上一篇文章：yolov5目标检测多线程C++部署
V1 基本功能实现
mainwindow.h
#pragma once
#include <iostream>
#include <QMainWindow>
#include <QFileDialog>
#include <QThread>
#include <opencv2/opencv.hpp>
#include "yolov5.h"
#include "blockingconcurrentqueue.h"
QT_BEGIN_NAMESPACE
namespace Ui { class MainWindow; }
using namespace moodycamel;
QT_END_NAMESPACE
class Infer1 : public QThread
{
Q_OBJECT
public slots:
void receive_image(){};
private:
void run();
private:
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
};
class Infer2 : public QThread
{
Q_OBJECT
public slots:
void receive_image(){};
private:
void run();
private:
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
};
class MainWindow : public QMainWindow
{
Q_OBJECT
public:
MainWindow(QWidget *parent = nullptr);
~MainWindow();
private slots:
void on_pushButton_open_video_clicked();
void receive_image();
private:
Ui::MainWindow *ui;
Infer1 *infer1;
Infer2 *infer2;
signals:
void send_image();
};
mainwindow.cpp
#include "mainwindow.h"
#include "ui_mainwindow.h"
bool stop = false;
BlockingConcurrentQueue<cv::Mat> bcq_capture1, bcq_infer1;
BlockingConcurrentQueue<cv::Mat> bcq_capture2, bcq_infer2;
void print_time(int id)
{
auto now = std::chrono::system_clock::now();
uint64_t dis_millseconds = std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()).count()
- std::chrono::duration_cast<std::chrono::seconds>(now.time_since_epoch()).count() * 1000;
time_t tt = std::chrono::system_clock::to_time_t(now);
auto time_tm = localtime(&tt);
char time[100] = { 0 };
sprintf(time, "%d-%02d-%02d %02d:%02d:%02d %03d", time_tm->tm_year + 1900,
time_tm->tm_mon + 1, time_tm->tm_mday, time_tm->tm_hour,
time_tm->tm_min, time_tm->tm_sec, (int)dis_millseconds);
std::cout << "infer" << std::to_string(id) << " 当前时间为：" << time << std::endl;
}
void Infer1::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5n-w640h352.onnx");
while (true)
{
if(stop) break;
if(bcq_capture1.try_dequeue(input_image))
{
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
bcq_infer1.enqueue(output_image);
emit send_image();
print_time(1);
}
}
}
void Infer2::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5s-w640h352.onnx");
while (true)
{
if(stop) break;
if(bcq_capture2.try_dequeue(input_image))
{
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
bcq_infer2.enqueue(output_image);
emit send_image();
print_time(2);
}
}
}
MainWindow::MainWindow(QWidget *parent)
: QMainWindow(parent)
, ui(new Ui::MainWindow)
{
ui->setupUi(this);
infer1 = new Infer1;
infer2 = new Infer2;
connect(infer1, &Infer1::send_image, this, &MainWindow::receive_image);
connect(infer2, &Infer2::send_image, this, &MainWindow::receive_image);
}
MainWindow::~MainWindow()
{
delete ui;
}
void MainWindow::receive_image()
{
cv::Mat output_image;
if(bcq_infer1.try_dequeue(output_image))
{
QImage image = QImage((const uchar*)output_image.data, output_image.cols, output_image.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_1->clear();
ui->label_1->setPixmap(QPixmap::fromImage(image));
ui->label_1->show();
}
if(bcq_infer2.try_dequeue(output_image))
{
QImage image = QImage((const uchar*)output_image.data, output_image.cols, output_image.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_2->clear();
ui->label_2->setPixmap(QPixmap::fromImage(image));
ui->label_2->show();
}
}
void MainWindow::on_pushButton_open_video_clicked()
{
QString qstr = QFileDialog::getOpenFileName(this, tr("Open Video"), "", tr("(*.mp4 *.avi *.mkv)"));
if(qstr.isEmpty()) return;
infer1->start();
infer2->start();
cv::VideoCapture cap;
cap.open(qstr.toStdString());
while (cv::waitKey(1) < 0)
{
cv::Mat frame;
cap.read(frame);
if (frame.empty())
{
stop = true;
break;
}
bcq_capture1.enqueue(frame);
bcq_capture2.enqueue(frame);
}
}
这里引入的第三方库moodycamel::ConcurrentQueue是一个用C++11实现的多生产者、多消费者无锁队列。
程序输出：
infer1 当前时间为：2023-08-12 13:17:14 402
infer2 当前时间为：2023-08-12 13:17:14 424
infer1 当前时间为：2023-08-12 13:17:14 448
infer2 当前时间为：2023-08-12 13:17:14 480
infer1 当前时间为：2023-08-12 13:17:14 494
infer2 当前时间为：2023-08-12 13:17:14 532
infer1 当前时间为：2023-08-12 13:17:14 544
infer2 当前时间为：2023-08-12 13:17:14 586
infer1 当前时间为：2023-08-12 13:17:14 590
infer1 当前时间为：2023-08-12 13:17:14 637
infer2 当前时间为：2023-08-12 13:17:14 645
infer1 当前时间为：2023-08-12 13:17:14 678
infer2 当前时间为：2023-08-12 13:17:14 702
infer1 当前时间为：2023-08-12 13:17:14 719
infer2 当前时间为：2023-08-12 13:17:14 758
infer1 当前时间为：2023-08-12 13:17:14 760
infer1 当前时间为：2023-08-12 13:17:14 808
infer2 当前时间为：2023-08-12 13:17:14 817
infer1 当前时间为：2023-08-12 13:17:14 852
infer2 当前时间为：2023-08-12 13:17:14 881
...
界面效果：
可以看到，上面的程序实现了两个模型的多线程推理，但由于不同模型推理速度有差异，导致画面显示不同步。另外，把读取视频帧的实现写入主线程时，一旦视频帧读取结束则无法处理后面的帧，导致显示卡死。
V2 修正画面不同步问题
mainwindow.h
#pragma once
#include <iostream>
#include <QMainWindow>
#include <QFileDialog>
#include <QThread>
#include <opencv2/opencv.hpp>
#include "yolov5.h"
#include "blockingconcurrentqueue.h"
QT_BEGIN_NAMESPACE
namespace Ui { class MainWindow; }
using namespace moodycamel;
QT_END_NAMESPACE
class Capture : public QThread
{
Q_OBJECT
public:
void set_video(QString video)
{
cap.open(video.toStdString());
}
private:
void run();
private:
cv::VideoCapture cap;
};
class Infer1 : public QThread
{
Q_OBJECT
public slots:
void receive_image(){};
private:
void run();
private:
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
};
class Infer2 : public QThread
{
Q_OBJECT
public slots:
void receive_image(){};
private:
void run();
private:
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
};
class MainWindow : public QMainWindow
{
Q_OBJECT
public:
MainWindow(QWidget *parent = nullptr);
~MainWindow();
private slots:
void on_pushButton_open_video_clicked();
void receive_image();
private:
Ui::MainWindow *ui;
QString video;
Capture *capture;
Infer1 *infer1;
Infer2 *infer2;
signals:
void send_image();
};
mainwindow.cpp
#include "mainwindow.h"
#include "ui_mainwindow.h"
bool stop = false;
BlockingConcurrentQueue<cv::Mat> bcq_capture1, bcq_infer1;
BlockingConcurrentQueue<cv::Mat> bcq_capture2, bcq_infer2;
void print_time(int id)
{
auto now = std::chrono::system_clock::now();
uint64_t dis_millseconds = std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()).count()
- std::chrono::duration_cast<std::chrono::seconds>(now.time_since_epoch()).count() * 1000;
time_t tt = std::chrono::system_clock::to_time_t(now);
auto time_tm = localtime(&tt);
char time[100] = { 0 };
sprintf(time, "%d-%02d-%02d %02d:%02d:%02d %03d", time_tm->tm_year + 1900,
time_tm->tm_mon + 1, time_tm->tm_mday, time_tm->tm_hour,
time_tm->tm_min, time_tm->tm_sec, (int)dis_millseconds);
std::cout << "infer" << std::to_string(id) << " 当前时间为：" << time << std::endl;
}
void Capture::run()
{
while (cv::waitKey(50) < 0)
{
cv::Mat frame;
cap.read(frame);
if (frame.empty())
{
stop = true;
break;
}
bcq_capture1.enqueue(frame);
bcq_capture2.enqueue(frame);
}
}
void Infer1::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5n-w640h352.onnx");
while (true)
{
if(stop) break;
if(bcq_capture1.try_dequeue(input_image))
{
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
bcq_infer1.enqueue(output_image);
emit send_image();
print_time(1);
}
}
}
void Infer2::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5s-w640h352.onnx");
while (true)
{
if(stop) break;
if(bcq_capture2.try_dequeue(input_image))
{
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
bcq_infer2.enqueue(output_image);
emit send_image();
print_time(2);
}
}
}
MainWindow::MainWindow(QWidget *parent)
: QMainWindow(parent)
, ui(new Ui::MainWindow)
{
ui->setupUi(this);
capture = new Capture;
infer1 = new Infer1;
infer2 = new Infer2;
connect(infer1, &Infer1::send_image, this, &MainWindow::receive_image);
connect(infer2, &Infer2::send_image, this, &MainWindow::receive_image);
}
MainWindow::~MainWindow()
{
delete ui;
}
void MainWindow::receive_image()
{
cv::Mat output_image;
if(bcq_infer1.try_dequeue(output_image))
{
QImage image = QImage((const uchar*)output_image.data, output_image.cols, output_image.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_1->clear();
ui->label_1->setPixmap(QPixmap::fromImage(image));
ui->label_1->show();
}
if(bcq_infer2.try_dequeue(output_image))
{
QImage image = QImage((const uchar*)output_image.data, output_image.cols, output_image.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_2->clear();
ui->label_2->setPixmap(QPixmap::fromImage(image));
ui->label_2->show();
}
}
void MainWindow::on_pushButton_open_video_clicked()
{
video = QFileDialog::getOpenFileName(this, tr("Open Video"), "", tr("(*.mp4 *.avi *.mkv)"));
if(video.isEmpty()) return;
capture->set_video(video);
capture->start();
infer1->start();
infer2->start();
}
界面显示：
V3 修正视频播放完成界面显示问题
和V2比较，V3的改动不大，仅增加在视频播放完成时发出信号调用清除界面显示的功能。
mainwindow.h
#pragma once
#include <iostream>
#include <QMainWindow>
#include <QFileDialog>
#include <QThread>
#include <opencv2/opencv.hpp>
#include "yolov5.h"
#include "blockingconcurrentqueue.h"
QT_BEGIN_NAMESPACE
namespace Ui { class MainWindow; }
using namespace moodycamel;
QT_END_NAMESPACE
class Capture : public QThread
{
Q_OBJECT
public:
void set_video(QString video)
{
cap.open(video.toStdString());
}
private:
void run();
private:
cv::VideoCapture cap;
signals:
void stop();
};
class Infer1 : public QThread
{
Q_OBJECT
private:
void run();
private:
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
};
class Infer2 : public QThread
{
Q_OBJECT
private:
void run();
private:
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
};
class MainWindow : public QMainWindow
{
Q_OBJECT
public:
MainWindow(QWidget *parent = nullptr);
~MainWindow();
private slots:
void on_pushButton_open_video_clicked();
void receive_image();
void clear_image();
private:
Ui::MainWindow *ui;
QString video;
Capture *capture;
Infer1 *infer1;
Infer2 *infer2;
};
mainwindow.cpp
#include "mainwindow.h"
#include "ui_mainwindow.h"
bool flag = false;
BlockingConcurrentQueue<cv::Mat> bcq_capture1, bcq_infer1;
BlockingConcurrentQueue<cv::Mat> bcq_capture2, bcq_infer2;
void print_time(int id)
{
auto now = std::chrono::system_clock::now();
uint64_t dis_millseconds = std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()).count()
- std::chrono::duration_cast<std::chrono::seconds>(now.time_since_epoch()).count() * 1000;
time_t tt = std::chrono::system_clock::to_time_t(now);
auto time_tm = localtime(&tt);
char time[100] = { 0 };
sprintf(time, "%d-%02d-%02d %02d:%02d:%02d %03d", time_tm->tm_year + 1900,
time_tm->tm_mon + 1, time_tm->tm_mday, time_tm->tm_hour,
time_tm->tm_min, time_tm->tm_sec, (int)dis_millseconds);
std::cout << "infer" << std::to_string(id) << " 当前时间为：" << time << std::endl;
}
void Capture::run()
{
while (cv::waitKey(50) < 0)
{
cv::Mat frame;
cap.read(frame);
if (frame.empty())
{
flag = true;
emit stop();
break;
}
bcq_capture1.enqueue(frame);
bcq_capture2.enqueue(frame);
}
}
void Infer1::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5n-w640h352.onnx");
while (true)
{
if(flag) break;
if(bcq_capture1.try_dequeue(input_image))
{
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
bcq_infer1.enqueue(output_image);
emit send_image();
print_time(1);
}
std::this_thread::yield();
}
}
void Infer2::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5s-w640h352.onnx");
while (true)
{
if(flag) break;
if(bcq_capture2.try_dequeue(input_image))
{
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
bcq_infer2.enqueue(output_image);
emit send_image();
print_time(2);
}
std::this_thread::yield();
}
}
MainWindow::MainWindow(QWidget *parent)
: QMainWindow(parent)
, ui(new Ui::MainWindow)
{
ui->setupUi(this);
capture = new Capture;
infer1 = new Infer1;
infer2 = new Infer2;
connect(infer1, &Infer1::send_image, this, &MainWindow::receive_image);
connect(infer2, &Infer2::send_image, this, &MainWindow::receive_image);
connect(capture, &Capture::stop, this, &MainWindow::clear_image);
}
MainWindow::~MainWindow()
{
delete ui;
}
void MainWindow::on_pushButton_open_video_clicked()
{
video = QFileDialog::getOpenFileName(this, tr("Open Video"), "", tr("(*.mp4 *.avi *.mkv)"));
if(video.isEmpty()) return;
capture->set_video(video);
capture->start();
infer1->start();
infer2->start();
}
void MainWindow::receive_image()
{
cv::Mat output_image;
if(bcq_infer1.try_dequeue(output_image))
{
QImage image = QImage((const uchar*)output_image.data, output_image.cols, output_image.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_1->clear();
ui->label_1->setPixmap(QPixmap::fromImage(image));
ui->label_1->show();
}
if(bcq_infer2.try_dequeue(output_image))
{
QImage image = QImage((const uchar*)output_image.data, output_image.cols, output_image.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_2->clear();
ui->label_2->setPixmap(QPixmap::fromImage(image));
ui->label_2->show();
}
}
void MainWindow::clear_image()
{
ui->label_1->clear();
ui->label_2->clear();
}
V4 通过Qt自带QThread、QMutex、QWaitCondition实现
mainwindow.h
#pragma once
#include <iostream>
#include <QMainWindow>
#include <QFileDialog>
#include <QThread>
#include <QMutex>
#include <QWaitCondition>
#include <opencv2/opencv.hpp>
#include "yolov5.h"
QT_BEGIN_NAMESPACE
namespace Ui { class MainWindow; }
QT_END_NAMESPACE
class Capture : public QThread
{
Q_OBJECT
public:
void set_video(QString video)
{
cap.open(video.toStdString());
}
private:
void run();
private:
cv::VideoCapture cap;
signals:
void stop();
};
class Infer1 : public QThread
{
Q_OBJECT
public:
void set_model(QString model)
{
net = cv::dnn::readNet(model.toStdString());
}
private:
void run();
private:
cv::dnn::Net net;
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
void stop();
};
class Infer2 : public QThread
{
Q_OBJECT
public:
void set_model(QString model)
{
net = cv::dnn::readNet(model.toStdString());
}
private:
void run();
private:
cv::dnn::Net net;
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
signals:
void send_image();
void stop();
};
class MainWindow : public QMainWindow
{
Q_OBJECT
public:
MainWindow(QWidget *parent = nullptr);
~MainWindow();
private slots:
void on_pushButton_open_video_clicked();
void receive_image();
void clear_image();
private:
Ui::MainWindow *ui;
QString video;
Capture *capture;
Infer1 *infer1;
Infer2 *infer2;
};
mainwindow.cpp
#include "mainwindow.h"
#include "ui_mainwindow.h"
bool video_end = false;
QMutex mutex1, mutex2;
QWaitCondition qwc1, qwc2;
cv::Mat g_frame1, g_frame2;
cv::Mat g_result1, g_result2;
void print_time(int id)
{
auto now = std::chrono::system_clock::now();
uint64_t dis_millseconds = std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()).count()
- std::chrono::duration_cast<std::chrono::seconds>(now.time_since_epoch()).count() * 1000;
time_t tt = std::chrono::system_clock::to_time_t(now);
auto time_tm = localtime(&tt);
char time[100] = { 0 };
sprintf(time, "%d-%02d-%02d %02d:%02d:%02d %03d", time_tm->tm_year + 1900,
time_tm->tm_mon + 1, time_tm->tm_mday, time_tm->tm_hour,
time_tm->tm_min, time_tm->tm_sec, (int)dis_millseconds);
std::cout << "infer" << std::to_string(id) << " 当前时间为：" << time << std::endl;
}
void Capture::run()
{
while (cv::waitKey(1) < 0)
{
cv::Mat frame;
cap.read(frame);
if (frame.empty())
{
video_end = true;
cap.release();
emit stop();
break;
}
g_frame1 = frame;
qwc1.wakeAll();
g_frame2 = frame;
qwc2.wakeAll();
}
}
void Infer1::run()
{
while (true)
{
if(video_end)
{
emit stop();
break;
}
mutex1.lock();
qwc1.wait(&mutex1);
input_image = g_frame1;
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
g_result1 = output_image;
emit send_image();
mutex1.unlock();
print_time(1);
}
}
void Infer2::run()
{
while (true)
{
if(video_end)
{
emit stop();
break;
}
mutex2.lock();
qwc2.wait(&mutex2);
input_image = g_frame2;
pre_process(input_image, blob);
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
g_result2 = output_image;
emit send_image();
mutex2.unlock();
print_time(2);
}
}
MainWindow::MainWindow(QWidget *parent)
: QMainWindow(parent)
, ui(new Ui::MainWindow)
{
ui->setupUi(this);
capture = new Capture;
infer1 = new Infer1;
infer2 = new Infer2;
connect(capture, &Capture::stop, this, &MainWindow::clear_image);
connect(infer1, &Infer1::send_image, this, &MainWindow::receive_image);
connect(infer1, &Infer1::stop, this, &MainWindow::clear_image);
connect(infer2, &Infer2::send_image, this, &MainWindow::receive_image);
connect(infer2, &Infer2::stop, this, &MainWindow::clear_image);
}
MainWindow::~MainWindow()
{
delete ui;
}
void MainWindow::on_pushButton_open_video_clicked()
{
video = QFileDialog::getOpenFileName(this, tr("Open Video"), "", tr("(*.mp4 *.avi *.mkv)"));
if(video.isEmpty()) return;
video_end = false;
capture->set_video(video);
infer1->set_model("yolov5n-w640h352.onnx");
infer2->set_model("yolov5s-w640h352.onnx");
capture->start();
infer1->start();
infer2->start();
}
void MainWindow::receive_image()
{
QImage image1 = QImage((const uchar*)g_result1.data, g_result1.cols, g_result1.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_1->clear();
ui->label_1->setPixmap(QPixmap::fromImage(image1));
ui->label_1->show();
QImage image2 = QImage((const uchar*)g_result2.data, g_result2.cols, g_result2.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_2->clear();
ui->label_2->setPixmap(QPixmap::fromImage(image2));
ui->label_2->show();
}
void MainWindow::clear_image()
{
ui->label_1->clear();
ui->label_2->clear();
capture->quit();
infer1->quit();
infer2->quit();
}
V5 通过std::mutex、std::condition_variable、std::promise实现
mainwindow.h
#pragma once
#include <iostream>
#include <string>
#include <queue>
#include <thread>
#include <mutex>
#include <condition_variable>
#include <future>
#include <ctime>
#include <windows.h>
#include <QMainWindow>
#include <QFileDialog>
#include <QThread>
#include <QMutex>
#include <QWaitCondition>
#include <opencv2/opencv.hpp>
#include "yolov5.h"
QT_BEGIN_NAMESPACE
namespace Ui { class MainWindow; }
QT_END_NAMESPACE
class Capture : public QThread
{
Q_OBJECT
public:
void set_capture(QString video)
{
cap.open(video.toStdString());
}
private:
void run();
private:
cv::VideoCapture cap;
signals:
void show();
void stop();
};
class Infer1 : public QThread
{
Q_OBJECT
public:
void set_model(QString model)
{
net = cv::dnn::readNet(model.toStdString());
}
private:
void run();
private:
cv::dnn::Net net;
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
};
class Infer2 : public QThread
{
Q_OBJECT
public:
void set_model(QString model)
{
net = cv::dnn::readNet(model.toStdString());
}
private:
void run();
private:
cv::dnn::Net net;
cv::Mat input_image;
cv::Mat blob;
cv::Mat output_image;
std::vector<cv::Mat> network_outputs;
};
class MainWindow : public QMainWindow
{
Q_OBJECT
public:
MainWindow(QWidget *parent = nullptr);
~MainWindow();
private slots:
void receive_image();
void clear_image();
void on_pushButton_open_video_clicked();
private:
Ui::MainWindow *ui;
QString video;
Capture *capture;
Infer1 *infer1;
Infer2 *infer2;
};
mainwindow.cpp文章来源：https://www.toymoban.com/news/detail-644750.html
#include "mainwindow.h"
#include "ui_mainwindow.h"
struct Job
{
cv::Mat input_image;
std::shared_ptr<std::promise<cv::Mat>> output_image;
};
std::queue<Job> jobs1, jobs2;
std::mutex lock1, lock2;
std::condition_variable cv1, cv2;
cv::Mat result1, result2;
const int limit = 10;
bool video_end = false;
void print_time(int id)
{
auto now = std::chrono::system_clock::now();
uint64_t dis_millseconds = std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()).count()
- std::chrono::duration_cast<std::chrono::seconds>(now.time_since_epoch()).count() * 1000;
time_t tt = std::chrono::system_clock::to_time_t(now);
auto time_tm = localtime(&tt);
char time[100] = { 0 };
sprintf(time, "%d-%02d-%02d %02d:%02d:%02d %03d", time_tm->tm_year + 1900,
time_tm->tm_mon + 1, time_tm->tm_mday, time_tm->tm_hour,
time_tm->tm_min, time_tm->tm_sec, (int)dis_millseconds);
std::cout << "infer" << std::to_string(id) << ": 当前时间为：" << time << std::endl;
}
void Capture::run()
{
while (cv::waitKey(1) < 0)
{
Job job1, job2;
cv::Mat frame;
cap.read(frame);
if (frame.empty())
{
video_end = true;
emit stop();
break;
}
{
std::unique_lock<std::mutex> l1(lock1);
cv1.wait(l1, [&]() { return jobs1.size()<limit; });
job1.input_image = frame;
job1.output_image.reset(new std::promise<cv::Mat>());
jobs1.push(job1);
}
{
std::unique_lock<std::mutex> l2(lock2);
cv1.wait(l2, [&]() { return jobs2.size() < limit; });
job2.input_image = frame;
job2.output_image.reset(new std::promise<cv::Mat>());
jobs2.push(job2);
}
result1 = job1.output_image->get_future().get();
result2 = job2.output_image->get_future().get();
emit show();
}
}
void Infer1::run()
{
while (true)
{
if (video_end)
break; //不加线程无法退出
if (!jobs1.empty())
{
std::lock_guard<std::mutex> l1(lock1);
auto job = jobs1.front();
jobs1.pop();
cv1.notify_all();
cv::Mat input_image = job.input_image, blob, output_image;
pre_process(input_image, blob);
std::vector<cv::Mat> network_outputs;
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
job.output_image->set_value(output_image);
print_time(0);
}
std::this_thread::yield(); //不加线程无法退出
}
}
void Infer2::run()
{
cv::dnn::Net net = cv::dnn::readNet("yolov5s-w640h352.onnx");
while (true)
{
if (video_end)
break;
if (!jobs2.empty())
{
std::lock_guard<std::mutex> l2(lock2);
auto job = jobs2.front();
jobs2.pop();
cv2.notify_all();
cv::Mat input_image = job.input_image, blob, output_image;
pre_process(input_image, blob);
std::vector<cv::Mat> network_outputs;
process(blob, net, network_outputs);
post_process(input_image, output_image, network_outputs);
job.output_image->set_value(output_image);
print_time(1);
}
std::this_thread::yield();
}
}
MainWindow::MainWindow(QWidget *parent)
: QMainWindow(parent)
, ui(new Ui::MainWindow)
{
ui->setupUi(this);
capture = new Capture;
infer1 = new Infer1;
infer2 = new Infer2;
connect(capture, &Capture::stop, this, &MainWindow::clear_image);
connect(capture, &Capture::show, this, &MainWindow::receive_image);
}
MainWindow::~MainWindow()
{
delete ui;
}
void MainWindow::receive_image()
{
QImage image1 = QImage((const uchar*)result1.data, result1.cols, result1.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_1->clear();
ui->label_1->setPixmap(QPixmap::fromImage(image1));
ui->label_1->show();
QImage image2 = QImage((const uchar*)result2.data, result2.cols, result2.rows, QImage::Format_RGB888).rgbSwapped();
ui->label_2->clear();
ui->label_2->setPixmap(QPixmap::fromImage(image2));
ui->label_2->show();
}
void MainWindow::clear_image()
{
ui->label_1->clear();
ui->label_2->clear();
capture->quit();
infer1->quit();
infer2->quit();
}
void MainWindow::on_pushButton_open_video_clicked()
{
video = QFileDialog::getOpenFileName(this, tr("Open Video"), "", tr("(*.mp4 *.avi *.mkv *mpg *wmv)"));
if(video.isEmpty()) return;
video_end = false;
capture->set_capture(video);
infer1->set_model("yolov5n-w640h352.onnx");
infer2->set_model("yolov5s-w640h352.onnx");
capture->start();
infer1->start();
infer2->start();
}
完整工程下载链接：yolov5目标检测多线程Qt界面文章来源地址https://www.toymoban.com/news/detail-644750.html
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