Opencv实现微信跳一跳 （C++实现，区域截图条用了Python）

#define _CRT_SECURE_NO_WARNINGS #include<opencv2/opencv.hpp> #include<iostream> #include<math.h> #include <windows.h> #include <list> using namespace cv; using namespace std; //截取跳一跳屏幕 void ScreenShot(void); //获取Character坐标 Point GetNowPoint(Mat& srcImage, Mat& Tem_img); //获取下一个要跳的点 Point GetNextPoint(Mat& srcImage); //计算距离 int GetDistance(Point& first_point, Point& next_point); //跳跃 void Jump(int&g_distance); int main(int argc, char** argv) { ScreenShot(); //截取图片 Sleep(1000); Mat dstImage; Mat Character; // system("color 3F"); while (true) { // get_screenshot(); Mat srcImage = imread("helloworld.jpg", IMREAD_GRAYSCALE); //读取图片 dstImage = srcImage.clone(); Character = imread("template.jpg", IMREAD_GRAYSCALE); //读取样本 //imshow("Character",Character); //cvtColor(srcImage,srcImage,CV_BGR2GRAY); Point nowPoint = GetNowPoint(srcImage, Character); cout << "nowPoint:" << nowPoint << endl; Point nextPoint = GetNextPoint(srcImage); cout << "nextPoint:" << nextPoint << endl; int nDistance = GetDistance(nowPoint, nextPoint); Jump(nDistance); Sleep(1000); ScreenShot(); Sleep(1000); } return 0; } Point GetNowPoint(Mat& srcImage, Mat& Tem_img) { cv::Mat image_matched; matchTemplate(srcImage, Tem_img, image_matched, CV_TM_SQDIFF);// 匹配黑棋子 double minVal, maxVal; Point minLoc, maxLoc, matchLoc; minMaxLoc(image_matched, &minVal, &maxVal, &minLoc, &maxLoc, Mat()); matchLoc = minLoc; //matchLoc是最佳匹配的区域左上角点 return Point(matchLoc.x + Tem_img.cols*0.5, matchLoc.y + Tem_img.rows); } Point GetNextPoint(Mat& srcImage) { cv::Point point1; cv::Point point2; cv::GaussianBlur(srcImage, srcImage, cv::Size(5, 5), 0); //高斯滤波，降低噪声 // cv::threshold(srcImage, srcImage, 0, 255, 8); Canny(srcImage, srcImage, 20, 30); //进行边缘检测 vector<vector<Point>> contours; vector<Vec4i> hierarchy; findContours(srcImage, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point()); //找到关键的角点 //遍历每一个轮廓，把多余的轮廓去掉 std::vector<std::vector<cv::Point> >::const_iterator it = contours.begin(); while (it != contours.end()) { if (it->size()<150) it = contours.erase(it); else ++it; } int nYMin = srcImage.rows; int nXMin = srcImage.cols; int nYMax = 0; int nXMax = 0; int nIdY = 0; for (int i = 0; i < contours.size(); i++) { //contours[i]代表的是第i个轮廓，contours[i].size()代表的是第i个轮廓上所有的像素点数 for (int j = 0; j < contours[i].size(); j++) { if (contours[i][j].y < nYMin) { nYMin = contours[i][j].y; //找到最低的y值 point1 = contours[i][j]; //记录 y值最低点坐标 nIdY = i; //记录哪个区域内的 } } } int minY = srcImage.cols; for (int j = 0; j < contours[nIdY].size(); j++) //在哪个区域内继续变量 找到x最大值 { if (contours[nIdY][j].x >nXMax) { nXMax = contours[nIdY][j].x; } } for (int j = 0; j < contours[nIdY].size(); j++) {//找到x中最大值上的最小值 if (contours[nIdY][j].x == nXMax && contours[nIdY][j].y < minY) { point2 = contours[nIdY][j]; minY = contours[nIdY][j].y; //记录X点的最大值 } } return cv::Point(point1.x, point2.y); //返回中点坐标 } int GetDistance(Point& first_point, Point& next_point) { int A = first_point.x - next_point.x; int B = first_point.y - (next_point.y + 50); return int(pow(pow(A, 2) + pow(B, 2), 0.5)); } void Jump(int&g_distance) { cout << "distance:" << g_distance << endl; int time = g_distance*4+330; RECT rect; HWND hwnd = ::FindWindow(NULL, L"实时演示"); GetWindowRect(hwnd, &rect); ::SetCursorPos(rect.left+100, rect.bottom-500); INPUT Input = { 0 }; //鼠标按下 Input.type = INPUT_MOUSE; Input.mi.dwFlags = MOUSEEVENTF_LEFTDOWN; SendInput(1, &Input, sizeof(INPUT)); Sleep(time);//鼠标下的时间 Input = { 0 }; //鼠标松开 Input.type = INPUT_MOUSE; Input.mi.dwFlags = MOUSEEVENTF_LEFTUP; SendInput(1, &Input, sizeof(INPUT)); } void ScreenShot(void) { RECT rect; HWND hwnd = ::FindWindow(NULL, L"实时演示"); //获取360演示的句柄 GetWindowRect(hwnd, &rect); //获取图像的位置 char sScreenShot[64]; sprintf(sScreenShot, "grab.exe %d %d %d %d", rect.left, rect.top+135, rect.right, rect.bottom-50);//组成字符串 system(sScreenShot); //调用python截取图片 }