| @@ -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 | * 生成PNet训练数据和标注文件 | ||||
| ```shell | ```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 | * 乱序合并标注文件 | ||||
| ```shell | ```shell | ||||
| python src/prepare_data/assemble_pnet_imglist.py | |||||
| python dface/prepare_data/assemble_pnet_imglist.py | |||||
| ``` | ``` | ||||
| * 训练PNet模型 | * 训练PNet模型 | ||||
| ```shell | ```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 | * 生成RNet训练数据和标注文件 | ||||
| ```shell | ```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 | * 乱序合并标注文件 | ||||
| ```shell | ```shell | ||||
| python src/prepare_data/assemble_rnet_imglist.py | |||||
| python dface/prepare_data/assemble_rnet_imglist.py | |||||
| ``` | ``` | ||||
| * 训练RNet模型 | * 训练RNet模型 | ||||
| ```shell | ```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 | * 生成ONet训练数据和标注文件 | ||||
| ```shell | ```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 | * 生成ONet的人脸关键点训练数据和标注文件 | ||||
| ```shell | ```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) | * 乱序合并标注文件(包括人脸关键点) | ||||
| ```shell | ```shell | ||||
| python src/prepare_data/assemble_onet_imglist.py | |||||
| python dface/prepare_data/assemble_onet_imglist.py | |||||
| ``` | ``` | ||||
| * 训练ONet模型 | * 训练ONet模型 | ||||
| ```shell | ```shell | ||||
| python src/train_net/train_o_net.py | |||||
| python dface/train_net/train_o_net.py | |||||
| ``` | ``` | ||||
| #### 测试人脸检测 | #### 测试人脸检测 | ||||