OpenCV实现人脸检测功能

2023-08-01 13:12:04 72

本文实例为大家分享了OpenCV实现人脸检测功能的具体代码，供大家参考，具体内容如下

1、HAAR级联检测

#include
#include

usingnamespacecv;

#include
#include
usingnamespacestd;

intmain(intartc,char**argv){
face_detect_haar();
waitKey(0);
return0;
}

voidface_detect_haar(){
CascadeClassifierfaceDetector;
std::stringhaar_data_file="./models/haarcascades/haarcascade_frontalface_alt_tree.xml";
faceDetector.load(haar_data_file);
vectorfaces;
//VideoCapturecapture(0);
VideoCapturecapture("./video/test.mp4");
Matframe,gray;
intcount=0;
while(capture.read(frame)){
int64start=getTickCount();
if(frame.empty())
{
break;
}
//水平镜像调整
//flip(frame,frame,1);
imshow("input",frame);
if(frame.channels()==4)
cvtColor(frame,frame,COLOR_BGRA2BGR);
cvtColor(frame,gray,COLOR_BGR2GRAY);
equalizeHist(gray,gray);
faceDetector.detectMultiScale(gray,faces,1.2,1,0,Size(30,30),Size(400,400));
for(size_tt=0;t=0)break;
}

printf("totalface:%d\n",count);
}

2、 DNN人脸检测

#include
#include

usingnamespacecv;
usingnamespacecv::dnn;

#include
#include
usingnamespacestd;

constsize_tinWidth=300;
constsize_tinHeight=300;
constdoubleinScaleFactor=1.0;
constScalarmeanVal(104.0,177.0,123.0);
constfloatconfidenceThreshold=0.7;
voidface_detect_dnn();
voidmtcnn_demo();
intmain(intargc,char**argv)
{
face_detect_dnn();
waitKey(0);
return0;
}

voidface_detect_dnn(){
//这里采用tensorflow模型
std::stringmodelBinary="./models/dnn/face_detector/opencv_face_detector_uint8.pb";
std::stringmodelDesc="./models/dnn/face_detector/opencv_face_detector.pbtxt";
//初始化网络
dnn::Netnet=readNetFromTensorflow(modelBinary,modelDesc);

net.setPreferableBackend(DNN_BACKEND_OPENCV);
net.setPreferableTarget(DNN_TARGET_CPU);
if(net.empty())
{
printf("Loadmodelsfail...\n");
return;
}

//打开摄像头
//VideoCapturecapture(0);
VideoCapturecapture("./video/test.mp4");
if(!capture.isOpened()){
printf("Don'tfindvideo...\n");
return;
}

Matframe;
intcount=0;
while(capture.read(frame)){
int64start=getTickCount();
if(frame.empty())
{
break;
}
//水平镜像调整
//flip(frame,frame,1);
imshow("input",frame);
if(frame.channels()==4)
cvtColor(frame,frame,COLOR_BGRA2BGR);

//输入数据调整
MatinputBlob=blobFromImage(frame,inScaleFactor,
Size(inWidth,inHeight),meanVal,false,false);
net.setInput(inputBlob,"data");

//人脸检测
Matdetection=net.forward("detection_out");
vectorlayersTimings;
doublefreq=getTickFrequency()/1000;
doubletime=net.getPerfProfile(layersTimings)/freq;
MatdetectionMat(detection.size[2],detection.size[3],CV_32F,detection.ptr());

ostringstreamss;
for(inti=0;i(i,2);
if(confidence>confidenceThreshold)
{
count++;
intxLeftBottom=static_cast(detectionMat.at(i,3)*frame.cols);
intyLeftBottom=static_cast(detectionMat.at(i,4)*frame.rows);
intxRightTop=static_cast(detectionMat.at(i,5)*frame.cols);
intyRightTop=static_cast(detectionMat.at(i,6)*frame.rows);

Rectobject((int)xLeftBottom,(int)yLeftBottom,
(int)(xRightTop-xLeftBottom),
(int)(yRightTop-yLeftBottom));

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

ss<=0)break;
}
printf("totalface:%d\n",count);
}

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持毛票票。

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OpenCV实现人脸检测功能

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