#include <opencv2/ml/ml.hpp>  
#include <iostream>  
#include <opencv2/core/core.hpp>  
#include <opencv2/highgui/highgui.hpp>  
#include <opencv2/imgproc/imgproc.hpp>  
using namespace std;  
using namespace cv;  

int main()  
{  
    float labels[10] = {0,0,0,0,0,1,1,1,1,1};  
    Mat labelsMat(10, 1, CV_32FC1, labels);  
    cout<<labelsMat<<endl;  
    float trainingData[10][2];  
   // srand(time(0));   
    for(int i=0;i<5;i++){  
        trainingData[i][0] = rand()%255+1;  
        trainingData[i][1] = rand()%255+1;  
        trainingData[i+5][0] = rand()%255+255;  
        trainingData[i+5][1] = rand()%255+255;  
    }  
    Mat trainingDataMat(10, 2, CV_32FC1, trainingData);  
    cout<<trainingDataMat<<endl;  
    CvKNearest knn;  
    knn.train(trainingDataMat,labelsMat,Mat(), false, 2 );  
    // Data for visual representation  
    int width = 512, height = 512;  
    Mat image = Mat::zeros(height, width, CV_8UC3);  
    Vec3b green(0,255,0), blue (255,0,0);  
  
    for (int i = 0; i < image.rows; ++i){  
        for (int j = 0; j < image.cols; ++j){  
            const Mat sampleMat = (Mat_<float>(1,2) << i,j);  
            Mat response;  
            float result = knn.find_nearest(sampleMat,1);  
            if (result !=0){  
                image.at<Vec3b>(j, i)  = green;  
            }  
            else    
                image.at<Vec3b>(j, i)  = blue;  
        }  
    }  
  
        // Show the training data  
        for(int i=0;i<5;i++){  
            circle( image, Point(trainingData[i][0],  trainingData[i][1]),   
                5, Scalar(  0,   0,   0), -1, 8);  
            circle( image, Point(trainingData[i+5][0],  trainingData[i+5][1]),   
                5, Scalar(255, 255, 255), -1, 8);  
        }  
        imshow("KNN Simple Example", image); // show it to the user  
        waitKey(0);  
		return 0;
  
}