loadin_digit_dataset.asv

clear;
load('cifar10.mat');
% [XTrain,YTrain,~] = digitTrain4DArrayData;
% [XTest,YTest,~] = digitTest4DArrayData;

% trainData = orzReshape(squeeze(XTrain), 1);
% testData = orzReshape(squeeze(XTest), 1);
% trainLabels = YTrain;
% testLabels = YTest;

% trainData = convertkkkDatasetToMatlabSubspaceFormat(trainData, trainLabels);
% testData = convertDatasetToMatlabSubspaceFormat(testData, testLabels);
imageSize = 32;
data = reshape(trainData, imageSize, imageSize, size(trainData, 2), size(trainData, 3));
figure; % Create a new figure window
for i = 1:10 % Loop through each of the 10 classes
    % random integer, used to display random image
    idx = randi([1, 100]);
    img = squeeze(data(:,:,idx,i)); % Extract the first 16x16 image of the i-th class
    subplot(2, 5, i); % Arrange the plots in a 2x5 grid
    imagesc(img); % Display the image
    axis square; % Make each subplot square in shape
    colormap gray; % Use grayscale colors
    title(sprintf('Class %d', i)); % Title each subplot with its class number
end
% save('rotated_digits_mnist.mat', 'trainData', 'testData');