void k_means(){


	Mat_<uchar> dt = imread("./Images/points3.bmp", CV_LOAD_IMAGE_GRAYSCALE);
	Mat img(dt.rows, dt.cols, CV_8UC3, Scalar(255, 255,255));
	std::uniform_int_distribution<int> dis_colors(0, 255);

	const int K = 3;
	int x, y;
	Point2i a;
	vector<Point2i> vec;
	vector<Point2i> centre;

	Vec3b colors[K];
	std::uniform_int_distribution<int> dist_colors(0, 255);
	for (int i = 0; i < K; i++)
		colors[i] = Vec3b(dist_colors(gen), dist_colors(gen), dist_colors(gen));

	for (int i = 0; i < img.rows; i++)
		for (int j = 0; j < img.cols; j++)
			if (dt(i, j) == 0)
				vec.push_back(Point2i(j, i));

	std::uniform_int_distribution<int> dist(0, vec.size());
	for (int i = 0; i < K; i++){
		int idx = dist(gen);
		centre.push_back(vec.at(idx));
	}


	int minx = 100000000, miny = 10000000, minsum = 10000, ab = 0;
	int vx[K], vy[K], vsum[K];

	bool update = true;
	int nrIt = 0;
	while (update){
		for (int i = 0; i < img.rows; i++)
			for (int j = 0; j < img.cols; j++)
				img.at<Vec3b>(i, j) = Vec3b(255,255,255);

		update = false;
		for (int i = 0; i < K; i++)
		{
			vx[i] = 0;
			vy[i] = 0;
			vsum[i] = 0;
		}
		for (int i = 0; i < vec.size(); i++) {
			Point2i crt = vec.at(i);
			int k = 0;
			minsum = 10000000;
			for (Point2i p : centre)
			{

				ab = abs((p.x - crt.x)*(p.x - crt.x) - (p.y - crt.y)*(p.y - crt.y));
				if (minsum > ab)
				{
					minsum = ab;
					img.at<Vec3b>(crt.y, crt.x) = colors[k];

					vx[k] += crt.x;
					vy[k] += crt.y;
					vsum[k]++;
				}
				k++;
			}
		}
		int k = 0;
		for (Point2i &p : centre){
			int help = round(vx[k] / vsum[k]);
			if (p.x != help){
				p.x = help;
				update = true;
			}
			help = round(vy[k] / vsum[k]);
			if (p.y != help){
				p.y = help;
				update = true;
			}
			circle(img, p, 3, Scalar(colors[k]), 3);
			k++;
		}


		imshow("Dest", img);
		waitKey(0);

	}
	imshow("Dest", img);
	waitKey(0);
}