OpenCV： Kmeans的使用一维和二维点集

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mb5ff40c7a158f2 2017-08-19 23:28:00

OpenCVKmeans算法默认使用了Kmeans++选取种子点

//效果：根据半径聚类，并不一定能得到好的结果。
float CBlotGlint::ClusterByR(  )
{
  //根据半径大小聚类，找出合适的类别个数和每一类的个数
  std::vector<float>   radiuses(this->blobs.size() );
  std::vector<std::pair<float,int> >   radiusesIdx(this->blobs.size() );
  for ( int i=0; i< this->blobs.size(); ++i ){
    radiuses[i] =this->blobs[i].diaGlint;
    radiusesIdx[i].first  = radiuses[i];
    radiusesIdx[i].second = i;
  }

  {
    using namespace cv;

    this->blobs[0].diaGlint;

    const int MAX_CLUSTERS = 5;
    Scalar colorTab[] =
    {
      Scalar(0, 0, 255),
      Scalar(0,255,0),
      Scalar(255,100,100),
      Scalar(255,0,255),
      Scalar(0,255,255)
    };

    Mat img( 500, 500, CV_8UC3 );
    RNG rng( 12345 );
    std::vector<std::vector<float> >  outC;
    std::vector<std::vector<std::pair<float,int> > >  outCidx;

    {
      outC.clear();
      int k;
      int clusterCount = rng.uniform(2, MAX_CLUSTERS+1);
      int i;
      int sampleCount =radiuses.size();// rng.uniform(1, 1001);
      Mat points(sampleCount, 1, CV_32FC1), labels;
      for ( int i=0; i< sampleCount; ++i ){
        points.at<float>(i) = radiuses[i];
      }

      clusterCount = MIN(clusterCount, sampleCount);
      clusterCount = std::max(clusterCount,3);
      clusterCount = 3;

      Mat centers;
      kmeans(points, clusterCount, labels,
        TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, 1.0),
        3, KMEANS_PP_CENTERS, centers);

      outC.resize( clusterCount );
      outCidx.resize( clusterCount );

      img = Scalar::all(0);
      for( i = 0; i < sampleCount; i++ )
      {
        int clusterIdx = labels.at<int>( i );
        outC[clusterIdx].push_back( points.at<float>( i  ) );
        outCidx[clusterIdx].push_back( 
          std::make_pair ( points.at<float>( i  ) ,radiusesIdx[i].second ) );

        Point ipt = this->blobs[i].centerOfGlint;
        circle( img, ipt, 2, colorTab[clusterIdx], CV_FILLED, CV_AA );
      }

      cv::imshow("clusters", img);

      char key = (char)cv::waitKey(1);
    }

    return 0;

  }

  return 1.0;
}