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demoRelease.m in standardmodelrelease

			
%demoRelease.m
%demonstrates how to use C2 standard model features in a pattern classification framework

addpath ~/scratch2/osusvm/ %put your own path to osusvm here

useSVM = 1; %if you do not have osusvm installed you can turn this
            %to 0, so that the classifier would be a NN classifier
	    %note: NN is not a great classifier for these features
	    
READPATCHESFROMFILE = 0; %use patches that were already computed
                         %(e.g., from natural images)

patchSizes = [4 8 12 16]; %other sizes might be better, maybe not
                          %all sizes are required
			  
numPatchSizes = length(patchSizes);

%specify directories for training and testing images
train_set.pos   = 'Image_Datasets/airTr';
train_set.neg   = 'Image_Datasets/bckgTr';
test_set.pos    = 'Image_Datasets/airTe';
test_set.neg    = 'Image_Datasets/bckgTe';

cI = readAllImages(train_set,test_set); %cI is a cell containing
                                        %all training and testing images

if isempty(cI{1}) | isempty(cI{2})
  error(['No training images were loaded -- did you remember to' ...
	' change the path names?']);
end
  
%below the c1 prototypes are extracted from the images/ read from file
if ~READPATCHESFROMFILE
  tic
  numPatchesPerSize = 250; %more will give better results, but will
                           %take more time to compute
  cPatches = extractRandC1Patches(cI{1}, numPatchSizes, ...
      numPatchesPerSize, patchSizes); %fix: extracting from positive only 
                                 			

			...
			...
			... to be continued.

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