//g++ -Wall -Wextra -pedantic -ansi -march=native -mtune=native `pkg-config --cflags --libs opencv` -o test_KMeans test_KMeans.cpp

#include <cstdlib>

#include <iostream>

#include "opencv2/highgui/highgui.hpp"

#include "opencv2/calib3d/calib3d.hpp"

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/features2d/features2d.hpp"

#if CV_MAJOR_VERSION*100+CV_MINOR_VERSION*10+CV_SUBMINOR_VERSION > 233

#include "opencv2/nonfree/nonfree.hpp"

#endif

int

main(int argc, char* argv[])

{

#if CV_MAJOR_VERSION*100+CV_MINOR_VERSION*10+CV_SUBMINOR_VERSION > 233

  cv::initModule_nonfree();

#endif

  if (argc != 2) {

    std::cerr<<"Usage"<<argv[0]<<" imageFilename\n";

    exit(EXIT_FAILURE);

  }

  const char *imageFilename = argv[1];

  cv::Mat img = cv::imread(imageFilename);

  if (img.empty()) {

    std::cerr<<"Error: unable to load imageFilename: "<<imageFilename<<"\n";

    exit(EXIT_FAILURE);

  }

  cv::Ptr<cv::FeatureDetector> detector = new cv::DenseFeatureDetector();

  cv::Ptr<cv::DescriptorExtractor> descriptorExtractor = new cv::SiftDescriptorExtractor(); //cv::DescriptorExtractor::create("SIFT");

  std::vector<cv::KeyPoint> keypoints;

  detector->detect(img, keypoints );

  cv::Mat descriptors;

  descriptorExtractor->compute(img, keypoints, descriptors);

  const int cluster_count = keypoints.size() * 0.01; 

  std::cerr<<"kmeans of "<<descriptors.rows<<" descriptors of size "<<descriptors.cols<<": ";

  cv::Mat labels(descriptors.rows, 1, CV_32S);

  cv::Mat centers(descriptors.rows, descriptors.rows, CV_32F); //B: do we have to allocate it ???????

  const int attempts = 3;

  double t = (double)cv::getTickCount();

  cv::kmeans(descriptors, cluster_count, labels, cv::TermCriteria(), attempts, cv::KMEANS_PP_CENTERS, centers);

  t = ((double)cv::getTickCount() -t )/cv::getTickFrequency();

  std::cerr<<t<<"s\n";

  return 0;

}