% DEI Practical assignment 2018/19
% Objective: 3D HCI Gesture learning

%% Acquisition
function sol = funcion(nombre,et)
%     load(nombre); % Load dataset
%
%     figure;imagesc(scan3d.img(:,:,:,1)); %Show images
%
%     scan3dmano = scan3d;
%
%      for i = 1:scan3d.numImages
%         maskAuxColor = createMaskColor(scan3dmano.img(:,:,:,i),100,250,50,200,50,200);
%
%         % Depth direct
%         maskAux = createMaskDepth(scan3dmano.depth(:,:,i),800);
%
%         % Colour + Depth
%         maskC=maskAux & maskAuxColor;
%         N = medfilt2(maskC);
%
%         s = regionprops(N,'Area','Centroid');
%         centro = [0,0];
%          for j = 1:size(s)
%              if s(j).Area==max([s.Area])
%                  centro = s(j).Centroid;
%              end
%          end
%
%         imshow(N)
%
%         m{i,1} = centro(1);
%         m{i,2} = centro(2);
%         m{i,3} = et;
%
%      end
    fid = fopen(nombre);
    data = textscan(fid,'%f%f%f%f','HeaderLines',0,'CollectOutput',1);
    data = data{:};
    fid = fclose(fid);
    data(:,1);

    j=1;
    k=1;
    coord = [0 0 0];
    prof = [0 0 0 0];
    for i = 3:size(data)
        if data(i,1) == 40

        else
           if mod(i,2) == 1
              coord(j,1) = data(i,1);
              coord(j,2) = data(i,2);
              coord(j,3) = data(i,3);
              j = j + 1;
           else
            prof(k,1) = data(i,1);
            prof(k,2) = data(i,2);
            prof(k,3) = data(i,3);
            prof(k,4) = et;
            k = k + 1;
           end;

        end;

    end;

    total = [coord prof];
     sol=total;
end