Qt + OpenCV 部署yolov5
Posted SongpingWang
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文章目录
分别使用了openvino，opencv_cuda进行加速。
关于演示视频及代码讲解请查看：
https://www.bilibili.com/video/BV13S4y1c7ea/
https://www.bilibili.com/video/BV1Dq4y1x7r6/
https://www.bilibili.com/video/BV1kT4y1S7hz/
一、新建项目 UI设计
二、代码部分
mainwindow 类
mainwindow.h
#ifndef MAINWINDOW_H
#define MAINWINDOW_H
#include <QFileDialog>
#include <QFile>
#include <opencv2/opencv.hpp>
#include <opencv2/dnn.hpp>
#include <QMainWindow>
#include <QTimer>
#include <QImage>
#include <QPixmap>
#include <QDateTime>
#include <QMutex>
#include <QMutexLocker>
#include <QMimeDatabase>
#include <iostream>
#include <yolov5.h>
#include <chrono>
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\opencv\\\\lib\\\\opencv_core453.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\opencv\\\\lib\\\\opencv_imgcodecs453.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\opencv\\\\lib\\\\opencv_imgproc453.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\opencv\\\\lib\\\\opencv_videoio453.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\opencv\\\\lib\\\\opencv_objdetect453.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\opencv\\\\lib\\\\opencv_dnn453.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\deployment_tools\\\\inference_engine\\\\lib\\\\intel64\\\\Release\\\\inference_engine.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\deployment_tools\\\\inference_engine\\\\lib\\\\intel64\\\\Release\\\\inference_engine_c_api.lib")
#pragma comment(lib,"C:\\\\Program Files (x86)\\\\Intel\\\\openvino_2021\\\\deployment_tools\\\\inference_engine\\\\lib\\\\intel64\\\\Release\\\\inference_engine_transformations.lib")
//LIBS+= -L "C:\\Program Files (x86)\\Intel\\openvino_2021\\opencv\\lib\\*.lib"
//LIBS+= -L "C:\\Program Files (x86)\\Intel\\openvino_2021\\deployment_tools\\inference_engine\\lib\\intel64\\Release\\*.lib"
//#ifdef QT_NO_DEBUG
//#pragma comment(lib,"C:\\Program Files (x86)\\Intel\\openvino_2021\\opencv\\lib\\opencv_core452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_imgcodecs452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_imgproc452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_imgcodecs452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_video452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_videoio452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_objdetect452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_shape452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_dnn452.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_dnn_objdetect452.lib")
//#else
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_core452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_imgcodecs452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_imgproc452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_imgcodecs452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_video452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_videoio452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_objdetect452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_shape452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_dnn452d.lib")
//#pragma comment(lib,"E:/opencv_build/install/x64/vc16/lib/opencv_dnn_objdetect452d.lib")
//#endif
//#ifdef QT_NO_DEBUG
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_core452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_imgcodecs452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_imgproc452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_imgcodecs452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_video452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_videoio452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_objdetect452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_shape452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_dnn452.lib")
//#pragma comment(lib,"E:/opencv452_cuda/install/x64/vc16/lib/opencv_dnn_objdetect452.lib")
//#endif
QPixmap Mat2Image(cv::Mat src);
QT_BEGIN_NAMESPACE
namespace Ui class MainWindow;
QT_END_NAMESPACE
class MainWindow : public QMainWindow
Q_OBJECT
public:
MainWindow(QWidget *parent = nullptr);
void Init();
~MainWindow();
private slots:
void readFrame(); //自定义信号处理函数
void on_openfile_clicked();
void on_loadfile_clicked();
void on_startdetect_clicked();
void on_stopdetect_clicked();
void on_comboBox_activated(const QString &arg1);
private:
Ui::MainWindow *ui;
QTimer *timer;
cv::VideoCapture *capture;
YOLOV5 *yolov5;
NetConfig conf;
NetConfig *yolo_nets;
std::vector<cv::Rect> bboxes;
int IsDetect_ok = 0;
;
#endif // MAINWINDOW_H
mainwindow.cpp
#include "mainwindow.h"
#include "ui_mainwindow.h"
MainWindow::MainWindow(QWidget *parent)
: QMainWindow(parent)
, ui(new Ui::MainWindow)
ui->setupUi(this);
setWindowTitle(QStringLiteral("YoloV5目标检测软件"));
timer = new QTimer(this);
timer->setInterval(33);
connect(timer,SIGNAL(timeout()),this,SLOT(readFrame()));
ui->startdetect->setEnabled(false);
ui->stopdetect->setEnabled(false);
Init();
MainWindow::~MainWindow()
capture->release();
delete capture;
delete [] yolo_nets;
delete yolov5;
delete ui;
void MainWindow::Init()
capture = new cv::VideoCapture();
yolo_nets = new NetConfig[4]
0.5, 0.5, 0.5, "yolov5s",
0.6, 0.6, 0.6, "yolov5m",
0.65, 0.65, 0.65, "yolov5l",
0.75, 0.75, 0.75, "yolov5x"
;
conf = yolo_nets[0];
yolov5 = new YOLOV5();
yolov5->Initialization(conf);
ui->textEditlog->append(QStringLiteral("默认模型类别：yolov5s args: %1 %2 %3")
.arg(conf.nmsThreshold)
.arg(conf.objThreshold)
.arg(conf.confThreshold));
void MainWindow::readFrame()
cv::Mat frame;
capture->read(frame);
if (frame.empty()) return;
auto start = std::chrono::steady_clock::now();
yolov5->detect(frame);
auto end = std::chrono::steady_clock::now();
std::chrono::duration<double, std::milli> elapsed = end - start;
ui->textEditlog->append(QString("cost_time: %1 ms").arg(elapsed.count()));
// double t0 = static_cast<double>(cv::getTickCount());
// yolov5->detect(frame);
// double t1 = static_cast<double>(cv::getTickCount());
// ui->textEditlog->append(QStringLiteral("cost_time: %1 ").arg((t1 - t0) / cv::getTickFrequency()));
cv::cvtColor(frame, frame, cv::COLOR_BGR2RGB);
QImage rawImage = QImage((uchar*)(frame.data),frame.cols,frame.rows,frame.step,QImage::Format_RGB888);
ui->label->setPixmap(QPixmap::fromImage(rawImage));
void MainWindow::on_openfile_clicked()
QString filename = QFileDialog::getOpenFileName(this,QStringLiteral("打开文件"),".","*.mp4 *.avi;;*.png *.jpg *.jpeg *.bmp");
if(!QFile::exists(filename))
return;
ui->statusbar->showMessage(filename);
QMimeDatabase db;
QMimeType mime = db.mimeTypeForFile(filename);
if (mime.name().startsWith("image/"))
cv::Mat src = cv::imread(filename.toLatin1().data());
if(src.empty())
ui->statusbar->showMessage("图像不存在！");
return;
cv::Mat temp;
if(src.channels()==4)
cv::cvtColor(src,temp,cv::COLOR_BGRA2RGB);
else if (src.channels()==3)
cv::cvtColor(src,temp,cv::COLOR_BGR2RGB);
else
cv::cvtColor(src,temp,cv::COLOR_GRAY2RGB);
auto start = std::chrono::steady_clock::now();
yolov5->detect(temp);
auto end = std::chrono::steady_clock::now();
std::chrono::duration<double, std::milli> elapsed = end - start;
ui->textEditlog->append(QString("cost_time: %1 ms").arg(elapsed.count()));
QImage img = QImage((uchar*)(temp.data),temp.cols,temp.rows,temp.step,QImage::Format_RGB888);
ui->label->setPixmap(QPixmap::fromImage(img));
ui->label->resize(ui->label->pixmap()->size());
filename.clear();
else if (mime.name().startsWith("video/"))
capture->open(filename.toLatin1().data());
if (!capture->isOpened())
ui->textEditlog->append("fail to open MP4!");
return;
IsDetect_ok +=1;
if (IsDetect_ok ==2)
ui->startdetect->setEnabled(true);
ui->textEditlog->append(QString::fromUtf8("Open video: %1 succesfully!").arg(filename));
//获取整个帧数QStringLiteral
long totalFrame = capture->get(cv::CAP_PROP_FRAME_COUNT);
ui->textEditlog->append(QStringLiteral("整个视频共 %1 帧").arg(totalFrame));
ui->label->resize(QSize(capture->get(cv::CAP_PROP_FRAME_WIDTH), capture->get(cv::CAP_PROP_FRAME_HEIGHT)));
//设置开始帧()
long frameToStart = 0;
capture->set(cv::CAP_PROP_POS_FRAMES, frameToStart);
ui->textEditlog->append(QStringLiteral("从第 %1 帧开始读").arg(frameToStart));
//获取帧率
double rate = capture->get(cv::CAP_PROP_FPS);
ui->textEditlog->append(QStringLiteral("帧率为: %1 ").arg(rate));
void MainWindow::on_loadfile_clicked()
QString onnxFile = QFileDialog::getOpenFileName(this,QStringLiteral("选择模型"),".","*.onnx");
if(!QFile::exists(onnxFile))
return;
ui->statusbar->showMessage(onnxFile);
if (!yolov5->loadModel(onnxFile.toLatin1().data()))
ui->textEditlog->append(QStringLiteral("加载模型失败！"));
return;
IsDetect_ok +=1;
ui->textEditlog->append(QString::fromUtf8("Open onnxFile: %1 succesfully!").arg(onnxFile));
if (IsDetect_ok ==2)
ui->startdetect->setEnabled(true);
void MainWindow::on_startdetect_clicked()
timer->start();
ui->startdetect->setEnabled(false);
ui->stopdetect->setEnabled(true);
ui->openfile->setEnabled(false);
ui->loadfile->setEnabled(false);
ui->comboBox->setEnabled(false);
ui->textEditlog->append(QStringLiteral("================\\n"
" 开始检测\\n"
"================\\n"));
void MainWindow::on_stopdetect_clicked()
ui->startdetect->setEnabled(true);
ui->stopdetect->setEnabled(false);
ui->openfile->setEnabled(true);
ui->loadfile->setEnabled(true);
ui->comboBox->setEnabled(true);
timer->stop();
ui->textEditlog->append(QStringLiteral("================\\n"
" 停止检测\\n"
"================\\n"));
void MainWindow::on_comboBox_activated(const QString &arg1)
if (arg1.contains("s"))
conf = yolo_nets[0];
else if (arg1.contains("m"))
conf = yolo_nets[1];
else if (arg1.contains("l"))
conf = yolo_nets[2];
else if (arg1.contains("x"))
conf = yolo_nets[3];
yolov5->Initialization(conf);
ui->textEditlog->append(QStringLiteral("使用模型类别：%1 args: %2 %3 %4")
.arg(arg1)
.arg(conf.nmsThreshold)
.arg(conf.objThreshold)
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