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continuing refactoring ml samples; added "max vote" response to ANN_MLP. Probably, should make it in less hacky way

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This commit is contained in:
Vadim Pisarevsky
2014-07-31 14:12:10 +04:00
parent 223cdcd0ee
commit 10b60f8d16
3 changed files with 281 additions and 361 deletions
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25
modules/ml/src/ann_mlp.cpp
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@@ -228,9 +228,8 @@ public:
int n = inputs.rows, dn0 = n;
CV_Assert( (type == CV_32F || type == CV_64F) && inputs.cols == layer_sizes[0] );
_outputs.create(n, layer_sizes[l_count-1], type);
Mat outputs = _outputs.getMat();
int noutputs = layer_sizes[l_count-1];
Mat outputs;
int min_buf_sz = 2*max_lsize;
int buf_sz = n*min_buf_sz;
@@ -242,9 +241,20 @@ public:
buf_sz = dn0*min_buf_sz;
}
cv::AutoBuffer<double> _buf(buf_sz);
cv::AutoBuffer<double> _buf(buf_sz+noutputs);
double* buf = _buf;
if( !_outputs.needed() )
{
CV_Assert( n == 1 );
outputs = Mat(n, noutputs, type, buf + buf_sz);
}
else
{
_outputs.create(n, noutputs, type);
outputs = _outputs.getMat();
}
int dn = 0;
for( int i = 0; i < n; i += dn )
{
@@ -273,6 +283,13 @@ public:
scale_output( layer_in, layer_out );
}
if( n == 1 )
{
int maxIdx[] = {0, 0};
minMaxIdx(outputs, 0, 0, 0, maxIdx);
return maxIdx[0] + maxIdx[1];
}
return 0.f;
}