#include <opencv2/opencv.hpp> #include <iostream> #include <opencv2/highgui/highgui.hpp> #include <math.h> using namespace std; using namespace cv; Mat src, temp, dst; int match_method = TM_SQDIFF; int max_track = 5; const char* INPUT_T = "temp image"; const char* OUTPUT_T = "result image"; const char* match_t = "template match-demo"; void Match_Demo(int, void*); int main(int argc, char** argv) { // 待检测图像 src = imread("E://VS-pro//images//zhu2.jpg"); // 模板图像 temp = imread("E://VS-pro//images//zhu2temp.bmp"); if (src.empty() || temp.empty()) { printf("could not load image...\n"); return -1; } namedWindow(INPUT_T); namedWindow(OUTPUT_T); namedWindow(match_t); imshow(INPUT_T, temp); //trackbar 变化的是 不同的匹配方法 从0到5共6种 const char* trackbar_title = "Match Algo Type:"; createTrackbar(trackbar_title, OUTPUT_T, &match_method, max_track, Match_Demo); Match_Demo(0, 0); waitKey(0); return 0; } void Match_Demo(int, void*) { //放结果 MAT 必为单通道32位浮点数 结果必须是 (src.cols - temp.rows + 1) * (src.cols - temp.rows + 1) int width = src.cols - temp.cols + 1; int height = src.rows - temp.rows + 1; Mat result; result.create(Size(width, height), CV_32FC1); //进行模板匹配以及归一化 matchTemplate(src, temp, result, match_method, Mat()); normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat()); Point minloc; Point maxloc; //放result中点的位置 double max, min; //存放result中值的大小 Point temloc; src.copyTo(dst); //minMaxLoc寻找矩阵(一维数组当作向量,用Mat定义) 中最小值和最大值的位置. //用minMaxLoc寻找result中最可能的结果; minMaxLoc(result, &min, &max, &minloc, &maxloc, Mat()); //若匹配方法为0 1 则最小值为最匹配结果 其余则最大值为最匹配结果 if (match_method <= 1) { temloc = minloc; } else { temloc = maxloc; } //画矩形(画出匹配位置 最匹配"点"加上temp模板大小即为匹配位置) rectangle(dst, Rect(temloc.x, temloc.y, temp.cols, temp.rows), Scalar(0, 0, 255), 2, 8); rectangle(result, Rect(temloc.x, temloc.y, temp.cols, temp.rows), Scalar(0, 0, 255), 2, 8); imshow(match_t, dst); imshow(OUTPUT_T, result); }