rtsEnviClassify.m 914 Bytes
function C = rtsEnviClassify(B, envi_filename, mask, nFeatures)

%   B = TreeBagger class
%   nFeatures = number of features cropped out (0 means use all features)

if nargin < 4
    nFeatures = 0;
end


batchSize = 100000;



Ns = nnz(mask)    %get the number of samples to be classified
Nb = ceil(Ns / batchSize);  %get the number of batches

C(Ns, 1) = char(0);

%open the ENVI file
envi = rtsEnviOpen(envi_filename, [envi_filename '.hdr'], mask);

for b = 1:Nb
    
    %load a batch
    batch = rtsEnviRead(envi, batchSize);
    
    %crop out the number of features specified (if it is specified)
    if nFeatures ~= 0
        batch = batch(1:nFeatures, :);
    end
    
    %classify the batch
    C( (b-1)*batchSize + 1 : (b-1)*batchSize + size(batch, 2) ) = cell2mat(predict(B, batch'));
    
    disp([num2str( round( b / Nb * 100 ) ) '%']);
end

rtsEnviClose(envi);