OpenCV实现马赛克和毛玻璃滤镜特效

#include <opencv2/core/core.hpp>#include <opencv2/highgui/highgui.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <iostream> using namespace cv;using namespace std; Mat inputImage;Mat inputImage_mosaic;Mat inputImage_clone; //马赛克的大小int neightbourhood = 20; //记录鼠标的状态，0为鼠标左键未按下或弹起，1为鼠标左键按下int mouseStatus = 0; void onMouse(int events, int x, int y, int flag, void* ustg); //创建马赛克图片void createMosaicImage(Mat inputMat, Mat& outputMat, int size); //设置马赛克区域void setMosaic(Mat& inputMat, Rect rect); int mainFun(void) { inputImage = imread("D://test//12.jpg"); inputImage_clone = inputImage.clone(); createMosaicImage(inputImage, inputImage_mosaic, neightbourhood);  namedWindow("showImage", WINDOW_AUTOSIZE); setMouseCallback("showImage", onMouse);  waitKey(); return 0;} void createMosaicImage(Mat inputMat, Mat& outputMat, int size) { RNG rng; int height = inputMat.rows; int width = inputMat.cols; Mat padding; Mat tempMat;  //为了方便后面的计算，将输入的图像大小扩充到宽高都是size的倍数 copyMakeBorder(inputMat, padding, 0, size - inputMat.rows % size, 0, size - inputMat.cols % size, BORDER_REPLICATE); tempMat = padding.clone();  for (int row = 0; row < padding.rows; row += size) { for (int col = 0; col < padding.cols; col += size) {  int rand_x = rng.uniform(0, size);  int rand_y = rng.uniform(0, size);  Rect rect = Rect(col, row, size, size);  Mat roi = tempMat(rect);  Scalar color = Scalar(padding.at<Vec3b>(row + rand_y, col + rand_x)[0], /  padding.at<Vec3b>(row + rand_y, col + rand_x)[1], /  padding.at<Vec3b>(row + rand_y, col + rand_x)[2]);  roi.setTo(color); } } outputMat = tempMat(Rect(0, 0, width, height)).clone();} void setMosaic(Mat& inputMat, Rect rect) { Mat roi = inputMat(rect); Mat tempRoi = inputImage_mosaic(rect); tempRoi.copyTo(roi);} void onMouse(int events, int x, int y, int flag, void* ustg) {  //当鼠标移除图片区域的时候，不做操作 if (x < 0 || x > inputImage.cols || y < 0 || y > inputImage.rows) { return; }  //马赛克块的位置信息 int x_left, x_right, y_top, y_bottom; x - neightbourhood <= 0 ? x_left = 0 : x_left = x - neightbourhood; x + neightbourhood > inputImage.cols ? x_right = inputImage.cols : x_right = x + neightbourhood; y - neightbourhood <= 0 ? y_top = 0 : y_top = y - neightbourhood; y + neightbourhood > inputImage.rows ? y_bottom = inputImage.rows : y_bottom = y + neightbourhood;  if (events == CV_EVENT_LBUTTONDOWN) { mouseStatus = 1; setMosaic(inputImage_clone, Rect(x_left, y_top, x_right - x_left, y_bottom - y_top)); } else if (events == CV_EVENT_MOUSEMOVE) { if (mouseStatus == 1) {  setMosaic(inputImage_clone, Rect(x_left, y_top, x_right - x_left, y_bottom - y_top)); } else {  //nothing } } else if (events == CV_EVENT_LBUTTONUP) { mouseStatus = 0; } else { //cout << "nothing" << endl; } imshow("showImage", inputImage_clone);}  //-----开始------void COpenCVLearningDlg::OnBnClickedStartButton(){ mainFun();}

#include <core/core.hpp>#include <highgui/highgui.hpp> using namespace cv; int mainFun(){ Mat imageSource = imread("D://test//12.jpg"); Mat imageResult = imageSource.clone(); RNG rng; int randomNum; int Number = 5;  for (int i = 0; i < imageSource.rows - Number; i++) for (int j = 0; j < imageSource.cols - Number; j++) {  randomNum = rng.uniform(0, Number);  imageResult.at<Vec3b>(i, j)[0] = imageSource.at<Vec3b>(i + randomNum, j + randomNum)[0];  imageResult.at<Vec3b>(i, j)[1] = imageSource.at<Vec3b>(i + randomNum, j + randomNum)[1];  imageResult.at<Vec3b>(i, j)[2] = imageSource.at<Vec3b>(i + randomNum, j + randomNum)[2]; } imshow("毛玻璃效果", imageResult); waitKey(); return 0;}  //-----开始------void COpenCVLearningDlg::OnBnClickedStartButton(){ mainFun();}