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

clear all
close all
clc

imgSz=28;           % square image pixel size
N=6e4;              % Number of pictures to label

%% Reading Binary Training Images
fileOffset = 16;    % bytes of file offset
fileID = fopen('../Data/train-images.idx3-ubyte');
Xset = fread(fileID,imgSz^2*N+fileOffset,'uint8');
Xset = Xset(fileOffset+1:end);

fclose(fileID);

%% Reading Binary Training Labels
fileOffsetL = 8;    % bytes of file offset
fileIDL = fopen('../Data/train-labels.idx1-ubyte');
Xl = fread(fileIDL,N+fileOffsetL,'uint8');
Xl = Xl(fileOffsetL+1:end);

fclose(fileIDL);

%% Building 3D matrix with N images

Xmat = Vector2PictureMatrix(imgSz, N, Xset);

%% Showing images

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