNet训练数据和标注文件
 
 ```shell
-python src/prepare_data/gen_Pnet_train_data.py --dataset_path {your dataset path} --anno_file {your dataset original annotation path}
+python dface/prepare_data/gen_Pnet_train_data.py --dataset_path {your dataset path} --anno_file {your dataset original annotation path}
 ```
 * 乱序合并标注文件
 
 ```shell
-python src/prepare_data/assemble_pnet_imglist.py
+python dface/prepare_data/assemble_pnet_imglist.py
 ```
 
 * 训练PNet模型
 
 
 ```shell
-python src/train_net/train_p_net.py
+python dface/train_net/train_p_net.py
 ```
 * 生成ＲNet训练数据和标注文件
 
 ```shell
-python src/prepare_data/gen_Rnet_train_data.py --dataset_path {your dataset path} --anno_file {your dataset original annotation path} --pmodel_file {yout PNet model file trained before}
+python dface/prepare_data/gen_Rnet_train_data.py --dataset_path {your dataset path} --anno_file {your dataset original annotation path} --pmodel_file {yout PNet model file trained before}
 ```
 * 乱序合并标注文件
 
 ```shell
-python src/prepare_data/assemble_rnet_imglist.py
+python dface/prepare_data/assemble_rnet_imglist.py
 ```
 
 * 训练RNet模型
 
 ```shell
-python src/train_net/train_r_net.py
+python dface/train_net/train_r_net.py
 ```
 
 * 生成ONet训练数据和标注文件
 
 ```shell
-python src/prepare_data/gen_Onet_train_data.py --dataset_path {your dataset path} --anno_file {your dataset original annotation path} --pmodel_file {yout PNet model file trained before} --rmodel_file {yout RNet model file trained before}
+python dface/prepare_data/gen_Onet_train_data.py --dataset_path {your dataset path} --anno_file {your dataset original annotation path} --pmodel_file {yout PNet model file trained before} --rmodel_file {yout RNet model file trained before}
 ```
 
 * 生成ONet的人脸关键点训练数据和标注文件
 
 ```shell
-python src/prepare_data/gen_landmark_48.py
+python dface/prepare_data/gen_landmark_48.py
 ```
 
 * 乱序合并标注文件(包括人脸关键点)
 
 ```shell
-python src/prepare_data/assemble_onet_imglist.py
+python dface/prepare_data/assemble_onet_imglist.py
 ```
 
 * 训练ONet模型
 
 ```shell
-python src/train_net/train_o_net.py
+python dface/train_net/train_o_net.py
 ```
 
 #### 测试人脸检测