人脸识别.rar_qt 人脸识别_qt 人脸采集_人脸_人脸识别_人脸识别qt

"haar"特征主要用于人脸检测 "hog"特征主要用于行人检测 "lbp"特征主要用于人脸识别 eye_Classifier.detectMultiScale(image_gray, eyeRect, 1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));//检测 face_cascade.detectMultiScale(image_gray, faceRect, 1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30, 30));//检测 #------------------------------------------------- # # Project created by QtCreator 2015-11-11T08:11:51 # #------------------------------------------------- QT += core gui greaterThan(QT_MAJOR_VERSION, 4): QT += widgets TARGET = face_recognition TEMPLATE = app SOURCES += main.cpp\ mainwindow.cpp HEADERS += mainwindow.h FORMS += mainwindow.ui INCLUDEPATH+=C:\OpenCV_contrib\include\opencv\ C:\OpenCV_contrib\include\opencv2\ C:\OpenCV_contrib\include LIBS += -LC:/OpenCV_contrib/lib -lopencv_core2410.dll \ -lopencv_highgui2410.dll -lopencv_imgproc2410.dll -lopencv_features2d2410.dll \ -lopencv_calib3d2410.dll \ -lopencv_objdetect2410.dll \ -lopencv_contrib2410.dll //mainwindow.h #ifndef MAINWINDOW_H #define MAINWINDOW_H #include<QMainWindow> #include<QCloseEvent> #include<opencv2/highgui/highgui.hpp> #include<opencv2/imgproc/imgproc.hpp> #include<opencv2/core/core.hpp> #include<opencv2/objdetect/objdetect.hpp> #include<opencv2/contrib/contrib.hpp> //#include<opencv2/face.hpp> #include<iostream> using namespace std; using namespace cv; using namespace face; namespace Ui { class MainWindow; } class MainWindow : public QMainWindow { Q_OBJECT public: explicit MainWindow(QWidget *parent = 0); ~MainWindow(); private slots: void on_loadButton_clicked(); void on_testButton_clicked(); void on_regButton_clicked(); void closeEvent(QCloseEvent *e); private: Ui::MainWindow *ui; Ptr<LBPHFaceRecognizer> model; QString fileName,saveXml,saveName,name[10]; }; #endif // MAINWINDOW_H //mainwindow.cpp #include "mainwindow.h" #include "ui_mainwindow.h" #include<QDebug> #include<QFileDialog> #include<QPixmap> #include<QFile> #include<QTextStream> //正面,上,下,左,右5张.阉值85.00 MainWindow::MainWindow(QWidget *parent): QMainWindow(parent), ui(new Ui::MainWindow) { ui->setupUi(this); saveName = "Names.txt"; saveXml = "att_model.xml"; model = createLBPHFaceRecognizer(); if(QFile::exists(saveXml)&&QFile::exists(saveName)) { model->load(saveXml.toStdString()); QFile file(saveName); if (!file.open(QIODevice::ReadOnly | QIODevice::Text)) return; QTextStream in(&file); QString lineText; while(!in.atEnd()) { lineText = in.readLine(); QString i = lineText.split(":").first(); name[i.toInt()] = lineText.split(":").last(); } } // for(int i=1;i<11;i++) // for(int j=1;j<10;j++) // { // QString file = "att_faces/s%1/%2.pgm"; // images.push_back(imread(file.arg(i).arg(j).toStdString(), CV_LOAD_IMAGE_GRAYSCALE)); // labels.push_back(i); // } // model = createLBPHFaceRecognizer(); // //model->train(images, labels); // //model->save("att_model.xml"); // model->load("att_model.xml"); } MainWindow::~MainWindow() { delete ui; } void MainWindow::closeEvent(QCloseEvent *e) { model->save(saveXml.toStdString()); QFile file(saveName); if(!file.open(QIODevice::WriteOnly|QIODevice::Text)) return; QTextStream out(&file); for(int i=0;i<10;i++) { if(name[i].isEmpty()) continue; out<<i<<":"<<name[i]<<"\n"; } e->accept(); } void MainWindow::on_loadButton_clicked() { fileName = QFileDialog::getOpenFileName(this,tr("选择图片"),tr(".")); if(fileName.isEmpty()) return; ui->showLabel->setPixmap(QPixmap(fileName)); ui->textBrowser->append(tr("打开图片%1").arg(fileName.split("/").last())); } void MainWindow::on_testButton_clicked() { if(fileName.isEmpty()||ui->nameEdit->text().isEmpty()) return; vector<Mat> images; vector<int> labels; images.push_back(imread(fileName.toStdString(),CV_LOAD_IMAGE_GRAYSCALE)); labels.push_back(ui->labelBox->value()); name[ui->labelBox->value()] = ui->nameEdit->text(); ui->textBrowser->append(tr("准备训练: 姓名:%1 标签:%2 ...").arg(ui->nameEdit->text()).arg(ui->labelBox->value())); model->update(images,labels); ui->textBrowser->append(tr("训练完成")); } void MainWindow::on_regButton_clicked() { ui->nameLabel->clear(); if(fileName.isEmpty()) return; Mat image = imread(fileName.toStdString(), CV_LOAD_IMAGE_GRAYSCALE); model->setThreshold(ui->doubleSpinBox->value()); ui->textBrowser->append(tr("准备识别Threshold:%1 ...").arg(ui->doubleSpinBox->value())); int result = model->predict(image); ui->textBrowser->append(tr("识别完成")); if(result < 0) ui->nameLabel->setText(tr("无法识别此人")); else ui->nameLabel->setText(tr("%1").arg(name[result])); } //main.cpp: #include "mainwindow.h" #include <QApplication> int main(int argc, char *argv[]) { QApplication a(argc, argv); MainWindow w; w.show(); return a.exec(); }