rcnn_features.m 1.45 KB
Newer Older
Ross Girshick's avatar
Ross Girshick committed
1
function feat = rcnn_features(im, boxes, rcnn_model)
Ross Girshick's avatar
Ross Girshick committed
2
3
4
5
6
7
8
9
10
% AUTORIGHTS
% ---------------------------------------------------------
% Copyright (c) 2014, Ross Girshick
% 
% This file is part of the R-CNN code and is available 
% under the terms of the Simplified BSD License provided in 
% LICENSE. Please retain this notice and LICENSE if you use 
% this file (or any portion of it) in your project.
% ---------------------------------------------------------
Ross Girshick's avatar
Ross Girshick committed
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
40
41
42
43
44
45
46
47
48
49

% make sure that caffe has been initialized for this model
if rcnn_model.cnn.init_key ~= caffe('get_init_key')
  error('You probably need to call rcnn_load_model');
end

% Each batch contains 256 (default) image regions.
% Processing more than this many at once takes too much memory
% for a typical high-end GPU.
[batches, batch_padding] = rcnn_extract_regions(im, boxes, rcnn_model);
batch_size = rcnn_model.cnn.batch_size;

% compute features for each batch of region images
feat_dim = -1;
feat = [];
curr = 1;
for j = 1:length(batches)
  % forward propagate batch of region images 
  f = caffe('forward', batches(j));
  f = f{1};
  
  % first batch, init feat_dim and feat
  if j == 1
    feat_dim = length(f)/batch_size;
    feat = zeros(size(boxes, 1), feat_dim, 'single');
  end

  f = reshape(f, [feat_dim batch_size]);

  % last batch, trim f to size
  if j == length(batches)
    if batch_padding > 0
      f = f(:, 1:end-batch_padding);
    end
  end

  feat(curr:curr+size(f,2)-1,:) = f';
  curr = curr + batch_size;
end