C++ OpenCV学习笔记(多线程,多个摄像头进行基于Haar+Adaboost实现的人脸检测功能)

 C++ OpenCV学习笔记(多线程,多个摄像头进行基于Haar+Adaboost实现的人脸检测功能)_第1张图片

#include   
#include   
#include   

#include   
#include   
#include    
#include 

using namespace std;
using namespace cv;

DWORD WINAPI Fun1(LPVOID lpParamter)
{
	int number = 0;
	// 【1】加载分类器  
	CascadeClassifier cascade;
	cascade.load("F:\\opencv\\haarcascade_frontalface_alt.xml");

	Mat frame;
	Mat image;
	Mat grayImage;

	VideoCapture cap(0);

	namedWindow("笔记本摄像头检测", 0);

	cout << "按下esc退出检测!" << endl;
	while (cap.read(frame))
	{
		char c = waitKey(30);
		if (c == 27)
		{
			break;
		}
		while (number >= 30)
		{
			number = 0;
			frame.copyTo(image);
			cvtColor(image, grayImage, CV_BGR2GRAY); // 生成灰度图,提高检测效率  

			// 定义7种颜色,用于标记人脸  
			Scalar colors[] =
			{
				// 红橙黄绿青蓝紫  
				CV_RGB(255, 0, 0),
				CV_RGB(255, 97, 0),
				CV_RGB(255, 255, 0),
				CV_RGB(0, 255, 0),
				CV_RGB(0, 255, 255),
				CV_RGB(0, 0, 255),
				CV_RGB(160, 32, 240)
			};

			// 【3】检测  
			vector rect;
			cascade.detectMultiScale(grayImage, rect, 1.1, 3, 0);  // 分类器对象调用  

			printf("笔记本摄像头检测到人脸个数:%d\n", rect.size());

			// 【4】标记--在脸部画圆  
			for (int i = 0; i < rect.size(); i++)
			{
				Point  center;
				int radius;
				center.x = cvRound((rect[i].x + rect[i].width * 0.5));
				center.y = cvRound((rect[i].y + rect[i].height * 0.5));

				radius = cvRound((rect[i].width + rect[i].height) * 0.25);
				circle(frame, center, radius, colors[i % 7], 2);
			}
		}
		number++;
		// 【5】显示  
		imshow("笔记本摄像头检测", frame);
	}
	cap.release();//释放资源
	return 0L;
}

DWORD WINAPI Fun2(LPVOID lpParamter)
{
	int number = 0;
	// 【1】加载分类器  
	CascadeClassifier cascade;
	cascade.load("F:\\opencv\\haarcascade_frontalface_alt.xml");

	Mat frame;
	Mat image;
	Mat grayImage;

	VideoCapture cap(1);

	namedWindow("外接摄像头检测", 0);

	cout << "按下esc退出检测!" << endl;
	while (cap.read(frame))
	{
		char c = waitKey(30);
		if (c == 27)
		{
			break;
		}
		while (number >= 30)
		{
			number = 0;
			frame.copyTo(image);
			cvtColor(image, grayImage, CV_BGR2GRAY); // 生成灰度图,提高检测效率  

			// 定义7种颜色,用于标记人脸  
			Scalar colors[] =
			{
				// 红橙黄绿青蓝紫  
				CV_RGB(255, 0, 0),
				CV_RGB(255, 97, 0),
				CV_RGB(255, 255, 0),
				CV_RGB(0, 255, 0),
				CV_RGB(0, 255, 255),
				CV_RGB(0, 0, 255),
				CV_RGB(160, 32, 240)
			};

			// 【3】检测  
			vector rect;
			cascade.detectMultiScale(grayImage, rect, 1.1, 3, 0);  // 分类器对象调用  

			printf("外接摄像头检测到人脸个数:%d\n", rect.size());

			// 【4】标记--在脸部画圆  
			for (int i = 0; i < rect.size(); i++)
			{
				Point  center;
				int radius;
				center.x = cvRound((rect[i].x + rect[i].width * 0.5));
				center.y = cvRound((rect[i].y + rect[i].height * 0.5));

				radius = cvRound((rect[i].width + rect[i].height) * 0.25);
				circle(frame, center, radius, colors[i % 7], 2);
			}
		}
		number++;
		// 【5】显示  
		imshow("外接摄像头检测", frame);
	}
	cap.release();//释放资源
	return 0L;
}

int main()
{
	HANDLE hThread1 = CreateThread(NULL, 0, Fun1, NULL, 0, NULL);
	CloseHandle(hThread1);
	HANDLE hThread2 = CreateThread(NULL, 0, Fun2, NULL, 0, NULL);
	CloseHandle(hThread2);
	while (true)
	{
		cout << "Main Thread Display!" << endl;
		Sleep(3000);
	}
	return 0;
}

 

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