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70 lines
1.7 KiB
Matlab
70 lines
1.7 KiB
Matlab
function test_ism_usps(imageNum,threshold)
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if nargin<1 || isempty(imageNum) || imageNum<0
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imageNum=1;
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end
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if nargin<2 || isempty(threshold) || threshold<0
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threshold=1
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end
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spread=2
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method{1}='Hough';method{2}='PC/BC-DIM';
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%DEFINE CODEBOOK
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load('ISM_codebook_USPS.mat');
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Locations=postprocess_codebook(Locations,patchClassList,spread);
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%DEFINE TEST IMAGE
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[images,classes,trainingIndeces,testingIndeces,numClasses]=load_data_usps;
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I=preprocess_usps_image(images(imageNum,:));
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figured(2),clf, imagesc(I), hold on, axis('equal','tight'); title(' ');
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set(gca,'FontSize',24);
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%set(gca,'XTick',[],'YTick',[]);
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set(gcf,'PaperSize',[20 15],'PaperPosition',[0 0 20 15]);
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colormap('gray');
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drawnow;
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%APPLY METHODS
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[param{1},param{2}]=ism_compare_methods(I,patches,patchClassList,Locations,similarityThres);
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class=classes(imageNum)
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for m=1:length(method)
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disp(method{m});
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%analyse results as a detection tasks
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coords=[];class=[];amplitude=[];
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for c=1:numClasses
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index=find(param{m}{c}(3,:)>threshold);
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class=[class,c.*ones(1,length(index))];
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coords=[coords,param{m}{c}(1:2,index)];
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amplitude=[amplitude,param{m}{c}(3,index)];
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end
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%num_per_class(coords)
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[~,order]=sort(amplitude,'descend');
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disp(' * class:');
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disp(class(order));
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disp(' * centre coords:');
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disp(coords(:,order));
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disp(' * amplitude:');
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disp(amplitude(order));
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%analyse results as a classification task
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prob=zeros(1,numClasses);
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for c=1:numClasses
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maxAmplitude=max(param{m}{c}(3,:));
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if ~isempty(maxAmplitude)
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prob(c)=maxAmplitude;
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end
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end
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[~,predictedClass]=max(prob)
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end
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function num=num_per_class(param)
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numClasses=length(param);
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num=zeros(1,numClasses);
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for c=1:numClasses
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num(c)=size(param{c},2);
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end
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