Direct Graphical Models  v.1.7.0
TrainEdgePottsCS.h
1 // Contrast-Sensitive Potts training model for pairwise potentials
2 // Written by Sergey G. Kosov in 2015 for Project X
3 #pragma once
4 
5 #include "TrainEdgePotts.h"
6 
7 namespace DirectGraphicalModels
8 {
22  };
23 
24 
25  // ============================= Contrast-Sensitive Potts Train Class =============================
36  {
37  public:
44  DllExport CTrainEdgePottsCS(byte nStates, word nFeatures, ePotPenalApproach penApproach = eP_APP_PEN_EXP)
45  : CBaseRandomModel(nStates)
46  , CTrainEdgePotts(nStates, nFeatures)
47  , m_penApproach(penApproach)
48  {}
49  DllExport virtual ~CTrainEdgePottsCS(void) {}
50 
51 
52  protected:
68  DllExport virtual Mat calculateEdgePotentials(const Mat &featureVector1, const Mat &featureVector2, const vec_float_t &vParams) const;
69 
70 
71  private:
73  };
74 }
Charbonnier penalization approach.
CTrainEdgePottsCS(byte nStates, word nFeatures, ePotPenalApproach penApproach=eP_APP_PEN_EXP)
Constructor.
Contrast-Sensitive Potts training class.
Base abstract class for random model training.
Potts edge training class.
Perrona-Malik penalization approach.
ePotPenalApproach
Penalization approach flag.
Exponential penalization approach.
virtual Mat calculateEdgePotentials(const Mat &featureVector1, const Mat &featureVector2, const vec_float_t &vParams) const
Returns the contrast-sensitive edge potentials.