Nearest-Neighbour-Search-Neural-Networks-Product-Quantization/MNIST/Functions/ReadingPicSetLabSet.m

%% Reading Pictures and Labels Sets
%  The function reads Pictures and Labels related to the pictures
%  from binary files in uint8 (unsigned int 8bits) format.
%  It provides also the possibility to Display the read pictures
%  in ordered arrangement, one for each diferent Label.
%
%  Inputs:
% - imgSz           Size of the single squared picture
% - N               Total Number of pictures
% - fileOffsetPic   Offset for files containing pictures
% - fileNamePic     Name of the binary file containing pictures
% - fileOffsetLab   Offset for files containing labels
% - fileNameLab     Name of the binary file containing labels
% - Display         Flag for the visualization of the read pictures
%
%  Outputs:
% - XSet            Vector containing the acquired pictures
% - XLab            Vector containing the acquired labels
%
%  Dependencies:
% - Xmat = Vector2Matrix(imgSz, N, XSet);
%
%%

function [XSet, XLab]=ReadingPicSetLabSet(imgSz, N, fileOffsetPic, fileNamePic, fileOffsetLab, fileNameLab, Display)

% Reading Binary Training Images
fileIDPic = fopen(fileNamePic);
XSet = fread(fileIDPic,imgSz^2*N+fileOffsetPic,'uint8');
%XSet = uint8(XSet(fileOffsetPic+1:end));
XSet = XSet(fileOffsetPic+1:end);
fclose(fileIDPic);

% Reading Binary Training Labels
fileIDLab = fopen(fileNameLab);
XLab = fread(fileIDLab,N+fileOffsetLab,'uint8');
%XLab = uint8(XLab(fileOffsetLab+1:end));
XLab = XLab(fileOffsetLab+1:end);
fclose(fileIDLab);

if(Display)
    % Building 3D matrix with N images
    Xmat = Vector2PictureMatrix(imgSz, N, XSet);

    % Showing images
    figure()
    suptitle('Ordered chosen pictures from the Training Data Set')
    for kk=1:10
        subplot(2, 5, kk)
        ind=find(XLab==kk-1,1,'first');
        imshow(255-Xmat(:,:,ind),[0 255])
        xlabel(int2str(XLab(ind)));
    end
end

end