最快人脸检测：

最新版本支持pytorch。现已开源！支持最小检测人脸10x10大小

  

   

    

     

    
    

     

      OpenCV DNN可以直接调用训练好的caffe模型文件，实现实时人脸检测，演示代码如下：
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 1#include <opencv2/opencv.hpp>
     
    
   

    

     

    
    

     
 2#include <opencv2/dnn.hpp>
     
    
   

    

     

    
    

     
 3#include <iostream>
     
    
   

    

     

    
    

     
 4
     
    
   

    

     

    
    

     
 5using namespace cv;
     
    
   

    

     

    
    

     
 6using namespace cv::dnn;
     
    
   

    

     

    
    

     
 7using namespace std;
     
    
   

    

     

    
    

     
 8
     
    
   

    

     

    
    

     
 9const size_t inWidth = 300;
     
    
   

    

     

    
    

     

      10const size_t inHeight = 300;
     
    
   

    

     

    
    

     

      11const double inScaleFactor = 0.007843;
     
    
   

    

     

    
    

     

      12const Scalar meanVal(104.0, 117, 123.0);
     
    
   

    

     

    
    

     

      13const float confidence = 0.5;
     
    
   

    

     

    
    

     

      14
     
    
   

    

     

    
    

     

      15int main(int argc, char** argv) {
     
    
   

    

     

    
    

     

      16 string model = "D:/projects/models/yufacedetectnet-open-v2.caffemodel";
     
    
   

    

     

    
    

     

      17 string config = "D:/projects/models/yufacedetectnet-open-v2.prototxt";
     
    
   

    

     

    
    

     

      18 // read network
     
    
   

    

     

    
    

     

      19 Net net = readNetFromCaffe(config, model);
     
    
   

    

     

    
    

     

      20 VideoCapture cap(0);
     
    
   

    

     

    
    

     

      21 Mat frame;
     
    
   

    

     

    
    

     

      22 while (true) {
     
    
   

    

     

    
    

     

      23 bool ret = cap.read(frame);
     
    
   

    

     

    
    

     

      24 if (!ret) {
     
    
   

    

     

    
    

     

      25 break;
     
    
   

    

     

    
    

     

      26 }
     
    
   

    

     

    
    

     

      27 int64 start = getTickCount();
     
    
   

    

     

    
    

     

      28 Mat input_data = blobFromImage(frame, inScaleFactor, Size(320, 240), meanVal, false, false);
     
    
   

    

     

    
    

     

      29 net.setInput(input_data);
     
    
   

    

     

    
    

     

      30
     
    
   

    

     

    
    

     

      31 // 人脸检测
     
    
   

    

     

    
    

     

      32 Mat detection = net.forward();
     
    
   

    

     

    
    

     

      33 Mat detectionMat(detection.size[2], detection.size[3], CV_32F, detection.ptr<float>());
     
    
   

    

     

    
    

     

      34
     
    
   

    

     

    
    

     

      35 // 推断时间
     
    
   

    

     

    
    

     

      36 vector<double> layersTimings;
     
    
   

    

     

    
    

     

      37 double freq = getTickFrequency() / 1000;
     
    
   

    

     

    
    

     

      38 double time = net.getPerfProfile(layersTimings) / freq;
     
    
   

    

     

    
    

     

      39
     
    
   

    

     

    
    

     

      40 ostringstream ss;
     
    
   

    

     

    
    

     

      41 for (int i = 0; i < detectionMat.rows; i++)
     
    
   

    

     

    
    

     

      42 {
     
    
   

    

     

    
    

     

      43 // 置信度 0～1之间
     
    
   

    

     

    
    

     

      44 float score = detectionMat.at<float>(i, 2);
     
    
   

    

     

    
    

     

      45 if (score > confidence)
     
    
   

    

     

    
    

     

      46 {
     
    
   

    

     

    
    

     

      47 int xLeftBottom = static_cast<int>(detectionMat.at<float>(i, 3) * frame.cols);
     
    
   

    

     

    
    

     

      48 int yLeftBottom = static_cast<int>(detectionMat.at<float>(i, 4) * frame.rows);
     
    
   

    

     

    
    

     

      49 int xRightTop = static_cast<int>(detectionMat.at<float>(i, 5) * frame.cols);
     
    
   

    

     

    
    

     

      50 int yRightTop = static_cast<int>(detectionMat.at<float>(i, 6) * frame.rows);
     
    
   

    

     

    
    

     

      51
     
    
   

    

     

    
    

     

      52 Rect object((int)xLeftBottom, (int)yLeftBottom,
     
    
   

    

     

    
    

     

      53 (int)(xRightTop - xLeftBottom),
     
    
   

    

     

    
    

     

      54 (int)(yRightTop - yLeftBottom));
     
    
   

    

     

    
    

     

      55
     
    
   

    

     

    
    

     

      56 rectangle(frame, object, Scalar(0, 255, 0));
     
    
   

    

     

    
    

     

      57
     
    
   

    

     

    
    

     

      58 ss << score;
     
    
   

    

     

    
    

     

      59 String conf(ss.str());
     
    
   

    

     

    
    

     

      60 String label = "Face: " + conf;
     
    
   

    

     

    
    

     

      61 int baseLine = 0;
     
    
   

    

     

    
    

     

      62 Size labelSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
     
    
   

    

     

    
    

     

      63 rectangle(frame, Rect(Point(xLeftBottom, yLeftBottom - labelSize.height),
     
    
   

    

     

    
    

     

      64 Size(labelSize.width, labelSize.height + baseLine)),
     
    
   

    

     

    
    

     

      65 Scalar(255, 255, 255), FILLED);
     
    
   

    

     

    
    

     

      66 putText(frame, label, Point(xLeftBottom, yLeftBottom),
     
    
   

    

     

    
    

     

      67 FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 0));
     
    
   

    

     

    
    

     

      68 }
     
    
   

    

     

    
    

     

      69 }
     
    
   

    

     

    
    

     

      70 float fps = getTickFrequency() / (getTickCount() - start);
     
    
   

    

     

    
    

     

      71 ss.str("");
     
    
   

    

     

    
    

     

      72 ss << "FPS: " << fps << " ; inference time: " << time << " ms";
     
    
   

    

     

    
    

     

      73 putText(frame, ss.str(), Point(20, 20), 0, 0.75, Scalar(0, 0, 255), 2, 8);
     
    
   

    

     

    
    

     

      74 imshow("dnn_face_detection", frame);
     
    
   

    

     

    
    

     

      75 if (waitKey(1) >= 0) break;
     
    
   

    

     

    
    

     

      76 }
     
    
   

    

     

    
    

     

      77 waitKey(0);
     
    
   

    

     

    
    

     

      78 return 0;
     
    
   

    

     

    
    

     

      79}
     
    
  
 

这个好像没有关键点：

https://github.com/ShiqiYu/libfacedetection

文章来源: blog.csdn.net，作者：网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/104705460