clc;

clear;

close all;







path    = 'img/test/';

images = dir(strcat(path, '*.jpg'));

count   = length(images);




GrayscaleMatris = ReadMatrix('GrayscaleMatris.txt');

HSMatris        = ReadMatrix('HSMatris.txt');

HSVMatris       = ReadMatrix('HSVMatris.txt');

RGBMatris       = ReadMatrix('RGBMatris.txt');




for i = 1 : count

    HSMatris(i, 4) = ( HSMatris(i, 4) / 2 ) * 255;

    

    HSVMatris(i, 5) = ( HSVMatris(i, 5) / 3 ) * 255;

    

    RGBMatris(i, 5) = RGBMatris(i, 5) / 3;

end




result = zeros(count, 10);




train_names = trainData();

train_size = size(train_names);

train_size = train_size(2);




figure;

for i = 1 : count

    image_file          = images(i).name;

    image               = imread(strcat(path, image_file));

    

    voteMatris = zeros(train_size + 1, 1);

    

    min_distance = min( min( GrayscaleMatris(i, 3), RGBMatris(i, 5) ), min( HSMatris(i, 4), HSVMatris(i, 5) ) );

    

    result(i, 1) = GrayscaleMatris(i, 3);

    result(i, 2) = RGBMatris(i, 5);

    result(i, 3) = HSMatris(i, 4);

    result(i, 4) = HSVMatris(i, 5);

    

    result(i, 6) = min_distance;

    

    if(min_distance == GrayscaleMatris(i, 3))

        result(i, 7) = GrayscaleMatris(i, 2);

        result(i, 8) = 1;

    end

    if(min_distance == RGBMatris(i, 5))

        result(i, 7) = RGBMatris(i, 4);  

        result(i, 8) = 2;

    end

    if(min_distance == HSMatris(i, 4))

        result(i, 7) = HSMatris(i, 3);

        result(i, 8) = 3;

    end

    if(min_distance == HSVMatris(i, 5))        

        result(i, 7) = HSVMatris(i, 4);

        result(i, 8) = 4;

    end

    

    voteMatris( GrayscaleMatris(i, 2) + 1, 1 )  = voteMatris( GrayscaleMatris(i, 2) + 1, 1 ) + 1;

    voteMatris( RGBMatris(i, 4) + 1, 1 )        = voteMatris( RGBMatris(i, 4) + 1, 1 ) + 1;

    voteMatris( HSMatris(i, 3) + 1, 1 )         = voteMatris( HSMatris(i, 3) + 1, 1 ) + 1;

    voteMatris( HSVMatris(i, 4) + 1, 1 )        = voteMatris( HSVMatris(i, 4) + 1, 1 ) + 1;

    voteMatris( result(i, 7) + 1, 1 )           = voteMatris( result(i, 7) + 1, 1 ) + 1;

    

    maxVote = max(voteMatris);

    

    result(i, 5) = NaN;

    result(i, 9) = NaN;

    

    if(maxVote > 1)

        for j = 1 : train_size() + 1

            if(voteMatris(j) == maxVote)

               break; 

            end

        end

        

        if(j == 1)

            result(i, 10) = 0;

        else

            result(i, 10) = j - 1;

        end

    else

        result(i, 10) = result(i, 7);

    end

    

    subplot(round(count / 4), round(count / 4),i),imshow(image);

    

    if(result(i, 10) == 0)

        title('no money');

    else

        title(train_names(result(i, 10)));

    end

end




SaveMatrix(result, 'mainResultMatris.txt');

done = 1