diff --git a/README.md b/README.md index 28585db..197c443 100644 --- a/README.md +++ b/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