#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>

using namespace cv;


void convert(const Mat img, Mat& lab){
    Mat imgf;
    img.convertTo(imgf, CV_32FC3, 1/255.0); //tipus converzio rgb 0-1 tartomany
    cvtColor(imgf, lab, COLOR_BGR2Lab);

}

double avg_diff(const Mat lab1, const Mat lab2){
    Mat diff = lab1 - lab2;
    Mat diff2 = diff.mul(diff); //1 kep 3 csatornara: dL^2 dA^2 dB^2 ezeket kellene osszeadni
    std::vector<Mat> chs;
    split(diff2, chs); //3 kep 1 csatorna

    Mat E;
    cv::sqrt(chs[0] + chs[1] + chs[2], E);

    return mean(E)[0]; //mivel osszeadtuk a skalarbol kivesszuk az elso erteket mert csak az a lenyeg
}

std::string get_category(double diff){}

int main(){
    Mat etalon = imread("padlolapok/etalon.png", IMREAD_COLOR);
    Mat elab;

    convert(etalon, elab);
    imshow("img", etalon);
    moveWindow("img", 0,0);


    /*Vec3f c1 = lab.at<Vec3f>(0,0);
    Vec3f c2 = lab.at<Vec3f>(0,1);

    std::cout<< c1 << " " << c2 << std::endl;
    std::cout << "tavolsag: " << norm(c2-c1) << std::endl;

    Vec3f c3 = lab.at<Vec3f>(lab.rows-1, lab.cols-1);
    std::cout<< "tavolsag: " << norm(c3-c1) << std::endl;*/
    
    for(int i = 1; i < 7; i++){
        Mat img = imread("padlolapok/fa_" + std::to_string(i) + ".png", IMREAD_COLOR);
        Mat lab;

        convert(img, lab);
        std::string name = "img" + std::to_string(i);
        imshow(name, img);

        moveWindow(name, 400, i*(img.rows+30));

        std::cout << i << " " << avg_diff(elab, lab) << std::endl; 
    }

    
    waitKey();
    return 0;
}