对单个图片进行模板匹配

对单个图片进行模板匹配

#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
using namespace std;
#define WINDOW_NAME1 "【原始图片】"        //为窗口标题定义的宏 
#define WINDOW_NAME2 "【匹配窗口】"        //为窗口标题定义的宏 
Mat g_srcImage; Mat g_templateImage; Mat g_resultImage;
int g_nMatchMethod;
int g_nMaxTrackbarNum = 5;
static void ShowHelpText()
{
	printf("\n\n 当前使用的OpenCV版本为：" CV_VERSION);
	printf("\n\n  ----------------------------------------------------------------------------\n");
	//输出一些帮助信息
	printf("\t欢迎来到【模板匹配】示例程序~\n");
	printf("\n\n\t请调整滑动条观察图像效果\n\n");
	printf("\n\t滑动条对应的方法数值说明: \n\n"
		"\t\t方法【0】- 平方差匹配法(SQDIFF)\n"
		"\t\t方法【1】- 归一化平方差匹配法(SQDIFF NORMED)\n"
		"\t\t方法【2】- 相关匹配法(TM CCORR)\n"
		"\t\t方法【3】- 归一化相关匹配法(TM CCORR NORMED)\n"
		"\t\t方法【4】- 相关系数匹配法(TM COEFF)\n"
		"\t\t方法【5】- 归一化相关系数匹配法(TM COEFF NORMED)\n");
}

void on_Matching(int, void*)
{
	//【1】给局部变量初始化
	Mat srcImage;
	g_srcImage.copyTo(srcImage);

	//【2】初始化用于结果输出的矩阵
	int resultImage_rows = g_srcImage.rows - g_templateImage.rows + 1;
	int resultImage_cols = g_srcImage.cols - g_templateImage.cols + 1;
	g_resultImage.create(resultImage_rows, resultImage_cols, CV_32FC1);

	//【3】进行匹配和标准化
	// 当模板匹配采用CV_TM_SQDIFF（g_nMatchMethod = 0）模式时，minValue值越小，说明匹配度越高
	matchTemplate(g_srcImage, g_templateImage, g_resultImage, g_nMatchMethod);
	normalize(g_resultImage, g_resultImage, 0, 1, NORM_MINMAX, -1, Mat());

	//【4】通过函数 minMaxLoc 定位最匹配的位置
	double minValue;  
	double maxValue; 
	Point minLocation;
	Point maxLocation;
	Point matchLocation;
	minMaxLoc(g_resultImage, &minValue, &maxValue, &minLocation, &maxLocation, Mat());

	//【5】对于方法 SQDIFF 和 SQDIFF_NORMED, 越小的数值有着更高的匹配结果. 而其余的方法, 数值越大匹配效果越好
	if (g_nMatchMethod == TM_SQDIFF || g_nMatchMethod == TM_SQDIFF_NORMED)
	{
		matchLocation = minLocation;
	}
	else
	{
		matchLocation = maxLocation;
	}

	//【6】绘制出矩形，并显示最终结果
	rectangle(srcImage, matchLocation, Point(matchLocation.x + g_templateImage.cols, matchLocation.y + g_templateImage.rows), Scalar(0, 0, 255), 2, 8, 0);
	rectangle(g_resultImage, matchLocation, Point(matchLocation.x + g_templateImage.cols, matchLocation.y + g_templateImage.rows), Scalar(0, 0, 255), 2, 8, 0);

	imshow(WINDOW_NAME1, srcImage);
	imshow(WINDOW_NAME2, g_resultImage);
}

int main()
{
	//【0】改变console字体颜色
	system("color 1F");

	//【0】显示帮助文字
	ShowHelpText();

	//【1】载入原图像和模板块
	g_srcImage = imread("1.jpg", 1);
	g_templateImage = imread("2.jpg", 1);

	//【2】创建窗口
	namedWindow(WINDOW_NAME1, WINDOW_AUTOSIZE);
	namedWindow(WINDOW_NAME2, WINDOW_AUTOSIZE);

	//【3】创建滑动条并进行一次初始化
	createTrackbar("方法", WINDOW_NAME1, &g_nMatchMethod, g_nMaxTrackbarNum, on_Matching);
	on_Matching(0, 0);

	waitKey(0);
	return 0;

}

对视频流进行模板匹配

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

#define  TPL_WIDTH       40      /* template width       */
#define  TPL_HEIGHT      40      /* template height      */

bool template_selected = false;
int ROIx, ROIy;
Mat frame, templateimage, templatematch;

static void onMouse(int event, int x, int y, int, void*);

int main(int argc, char** argv)
{
    
    
    int c = 0;
    Point minloc, maxloc;
    double  minval, maxval;

    VideoCapture cap(0);            // open the default camera
    if (!cap.isOpened()) return -1;      // Check if camera opened

    namedWindow("FrameWin", CV_WINDOW_AUTOSIZE);
    namedWindow("template", CV_WINDOW_AUTOSIZE);

    setMouseCallback("FrameWin", onMouse, 0);


    // Open the template image 
    templateimage = imread("./103044.jpg");

    if (!templateimage.empty()) {
    
    
        printf("Read template image: Rows = %i \t Cols = %i \n", templateimage.rows, templateimage.cols);
        template_selected = true;
    }
    else {
    
     printf("No template image found. Left click to define template\n"); }


    while (c != 'q') {
    
    
        cap >> frame;

        if (template_selected) {
    
    
            matchTemplate(frame, templateimage, templatematch, CV_TM_SQDIFF_NORMED);
            normalize(templatematch, templatematch, 0, 1, NORM_MINMAX, -1, Mat());
            minMaxLoc(templatematch, &minval, &maxval, &minloc, &maxloc, Mat());
            rectangle(frame, minloc, Point(minloc.x + TPL_WIDTH, minloc.y + TPL_HEIGHT), Scalar::all(0), 2, 8, 0);
        }

        imshow("FrameWin", frame);
        imshow("template", templateimage);

        c = cvWaitKey(100);

        if (c == 's') {
    
    
            imwrite("template.jpg", templateimage);
            cout << "Left button of the mouse is clicked - position (" << ROIx << ", " << ROIy << ")" << endl;
            cout << "Saved the template to template.jpg" << endl;
        }
    }
    destroyWindow("FrameWin");
    destroyWindow("template");
    return 0;
}

static void onMouse(int event, int x, int y, int, void*) {
    
    
    if (event == EVENT_LBUTTONDOWN)
    {
    
    
        ROIx = x - (TPL_WIDTH / 2);
        ROIy = y - (TPL_HEIGHT / 2);

        // Copy the ROI to the template image 
        templateimage = frame(cvRect(ROIx, ROIy, TPL_WIDTH, TPL_HEIGHT));
        //frame.copyTo(templateimage(Rect( ROIx,ROIy,TPL_WIDTH,TPL_HEIGHT)));


        template_selected = true;
    }
}