#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
using namespace cv;
using namespace std;
static void help() {
cout << "\n\t此程序演示了OpenCV中MeanShift图像分割的使用。\n"
<< "\n\t程序运行后我们可以通过3个滑动条调节分割效果。调节滑动条后可能会有些许卡顿,请耐心"
"等待\n"
<< "\n\t3个滑动条代表的参数分别为空间窗的半径 "
"(spatialRad)、色彩窗的半径(colorRad)、最大图像金字塔级别(maxPyrLevel)\n"
<< endl;
}
static void floodFillPostprocess(Mat &img, const Scalar &colorDiff = Scalar::all(1)) {
CV_Assert(!img.empty());
RNG rng = theRNG();
Mat mask(img.rows + 2, img.cols + 2, CV_8UC1, Scalar::all(0));
for (int y = 0; y < img.rows; y++) {
for (int x = 0; x < img.cols; x++) {
if (mask.at<uchar>(y + 1, x + 1) == 0) {
Scalar newVal(rng(256), rng(256), rng(256));
floodFill(img, mask, Point(x, y), newVal, 0, colorDiff, colorDiff);
}
}
}
}
string winName = "meanshift";
int spatialRad, colorRad, maxPyrLevel;
Mat img, res;
static void meanShiftSegmentation(int, void *) {
cout << "spatialRad=" << spatialRad << "; "
<< "colorRad=" << colorRad << "; "
<< "maxPyrLevel=" << maxPyrLevel << endl;
pyrMeanShiftFiltering(img, res, spatialRad, colorRad, maxPyrLevel);
floodFillPostprocess(res, Scalar::all(2));
imshow(winName, res);
}
int main(int argc, char **argv) {
help();
img = imread("1.jpg");
if (img.empty())
return -1;
imshow("原始图", img);
spatialRad = 10;
colorRad = 10;
maxPyrLevel = 1;
namedWindow(winName, WINDOW_AUTOSIZE);
createTrackbar("spatialRad", winName, &spatialRad, 80, meanShiftSegmentation);
createTrackbar("colorRad", winName, &colorRad, 60, meanShiftSegmentation);
createTrackbar("maxPyrLevel", winName, &maxPyrLevel, 5, meanShiftSegmentation);
meanShiftSegmentation(0, 0);
waitKey();
return 0;
}