基于opencv和qt的人脸检测小系统

摘要：利用opencv读取视频、图片并检测人脸，利用QT显示窗口，功能选择等

环境：Ubuntu18.04、OpenCV3.4.0、QT5.10.1

效果图：

代码如下（比较简单没什么注释）：

main.cpp

#include "widget.h"
#include <QApplication>
int main(int argc, char *argv[])
{
    QApplication a(argc, argv);
    Widget w;
    w.setWindowTitle("FaceDetect By lyj");
    w.show();
    return a.exec();
}

widget.cpp（xml文件路径要根据个人情况修改）

#include "widget.h"
#include "ui_widget.h"
#include <QDebug>
#include <QPaintEvent>
#include <QTimer>
#include <QPainter>
#include <QPixmap>
#include <QLabel>
#include <QImage>
#include <QFileDialog>
#include <QString>
using namespace std;

QString mydialog(QString title)
{
    QString path;
    QFileDialog *fileDialog = new QFileDialog();//创建一个QFileDialog对象，构造函数中的参数可以有所添加。
    fileDialog->setWindowTitle(title);//设置文件保存对话框的标题
    fileDialog->setFileMode(QFileDialog::AnyFile);//设置文件对话框弹出的时候显示任何文件，不论是文件夹还是文件
    fileDialog->setViewMode(QFileDialog::Detail);//文件以详细的形式显示，显示文件名，大小，创建日期等信息；
    fileDialog->setGeometry(,,,);//设置文件对话框的显示位置
    fileDialog->setDirectory(".");//设置文件对话框打开时初始打开的位置
    if(fileDialog->exec() == QDialog::Accepted)
    {
        //注意使用的是QFileDialog::Accepted或者QDialog::Accepted,不是QFileDialog::Accept
        path = fileDialog->selectedFiles()[];//得到用户选择的文件名
    }
    delete fileDialog;
    return path;
}

Widget::Widget(QWidget *parent) :
    QWidget(parent),
    ui(new Ui::Widget)
{
    ui->setupUi(this);
    state = ;
    connect(&theTimer, &QTimer::timeout, this, &Widget::updateImage);//连接信号与槽，图像刷新
    if(!face_cascade.load("/home/luoyijie/myprogram/qt_project/face_detection/haarcascade_frontalface_alt.xml"))
    {
        qDebug() << "load xml file failed";
    }
    num = ;
    ui->label->setText("FaceNum: " + QString::number(num));
    srcImage = Mat::zeros(, , CV_8UC3);//图像显示部分初始设置黑色
    this->update();
}

Widget::~Widget()
{
    delete ui;
}
void Widget::on_button1_clicked()
{
    if(state == )
    {
        state = ;
        if(videoCap.open())//摄像头读取视频流
        {
            srcImage = Mat::zeros(videoCap.get(CV_CAP_PROP_FRAME_HEIGHT), videoCap.get(CV_CAP_PROP_FRAME_WIDTH), CV_8UC3);
            theTimer.start();//time信号
        }
    }
}

void Widget::on_button2_clicked()
{
    if(state == )
    {
        state = ;
        string path_ = mydialog("Open Video").toStdString();
        if(videoCap.open(path_))
        {
            srcImage = Mat::zeros(videoCap.get(CV_CAP_PROP_FRAME_HEIGHT), videoCap.get(CV_CAP_PROP_FRAME_WIDTH), CV_8UC3);
            theTimer.start();
        }
    }
}
void Widget::on_button3_clicked()
{
    if(state == )
    {
        state = ;
        string path_ = mydialog("Open Picture").toStdString();
        srcImage = imread(path_);
        updateImage();
    }
}
void Widget::on_button4_clicked()
{
    num = ;
    switch(state)
    {
        case : break;
        case :
                srcImage = Mat::zeros(, , CV_8UC3);
                theTimer.stop();
                this->update();
                videoCap.release();
                break;
        case :
                srcImage = Mat::zeros(, , CV_8UC3);
                theTimer.stop();
                this->update();
                videoCap.release();
                break;
        case :
                srcImage = Mat::zeros(, , CV_8UC3);
                this->update();
                break;
    }
    state = ;
}
void Widget::updateImage()
{
    if(state ==  || state == )
    {
        videoCap >> srcImage;
    }
    if(srcImage.data)
    {
        vector<Rect> faces;
        face_cascade.detectMultiScale(srcImage, faces, 1.1, , , Size(,), Size(,));
        num = faces.size();
        if(faces.size() >= )
        {
            for(size_t i=;i<faces.size();i++)
            {
                Point p1(faces[i].x, faces[i].y);
                Point p2(faces[i].x + faces[i].width, faces[i].y + faces[i].height);
                rectangle(srcImage, p2, p1, cvScalar(, , ), , , );
            }
        }
        cvtColor(srcImage, srcImage, CV_BGR2RGB);//Qt中支持的是RGB图像, OpenCV中支持的是BGR
        cv::resize(srcImage, srcImage, Size(,));
        this->update();  //发送刷新消息
     }
}
void Widget::paintEvent(QPaintEvent *e)
{
    QPainter painter(this);
    ui->label->setText("FaceNum: " + QString::number(num));
    QImage image1 = QImage((uchar*)(srcImage.data), srcImage.cols, srcImage.rows, QImage::Format_RGB888);
    painter.drawImage(QPoint(,), image1);
}

widget.h

#ifndef WIDGET_H
#define WIDGET_H
#include <QWidget>
#include <QTimer>
#include <QLabel>
#include <QPaintEvent>
#include <QPainter>
#include <QPixmap>
#include <QImage>
#include "cv.h"
#include "highgui.h"
#include "opencv.hpp"
using namespace cv;
namespace Ui {
class Widget;
}

class Widget : public QWidget
{
    Q_OBJECT
public:
    explicit Widget(QWidget *parent = );
    ~Widget();
private slots:       //声明槽
    void on_button1_clicked();
    void on_button2_clicked();
    void updateImage();
    void on_button4_clicked();
    void on_button3_clicked();
private:
    Ui::Widget *ui;          //ui界面对象指针
    QTimer theTimer;
    //QTimer 计时用；
    QLabel *imageLabel;
    Mat srcImage;
    VideoCapture videoCap;
    CascadeClassifier face_cascade;
    int state;//状态 camera是1，video是2，picture是3，back返回0
    int num;//检测到的人脸数量
protected:
    void paintEvent(QPaintEvent *e);
};
#endif // WIDGET_H

.pro工程配置文件和.ui文件在整个工程的链接里面

https://files.cnblogs.com/files/luoyijie/face_detection.tar.gz