1、配置文件.pro
#-------------------------------------------------
#
# Project created by QtCreator 2023-09-05T19:00:36
#
#-------------------------------------------------QT += core guigreaterThan(QT_MAJOR_VERSION, 4): QT += widgetsTARGET = 01_face
TEMPLATE = appSOURCES += main.cpp\widget.cppHEADERS += widget.hFORMS += widget.uiINCLUDEPATH += 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
2、头文件
#ifndef WIDGET_H
#define WIDGET_H#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;namespace Ui {
class Widget;
}class Widget : public QWidget
{Q_OBJECTpublic:explicit Widget(QWidget *parent = 0);~Widget();void timerEvent(QTimerEvent *event); //定时器事件处理函数private slots:void on_open_camera_Btn_clicked();void on_close_camera_Btn_clicked();void on_input_face_Btn_clicked();private:Ui::Widget *ui;/************************第一模块:关于摄像头的组件***********************/VideoCapture v; //定义一个视频流对象Mat src; //原图像Mat rgb; //由于qt不识别grb图像,所以需要转化为rgb图像Mat gray; //灰度图Mat dst; //均衡化图像CascadeClassifier c; //级联分类器,用来获取人像的矩形框vector<Rect> faces; //定义一个存储人像矩形的容器int camera_timer_id; //定时器/************************第二模块:录入人脸的组件***********************/Ptr<FaceRecognizer> recognizer; //人脸识别器vector<Mat> study_face; //要录入的人脸容器vector<int> Study_lab; //要录入的人脸标签int input_timer_id; //录入人脸的定时器int flag; //判断是否正在录入中int count; //记录收集到的人脸的次数/************************第三模块:人脸检测的组件***********************/int check_timer_id; //定义一个人脸检测的定时器};#endif // WIDGET_H
3、源文件
main.app
#include "widget.h"
#include <QApplication>int main(int argc, char *argv[])
{QApplication a(argc, argv);Widget w;w.show();return a.exec();
}
widget.cpp
#include "widget.h"
#include "ui_widget.h"int face_count = 1; //录入对应的标签号
Widget::Widget(QWidget *parent) :QWidget(parent),ui(new Ui::Widget)
{ui->setupUi(this);//打开摄像头if(!v.open(0)){QMessageBox::information(this, "提示", "摄像头打开失败");return;}//将级联分类器加载进来if(!c.load("D:/opencv/resource/haarcascade_frontalface_alt2.xml")){QMessageBox::information(this, "提示", "练级分类器加载失败");return;}//配置人脸识别器QFile file("D:/opencv/resource/Face.xml");//判断是否存在,存在将其下载下来,不存在创建人脸模型if(file.exists()){//存在人脸模型,下载进来recognizer = FaceRecognizer::load<LBPHFaceRecognizer>("D:/opencv/resource/Face.xml");}else{//不存在,创建LBPHFaceRecognizer::create()recognizer = LBPHFaceRecognizer::create();}//启动人脸检测定时器check_timer_id = startTimer(3000);flag = 0;//设置可信度recognizer->setThreshold(100);}Widget::~Widget()
{delete ui;
}//打开摄像头按钮的槽函数
void Widget::on_open_camera_Btn_clicked()
{//开启定时器camera_timer_id = this->startTimer(20);}void Widget::on_close_camera_Btn_clicked()
{//关闭定时器this->killTimer(camera_timer_id);
}//定时器事件的函数
void Widget::timerEvent(QTimerEvent *event)
{//判断是否是打开摄像头定时器到位if(event->timerId() == camera_timer_id){//获取图像//函数原型:virtual bool read(OutputArray image);//参数:存储读取到的图像容器//成功返回真,失败/读取完毕返回假v.read(src);//翻转图像//函数原型:oid flip(InputArray src, OutputArray dst, int flipCode);flip(src, src, 1);//将图像转为rgb模式cvtColor(src, rgb, CV_BGR2RGB);//重新设置图像大小cv::resize(rgb, rgb, Size(300,300));//灰度化处理cvtColor(rgb, gray, CV_RGB2GRAY);//均衡化处理equalizeHist(gray, dst);//使用级联分类器获取人脸图像的矩形框,并存入参数2中(人像矩形框容器中)//函数原型:void detectMultiScale( InputArray image,// CV_OUT std::vector<Rect>& objects,// double scaleFactor = 1.1,// int minNeighbors = 3, int flags = 0,// Size minSize = Size(),// Size maxSize = Size() );c.detectMultiScale(dst, faces);//将矩形框绘制到rgb图像中去for(int i=0; i<faces.size(); i++){//使用全局函数rectangle函数,进行绘制rectangle(rgb, faces[i], Scalar(255, 0, 0), 1);}//将图像显示到ui界面上,ui界面的图像为QPixmap//需要将rgb图转为QImage的图像,再转为QPIXmapQImage img(rgb.data, rgb.cols, rgb.rows, rgb.cols*rgb.channels(), QImage::Format_RGB888);//功能:通过其他图像构造一个QImage图像//参数1:其他图像的数据//参数2:图像的宽度(列)//参数3:图像的高度(4)//参数4:每一行的字节数(列*通道)//参数5:图像格式,24位图,每一中颜色使用1字节8位表示//将其设置到ui界面的组件上ui->camera_Lab->setPixmap(QPixmap::fromImage(img)); //QPixmap::fromImage(img); 将QImage图像转为QPixmap图像}//判断是否是录入人脸定时器到位if(input_timer_id == event->timerId()){qDebug() << "正在录入....";//判断ui界面是否有矩形框if(faces.empty()) return;//判断人脸识别器是否存在if(recognizer.empty()) return;//获取矩形框中的图像Mat face = src(faces[0]);//重新设置大小cv::resize(face, face, Size(100, 100));//灰度化处理cvtColor(face, face, CV_BGR2GRAY);//均衡化处理equalizeHist(face, face);qDebug() << face_count;//将图像放入学习容器中study_face.push_back(face);Study_lab.push_back(face_count);count++;//当收集50张后更新学习模型if(50 == count){qDebug() << "hahhah";//将图像模型转为数据模型//函数原型:virtual void update(InputArrayOfArrays src, InputArray labels);//参数1:要进行更新的人脸图像容器//参数2:要进行封信的人脸标签容器recognizer->update(study_face, Study_lab);//将数据模型存入到本地磁盘中去recognizer->save("D:/opencv/resource/Face.xml");QMessageBox::information(this, "提示", "人脸录入成功");flag = 0;count = 0;killTimer(input_timer_id);study_face.clear();Study_lab.clear();face_count++;}}//判断是否是人脸检测定时器到位if(event->timerId() == check_timer_id){if(0 == flag){QFile file("D:/opencv/resource/Face.xml");//判断文件是否存在if(file.exists()){//判断ui->界面是否有矩形框和人脸识别器是否有if(faces.empty() || recognizer.empty()) return;//到此说明开始检测//获取ui界面上的矩形框中的图像Mat face = src(faces[0]);//重新设置图像大小, 与录入人脸时的大小一致cv::resize(face, face, Size(100, 100));//灰度化处理cvtColor(face, face, CV_BGR2GRAY);//均衡化处理equalizeHist(face, face);//定义记录,检测后的结果int lab = -1;double conf = 0.0;//将人脸进行检测recognizer->predict(face, lab, conf);//判断是否匹配if(lab != -1){qDebug() <<"匹配成功";}qDebug() << lab;}}}
}//录入人脸对应的参函数
void Widget::on_input_face_Btn_clicked()
{//启动定时器input_timer_id = startTimer(60);//将flag设置为1, 表明正在录入flag = 1;count = 0;}
4、ui界面