写一个基于opencv c++的聚类算法

以下是一个基于OpenCV C++的聚类算法示例，使用K-means算法实现：

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
#include <vector>

using namespace cv;
using namespace std;

int main()
{
    Mat image = imread("example.jpg", IMREAD_COLOR);
    if (image.empty())
    {
        cout << "Could not open or find the image" << endl;
        return -1;
    }

    Mat reshaped_image = image.reshape(1, image.rows * image.cols);
    reshaped_image.convertTo(reshaped_image, CV_32F);

    int K = 6; // number of clusters
    TermCriteria criteria(TermCriteria::EPS + TermCriteria::COUNT, 10, 1.0);
    int attempts = 5;
    Mat labels, centers;
    kmeans(reshaped_image, K, labels, criteria, attempts, KMEANS_RANDOM_CENTERS, centers);

    vector<Mat> clusters(K);
    for (int i = 0; i < K; i++)
    {
        clusters[i] = Mat::zeros(image.rows, image.cols, CV_8UC3);
    }

    MatIterator_<Vec3b> it, end;
    int i = 0;
    for (it = image.begin<Vec3b>(), end = image.end<Vec3b>(); it != end; ++it, ++i)
    {
        int cluster_idx = labels.at<int>(i);
        clusters[cluster_idx].at<Vec3b>(i) = *it;
    }

    for (int i = 0; i < K; i++)
    {
        imshow("Cluster " + to_string(i), clusters[i]);
    }

    waitKey(0);
    return 0;
}

该示例读取一张图像，将其重塑为行向量，然后使用K-means算法将其聚类为给定数量的簇。最终，每个簇都被分配到一个颜色，并显示在单独的窗口中。