📄 usps2mat.m
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% USPS2MAT converts USPS database to Matlab data file (MAT).%% Description: % It creates MAT-file containing training and testing part% of the USPS database of handwritten numerals.%% Input: % It requires input text files "zip.test" and "zip.train"% which can be downloaded from:%% http://www-stat-class.stanford.edu/~tibs/ElemStatLearn/datasets/zip.train.gz% http://www-stat-class.stanford.edu/~tibs/ElemStatLearn/datasets/zip.test.gz% % Output:% The output MAT-file "usps.mat" contains: % trn.X [256 x 7291] Images of training numerals stored as columns.% trn.y [1 x 7291] Labels y==1 -->"1", ..., y==9-->"9",... y==10-->"0".%% tst.X [256 x 2007] Images of testing numerals stored as columns.% tst.y [1 x 2007] Labels.%% Example:% The following code displays the first training image.% load usps.mat;% img = reshape(trn.X(:,1),16,16);% figure; % imshow(img,[]);% % About: Statistical Pattern Recognition Toolbox% (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac% <a href="http://www.cvut.cz">Czech Technical University Prague</a>% <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a>% <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a>% Modifications:% 07-jun-2004, VF% 10-mar-2004, VFtrn_data = load('zip.train','-ascii');tst_data = load('zip.test','-ascii');% processing training datatrn.y = trn_data(:,1);trn.y(find(trn.y==0)) = 10;tmp = trn_data(:,2:end)';trn.X = zeros(256, size(tmp,2));fprintf('Processing training data');for i=1:size(tmp,2), fprintf('.'); dummy = reshape( tmp(:,i), 16, 16 )'; trn.X(:,i) = (dummy(:)+1)/2;endfprintf('\n'); % processing testing datatst.y = tst_data(:,1);tst.y(find(tst.y==0)) = 10;tmp = tst_data(:,2:end)';tst.X = zeros(256, size(tmp,2));fprintf('Processing testing data');for i=1:size(tmp,2), fprintf('.'); dummy = reshape( tmp(:,i), 16, 16 )'; tst.X(:,i) = (dummy(:)+1)/2;endfprintf('\n');% name = 'USPS database of handwritten numerals';save usps trn tst name;% EOF
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