Beispiel #1
0
    void generate_random_clusters( const std::vector<sample_type>& samples)
    {
        typedef boost::variate_generator<boost::mt19937&, boost::uniform_int<> > random_type;
        random_type random_( random_generator_, boost::uniform_int<>(0, samples.size() - 1));

        for( int i = 0; i < K_; ++i)
        {
            while( 1)
            {
                int indx = random_();

                if( labels_[indx] == 0)
                {
                    clusters_.push_back( cluster_t( samples[indx]));
                    labels_[indx] = &(clusters_.back());
                    break;
                }
            }
        }
    }
Beispiel #2
0
    void clusterHistograms(const std::vector<Mat> &hists, std::vector<cluster_t> &clusters, const cluster_vars &vars) {

        // calculate hist distances
        Mat dists = Mat::zeros((int)hists.size(), (int)hists.size(), CV_64FC1);
        tbb::parallel_for(0, (int)hists.size()-1, 1, 
            [&hists, &dists](int i) {
                tbb::parallel_for(i, (int)hists.size(), 1, 
                    [&hists, &dists, &i](int j) {
                        double dist = compareHist(hists.at(i), hists.at(j), COMP_ALG);
                        dists.at<double>(i, j) = dist;
                        dists.at<double>(j, i) = dist;
                    } 
                );
            } 
        );
        
        // find optimal clusters
        std::vector<idx_cluster_t> idxClusters;
        find_optimal_clustering(dists, idxClusters, vars);

        // calculate the cluster average for each cluster
        for(size_t i = 0; i < idxClusters.size(); i++) {
            idx_cluster_t cluster = idxClusters.at((int)i);
            
            std::vector<Mat> clusterHists;
            Mat clusterAvg;
            
            for(size_t i = 0; i < cluster.size(); i++) {
            //for(idx_cluster_t::const_iterator it = cluster.begin(); it != cluster.end(); it++) {
                clusterHists.push_back(hists.at(cluster.at(i)));
            }
            
            averageHistograms(clusterHists, clusterAvg);

            clusters.push_back(cluster_t(clusterAvg, cluster));
        }
    }