source: foam/trunk/vision/src/Classifier.cpp @ 94

Revision 94, 1.7 KB checked in by dave, 10 years ago (diff)

added face classifier application, not working yet

Line 
1// Copyright (C) 2009 foam
2//
3// This program is free software; you can redistribute it and/or modify
4// it under the terms of the GNU General Public License as published by
5// the Free Software Foundation; either version 2 of the License, or
6// (at your option) any later version.
7//
8// This program is distributed in the hope that it will be useful,
9// but WITHOUT ANY WARRANTY; without even the implied warranty of
10// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
11// GNU General Public License for more details.
12//
13// You should have received a copy of the GNU General Public License
14// along with this program; if not, write to the Free Software
15// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
16
17#include "Classifier.h"
18
19using namespace std;
20
21Classifier::Classifier(unsigned int FeatureSize) :
22m_FeatureSize(FeatureSize),
23m_Mean(FeatureSize)
24{
25}
26
27Classifier::~Classifier()
28{
29}
30
31void Classifier::AddFeatureToGroup(int group, const Vector<float> &v)
32{
33        assert(v.Size()==m_FeatureSize);
34        m_Features[group].push_back(v);
35        // possibly overkill to do this each time we add a new feature...
36        CalcGroupMeans();
37}
38
39void Classifier::CalcMean()
40{
41        m_Mean.Zero();
42       
43        for (FeatureMap::iterator i=m_Features.begin();
44                i!=m_Features.end(); ++i)
45        {
46                for (FeatureVec::iterator vi = i->second.begin(); vi!=i->second.end(); ++vi)
47                {
48                        m_Mean+=*vi;
49                }
50        }
51       
52        m_Mean/=m_FeatureSize;
53}
54
55void Classifier::CalcGroupMeans()
56{
57        for (FeatureMap::iterator i=m_Features.begin();
58                i!=m_Features.end(); ++i)
59        {
60                Vector<float> mean;
61                for (FeatureVec::iterator vi = i->second.begin(); vi!=i->second.end(); ++vi)
62                {
63                        mean+=*vi;
64                }
65                mean/=i->second.size();
66                m_GroupMeans[i->first]=mean;
67        }
68}
69
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