QT实现人脸识别
Face.pro文件：
cpp
QT += core gui
greaterThan(QT_MAJOR_VERSION, 4): QT += widgets
CONFIG += c++11
# The following define makes your compiler emit warnings if you use
# any Qt feature that has been marked deprecated (the exact warnings
# depend on your compiler). Please consult the documentation of the
# deprecated API in order to know how to port your code away from it.
DEFINES += QT_DEPRECATED_WARNINGS
# You can also make your code fail to compile if it uses deprecated APIs.
# In order to do so, uncomment the following line.
# You can also select to disable deprecated APIs only up to a certain version of Qt.
#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000 # disables all the APIs deprecated before Qt 6.0.0
SOURCES += \
main.cpp \
widget.cpp
HEADERS += \
widget.h
FORMS += \
widget.ui
INCLUDEPATH += D:/opencv/opencv3.4-qt-intall/install/include
INCLUDEPATH += D:/opencv/opencv3.4-qt-intall/install/include/opencv
INCLUDEPATH += D:/opencv/opencv3.4-qt-intall/install/include/opencv2
LIBS += D:/opencv/opencv3.4-qt-intall/install/x86/mingw/lib/libopencv_*.a
# Default rules for deployment.
qnx: target.path = /tmp/$${TARGET}/bin
else: unix:!android: target.path = /opt/$${TARGET}/bin
!isEmpty(target.path): INSTALLS += targetwidget.h文件：
cpp
#ifndef WIDGET_H
#define WIDGET_H
#include <QWidget>
#include <QWidget>
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
#include<opencv2/face.hpp>
#include <vector>
#include <map>
#include <QMessageBox>
#include <QDebug>
#include <QFile>
#include <QTextStream>
#include <QDateTime>
#include <QTimerEvent>
#include<QtSerialPort/QtSerialPort>
#include<QtSerialPort/QSerialPortInfo>
using namespace cv;
using namespace cv::face;
using namespace std;
QT_BEGIN_NAMESPACE
namespace Ui { class Widget; }
QT_END_NAMESPACE
class Widget : public QWidget
{
Q_OBJECT
public:
Widget(QWidget *parent = nullptr);
~Widget();
private slots:
void on_openBtn_clicked();
void on_closeBtn_clicked();
void on_faceBtn_clicked();
private:
Ui::Widget *ui;
//=========摄像头相关成员的设置=========
VideoCapture v; //摄像头容器
Mat src; //存放 原图 的容器
Mat gray; //存放 灰度图 的容器
Mat dst; //存放 直方图 的容器
Mat rgb; //存放 rgb图 的容器
CascadeClassifier c; //定义一个级联分类器容器
vector<Rect> faces; // 定义一个数组存放人脸矩形框
int camera_id; //打开摄像头的定时器id
void timerEvent(QTimerEvent *e); //定时器事件 重写函数事件声明
//=========人脸录入相关成员的设置=========
Ptr<LBPHFaceRecognizer> recognizer; //人脸 识别器指针
vector<Mat> study_faces; //定义一个存放录入人脸的数组
vector<int> study_lables; //定义一个存放人脸对应的标签数组
int count; //记录录入人脸的次数
int flag; //用来区别是人脸录入还是人脸识别
int face_id; // 人脸录入定时器id
//=========人脸检测相关成员的设置=========
int check_id; //
};
#endif // WIDGET_Hwidget.cpp文件：
cpp
#include "widget.h"
#include "ui_widget.h"
Widget::Widget(QWidget *parent)
: QWidget(parent)
, ui(new Ui::Widget)
{
ui->setupUi(this);
ui->weChatBtn->setEnabled(false);
//打开系统摄像头
if(!v.open(0))
{
QMessageBox::information(this, "", "打开系统摄像头失败！");
return;
}
//配置 级联分类器
if(!c.load("D:\\opencv\\image\\haarcascade_frontalface_alt.xml"))
{
QMessageBox::information(this, "", "配置级联分类器失败！");
return;
}
//判断是否录入过人脸
QFile file("D:\\opencv\\image\\my_face.xml");
//判断文件是否存在
if(file.exists())
{
//表示之前录入过人脸 则下载文件
recognizer = LBPHFaceRecognizer::load<LBPHFaceRecognizer>("D:\\opencv\\image\\my_face.xml");
}else {
//表示之前没有录入过人脸
recognizer = LBPHFaceRecognizer::create();
}
//启动一个人脸检测定时器
check_id = startTimer(3000);
flag = 1; //可以人脸检测
recognizer->setThreshold(100);
}
Widget::~Widget()
{
delete ui;
}
//打开摄像头按钮对应的 槽函数
void Widget::on_openBtn_clicked()
{
//启动一个定时器
camera_id = startTimer(30);
}
//定时器重写的功能函数
void Widget::timerEvent(QTimerEvent *e)
{
//判断是否是 摄像头定时器 超时
if(e->timerId() == camera_id)
{
//读取系统摄像头中的图像
v.read(src);
//图像反转
flip(src, src, 1);
//将 bgr 转换成 rgb
cvtColor(src, rgb, CV_BGR2RGB);
//将图像重新设置大小 适应lab
cv::resize(rgb, rgb, Size(301,251));
//灰度处理
cvtColor(rgb, gray, CV_RGB2GRAY);
//均衡化处理
equalizeHist(gray, dst);
//锁定人脸矩形框位置
c.detectMultiScale(dst, faces);
//将矩形框绘制到人脸上
for(uint i=0; i<faces.size(); i++)
{
rectangle(rgb, faces[i], Scalar(255,0,0),2);
}
//将图像放入 lab 中
QImage img(rgb.data, rgb.cols, rgb.rows, rgb.cols*rgb.channels(), QImage::Format_RGB888);
ui->label->setPixmap(QPixmap::fromImage(img));
}
//判断是否是 人脸录入定时器 超时
if(e->timerId() == face_id)
{
if(0 == flag)
{
qDebug() << "人脸录入中，请正视摄像头！";
Mat face = src(faces[0]); //将摄像头当前的一帧图像上的一个人脸给face
//灰度处理
cvtColor(face, face, CV_BGR2GRAY);
//均衡化处理
equalizeHist(face, face);
//将人脸放入数组中
study_faces.push_back(face);
study_lables.push_back(1);
count++;
if(50 == count)
{
//将图像模型转换成数据模型
recognizer->update(study_faces, study_lables);
recognizer->save("D:\\opencv\\image\\my_face.xml");
QMessageBox::information(this, "", "录入人脸成功！");
//关闭定时器
killTimer(face_id);
flag = 1; //表示可以人脸识别
study_faces.clear(); //将存放人脸数组清空，方便下次录入
study_lables.clear();
}
}
}
//判断是否是 人脸检测定时器 超时
if(e->timerId() == check_id)
{
if(1 == flag)
{
QFile file("D:\\opencv\\image\\my_face.xml");
if(file.exists())
{
if(recognizer.empty() || faces.empty())
{
return;
}
Mat face = src(faces[0]);
//灰度处理
cvtColor(face, face, CV_BGR2GRAY);
//
equalizeHist(face, face);
int lab = -1;
double cof = 0.0;
recognizer->predict(face, lab, cof);
//根据 lab 判断是否识别成功
if(lab != -1)
{
QMessageBox::information(this, "", "人脸识别成功！");
ui->weChatBtn->setEnabled(true);
killTimer(check_id);
}
}
}
}
}
//关闭摄像头按钮对应的槽函数
void Widget::on_closeBtn_clicked()
{
killTimer(camera_id);
}
//录入人脸按钮对应的槽函数
void Widget::on_faceBtn_clicked()
{
count = 0; // 将录入人脸的次数设置为0
flag = 0; //表示只能做人脸录入，不能做人脸检测
face_id = startTimer(50);
}main.c文件：
cpp
#include "widget.h"
#include <QApplication>
int main(int argc, char *argv[])
{
QApplication a(argc, argv);
Widget w;
w.show();
return a.exec();
}ui布局：
