the first submit

+
+opencv4.5.5
+
+模型初始化
+
+FaceRecognize face_rec=FaceRecognize(det_model_path,landm_model_path,rec_model_path)
+
+    det_model_path:人脸检测模型retinaface的onnx模型路径
+    landm_model_path:106人脸关键点模型的onnx模型路径
+    rec_model_path:人脸识别模型的onnx模型路径
+
+重要参数(.h文件)
+
+    bool use_gpu=true;  //是否使用gpu
+    float confidence_threshold = 0.5;  //人脸检测阈值
+    float nms_threshold = 0.4;   //nms阈值
+    double face_recongnize_thr = 0.2;  //人脸相似度阈值 
+
+接口(返回结果 bool:true/false)
+
+    bool face_recognize(string image1_path,string image2_path);参数为两张图像地址，其中iamge1_path为face_id图像输入
+    bool face_recognize_image(Mat image1,Mat image2);参数为两张opencv读取的图像矩阵，其中iamge1为face_id图像输入
+
+编译
+
+    g++ main.cpp -L . -lfacerecognize -o main
+    如果报错无法找到改用：g++ main.cpp -L . -lfacerecognize -o main pkg-config --libs --cflags opencv4
+    ./main

+#ifndef FACERECOGNIZE_H
+#define FACERECOGNIZE_H
+#include<opencv2/opencv.hpp>
+
+using namespace std;
+using namespace cv;
+struct Bbox{
+        float xmin;
+        float ymin;
+        float xmax;
+        float ymax;
+        float score;
+        float x1;
+        float y1;
+        float x2;
+        float y2;
+        float x3;
+        float y3;
+        float x4;
+        float y4;
+        float x5;
+        float y5;
+        };
+class FaceRecognize{
+
+    private:
+        //是否使用gpu?
+        bool use_gpu=true;
+
+        //人脸检测
+        vector<float> input_size={640,640};
+        vector<float> variances={0.1,0.2};
+        vector<float> mean_data={104,117,128};
+        float confidence_threshold = 0.5;  //人脸检测阈值
+        float keep_top_k = 100;
+        float vis_threshold = 0.5;
+        float nms_threshold = 0.4;
+        float resize_scale = 1.0;
+        bool is_bbox_process=true;    //人脸外扩
+
+        //人脸识别
+        double face_recongnize_thr = 0.2;  //人脸相似度阈值 
+        cv::dnn::Net det_net,landm_net,rec_net;
+
+
+    public:
+        FaceRecognize();
+        FaceRecognize(string face_det_model_path,string face_landm_model_path,string face_rec_model_path){
+            det_net = cv::dnn::readNetFromONNX(face_det_model_path);
+            landm_net = cv::dnn::readNetFromONNX(face_landm_model_path);
+            rec_net = cv::dnn::readNetFromONNX(face_rec_model_path);
+            if(use_gpu){
+                det_net.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA);
+                det_net.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA);
+                landm_net.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA);
+                landm_net.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA);
+                rec_net.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA);
+                rec_net.setPreferableTarget(cv::dnn::DNN_TARGET_CUDA);
+            }
+            
+        }
+        //人脸检测部分
+        vector<vector<float>> priorBox(vector<float> image_size);
+        vector<Bbox> decode(vector<vector<float>> loc,vector<vector<float>> score,vector<vector<float>>pre,vector<vector<float>> priors,vector<float> variances);
+        void nms_cpu(std::vector<Bbox> &bboxes, float threshold);
+        vector<vector<float>> mat2vector(Mat mat);
+        vector<Bbox> select_score(vector<Bbox> bboxes,float threshold,float w_r,float h_r);
+        vector<Bbox> bbox_process(vector<Bbox> bboxes,float frame_w,float frame_h);
+        vector<Bbox> detect(string image_path);
+        vector<Bbox> detect_image(Mat image);
+
+
+        //人脸关键点部分
+        vector<vector<float>> detect_landmarks(string image_path);
+        vector<vector<float>> detect_image_landmarks(cv::Mat image);
+
+
+        //人脸识部分
+        cv::Mat meanAxis0(const cv::Mat &src);
+        cv::Mat elementwiseMinus(const cv::Mat &A,const cv::Mat &B);
+        cv::Mat varAxis0(const cv::Mat &src);
+        int MatrixRank(cv::Mat M);
+        cv::Mat similarTransform(cv::Mat src,cv::Mat dst);
+        Mat preprocess_face(Mat image,vector<vector<float>> land);
+        double getMold(const vector<double>& vec);
+        double cos_distance(const vector<double>& base, const vector<double>& target);
+        double get_samilar(Mat image1,Mat image2);
+
+
+        //整体
+        bool face_recognize(string image1_path,string image2_path);
+        bool face_recognize_image(Mat image1,Mat image2);
+};
+
+
+#endif
\ No newline at end of file

+#include"facerecognize.h"
+#include "ctime"
+
+int main(){
+    FaceRecognize face_rec=FaceRecognize("/home/situ/qfs/sdk_project/mobile_face_recognize/det_face_retina_torch_1.4_v0.0.2.onnx","/home/situ/qfs/sdk_project/mobile_face_recognize/det_landmarks_106_v0.0.1.onnx","/home/situ/qfs/sdk_project/mobile_face_recognize/ms1mv3_r18.onnx");
+    clock_t start, end;
+    cv::Mat image1=cv::imread("/data/face_recognize/pipeline_test/59297ec0094211ecaf3d00163e514671/310faceImageContent163029410817774.jpg");
+    cv::Mat image2=cv::imread("/data/face_recognize/pipeline_test/59297ec0094211ecaf3d00163e514671/310cardImageContent163029410836583.jpg");
+    cout<<"start"<<endl;
+    start = clock();
+    bool result=face_rec.face_recognize_image(image1,image2);
+    end = clock();
+    double elapsedTime = static_cast<double>(end-start) / CLOCKS_PER_SEC ;
+    
+    printf("PROCESSING TIME: %f",elapsedTime);
+
+}