kpfp

[~,cs] = kpfp_getchars('test7.png',false);
[feats,vec,labels] = kpfp_train();

charsN = size(cs,3);

[m,n] = size(vec);
featsT = zeros(charsN, n);
for i=1:charsN
    meanF = mean(cs, 3);
    meanF = reshape(cs(:,:,i)-meanF, m, 1);
    w = zeros(n,1);
    for ii=1:n
        w(i) = vec(:,ii)' * meanF;
    end
    featsT = w';
end

mld = ClassificationKNN.fit(featsT, labels);
yp = predict(mld, featsT);