opencv联合dlib人脸检测例子

Posted 2022-11-26 arvik

源码比较简洁，杂余信息全部去掉，源码中已经做了中文注释。本例子是用opencv加载图像，然后调用dlib进行人脸检测，得到人脸所在区域以及特征点，最后还是用opencv描绘人脸特征点。

例子源码以及解释：

#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
#include <dlib/gui_widgets.h>
#include <dlib/image_io.h>
#include <iostream>
#include <dlib/opencv.h>
#include "opencv2/opencv.hpp"
#include <vector>
#include <ctime>

//由于dlib和opencv中有相当一部分类同名，故不能同时对它们使用using namespace，否则会出现一些莫名其妙的问题
//using namespace dlib;
using namespace std;
//using namespace cv;

void line_one_face_detections(cv::Mat img, std::vector<dlib::full_object_detection> fs)

    int i, j;
    for(j=0; j<fs.size(); j++)
    
        cv::Point p1, p2;
        for(i = 0; i<67; i++)
        
            // 下巴到脸颊 0 ~ 16
            //左边眉毛 17 ~ 21
            //右边眉毛 21 ~ 26
            //鼻梁     27 ~ 30
            //鼻孔        31 ~ 35
            //左眼        36 ~ 41
            //右眼        42 ~ 47
            //嘴唇外圈  48 ~ 59
            //嘴唇内圈  59 ~ 67
            switch(i)
            
                case 16:
                case 21:
                case 26:
                case 30:
                case 35:
                case 41:
                case 47:
                case 59:
                    i++;
                    break;
                default:
                    break;
            

            p1.x = fs[j].part(i).x();
            p1.y = fs[j].part(i).y();
            p2.x = fs[j].part(i+1).x();
            p2.y = fs[j].part(i+1).y();
            cv::line(img, p1, p2, cv::Scalar(0,0,255), 2, 4, 0);
        
    



int main(int argc, char *argv[])

    if(argc != 2)
    
        std::cout<< "you should specified a picture!"<<std::endl;
        return 0;
    

    cv::Mat frame = cv::imread(argv[1]);
    cv::Mat dst;

    //提取灰度图
    cv::cvtColor(frame, dst, CV_BGR2GRAY);

    //加载dlib的人脸识别器
    dlib::frontal_face_detector detector = dlib::get_frontal_face_detector();

    //加载人脸形状探测器
    dlib::shape_predictor sp;
    dlib::deserialize("./shape_predictor_68_face_landmarks.dat") >> sp;

    //Mat转化为dlib的matrix
    dlib::array2d<dlib::bgr_pixel> dimg;
    dlib::assign_image(dimg, dlib::cv_image<uchar>(dst)); 

    //获取一系列人脸所在区域
    std::vector<dlib::rectangle> dets = detector(dimg);
    std::cout << "Number of faces detected: " << dets.size() << std::endl;

    if (dets.size() == 0)
        return 0;

    //获取人脸特征点分布
    std::vector<dlib::full_object_detection> shapes;
    int i = 0;
    for(i = 0; i < dets.size(); i++)
    
        dlib::full_object_detection shape = sp(dimg, dets[i]); //获取指定一个区域的人脸形状
        shapes.push_back(shape); 
       

    //指出每个检测到的人脸的位置
    for(i=0; i<dets.size(); i++)
    
        //画出人脸所在区域
        cv::Rect r;
        r.x = dets[i].left();
        r.y = dets[i].top();
        r.width = dets[i].width();
        r.height = dets[i].height();
        cv::rectangle(frame, r, cv::Scalar(0, 0, 255), 1, 1, 0); 
    

    line_one_face_detections(frame, shapes);

    cv::imshow("frame", frame);
    cv::waitKey(0);
    return 0;

效果：