opencv 训练人脸对比_(三)使用opencv官方训练的人脸检测
#include "mainwindow.h"#include"ui_mainwindow.h"MainWindow::MainWindow(QWidget*parent) :
QMainWindow(parent),
ui(newUi::MainWindow)
{
ui->setupUi(this);//****** 这个路径自行修改 ******
face_cascade_name = "haarcascade_frontalface_alt2.xml";
connect(ui->open, SIGNAL(clicked()), this, SLOT(openCamara()));
connect(ui->close, SIGNAL(clicked()), this, SLOT(closeCamera()));
}
MainWindow::~MainWindow()
{deleteui;
}/**
* @brief 打开本机摄像头，开始人脸识别
**/
voidMainWindow::openCamara()
{/** 人脸检测器(快速的Haar):haarcascade_frontalface_alt2.xml,需要先加载这个，在进行人脸识别*/qDebug()<< "openCamara ...";if (!face_cascade.load(face_cascade_name)){
qDebug()<< "级联分类器错误，可能未找到文件，拷贝该文件到工程目录下！";return;
}
Face_recognition();
}voidMainWindow::Face_recognition()
{//打开摄像头
capture.open(0);while (true)
{
Mat camerFrame;
capture>>camerFrame;if(camerFrame.empty())
{
std::cerr<< "无法获取摄像头图像" <<:endl>
break;
}//Mat displayedFrame(camerFrame.size(),CV_8UC3);
double scale = 0.5;
Size dsize= Size(camerFrame.cols*scale, camerFrame.rows*scale);
cv::resize(camerFrame, camerFrame, dsize);//人脸检测只试用于灰度图像
Mat gray;
Pic2Gray(camerFrame, gray);//直方图均匀化(改善图像的对比度和亮度)
Mat equalizedImg;
equalizeHist(gray, equalizedImg);//int flags = CASCADE_FIND_BIGGEST_OBJECT|CASCADE_DO_ROUGH_SEARCH;//只检测脸最大的人
int flags = CASCADE_SCALE_IMAGE; //检测多个人
Size minFeatureSize(30, 30);float searchScaleFactor = 1.1f;int minNeighbors = 4;
std::vectorfaces;//选择最终的人脸分类器后，若想在这个基础上继续优化，那就试试这个detectMultiScale函数.
face_cascade.detectMultiScale(equalizedImg, faces, searchScaleFactor, minNeighbors, flags, minFeatureSize);//画矩形框
cv::Mat face;
cv::Point text_lb;for (size_t i = 0; i < faces.size(); i++)
{if (faces[i].height > 0 && faces[i].width > 0)
{//face = gray(faces[i]);//text_lb = cv::Point(faces[i].x, faces[i].y);
cv::rectangle(equalizedImg, faces[i], cv::Scalar(255, 0, 0), 1, 8, 0);
cv::rectangle(gray, faces[i], cv::Scalar(255, 0, 0), 1, 8, 0);
cv::rectangle(camerFrame, faces[i], cv::Scalar(255, 0, 0), 1, 8, 0);
qDebug()<< "这是个脸";
}
}//imshow("直方图均匀化", equalizedImg);//imshow("灰度化", gray);//imshow("原图", camerFrame);
QImage image= QImage((const uchar*)camerFrame.data,camerFrame.cols,camerFrame.rows,QImage::Format_RGB888).rgbSwapped();
ui->label->setPixmap(QPixmap::fromImage(image));
QImage image2= QImage((const uchar*)gray.data,gray.cols,gray.rows,QImage::Format_Indexed8);
ui->label_2->setPixmap(QPixmap::fromImage(image2));
QImage image3= QImage((const uchar*)equalizedImg.data,equalizedImg.cols,equalizedImg.rows,QImage::Format_Indexed8).rgbSwapped();
ui->label_3->setPixmap(QPixmap::fromImage(image3));
waitKey(50);
}
}void MainWindow::Pic2Gray(Mat camerFrame,Mat &gray)
{//普通台式机3通道BGR,移动设备为4通道
if (camerFrame.channels() == 3)
{
cvtColor(camerFrame, gray, CV_BGR2GRAY);
}else if (camerFrame.channels() == 4)
{
cvtColor(camerFrame, gray, CV_BGRA2GRAY);
}elsegray=camerFrame;
}voidMainWindow::closeCamera()
{
capture.release();
}