rtsEnviClassify.m
876 Bytes
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
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);