Three images are displayed in output window instead of one - c++

Question

Hi everyone i tried using kmeans clustering to group the objects. So that i can use this clustering method to detect objects. I get output but the problem is its too slow{How can i solve this?? } and i get the output window is as shown in the below link. Three output images are displayed instead of one how can i solve this. I don't know where exactly the error lies.
http://tinypic.com/view.php?pic=30bd7dc&s=8#.VgkSIPmqqko
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;
int main( )
{
Mat src = imread( "Light.jpg", 0 );
// imshow("fff",src);
// cvtColor(src,src,COLOR_BGR2GRAY);
Mat dst;
// pyrDown(src,src,Size( src.cols/2, src.rows/2 ),4);
// src=dst;
resize(src,src,Size(128,128),0,0,1);
Mat samples(src.rows * src.cols, 3, CV_32F);
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
// for( int z = 0; z < 3; z++)
samples.at<float>(y + x*src.rows) = src.at<uchar>(y,x);
cout<<"aaa"<<endl;
int clusterCount = 15;
Mat labels;
int attempts = 2;
Mat centers;
cout<<"aaa"<<endl;
kmeans(samples, clusterCount, labels, TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10000, 0.0001), attempts, KMEANS_PP_CENTERS, centers );
Mat new_image( src.size(), src.type() );
cout<<"aaa"<<endl;
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
{
int cluster_idx = labels.at<int>(y + x*src.rows,0);
new_image.at<uchar>(y,x) = centers.at<float>(cluster_idx,0);
//new_image.at<Vec3b>(y,x)[1] = centers.at<float>(cluster_idx, 1);
// new_image.at<Vec3b>(y,x)[2] = centers.at<float>(cluster_idx, 2);
}
imshow( "clustered image", new_image );
waitKey( 0 );
}

Answer 1

In your initial code you have to change the intermedia Mat sample from 3 channels to 1 channel if you use grayscale images.
In addition, if you change the memory ordering, it might be faster (changed to (y*src.cols + x, 0) in both places):
int main( )
{
clock_t start = clock();
Mat src = imread( "Light.jpg", 0 );
Mat dst;
resize(src,src,Size(128,128),0,0,1);
Mat samples(src.rows * src.cols, 1, CV_32F);
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
samples.at<float>(y*src.cols + x, 0) = src.at<uchar>(y,x);
int clusterCount = 15;
Mat labels;
int attempts = 2;
Mat centers;
kmeans(samples, clusterCount, labels, TermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 10000, 0.0001), attempts, KMEANS_PP_CENTERS, centers );
Mat new_image( src.size(), src.type() );
for( int y = 0; y < src.rows; y++ )
for( int x = 0; x < src.cols; x++ )
{
int cluster_idx = labels.at<int>(y*src.cols + x,0);
new_image.at<uchar>(y,x) = centers.at<float>(cluster_idx,0);
}
imshow( "clustered image", new_image );
clock_t end = clock();
std::cout << "time: " << (end - start)/(float)CLOCKS_PER_SEC << std::endl;
waitKey( 0 );
}