TrainNode.h

// Base abstract class for random model nodes training
// Written by Sergey G. Kosov in 2013 for Project X
#pragma once

#include "ITrain.h"

namespace DirectGraphicalModels
{
    enum NodeRandomModel : byte { 
        Bayes = 0,              
        GMM,                    
        CvGMM,                  
        KNN,                    
        CvKNN,                  
        CvRF,                   
        MsRF,                   
        CvANN,                  
        CvSVM,                  

        GM,                     
        CvGM,                   
     };

    // ============================= Node Train Class =============================
    class CTrainNode : public ITrain
    {
    public:
        DllExport CTrainNode(byte nStates, word nFeatures)
                : CBaseRandomModel(nStates)
                , ITrain(nStates, nFeatures)
                , m_mask(nStates, 1, CV_8UC1)
        {}
        DllExport virtual ~CTrainNode(void) = default;
    
        DllExport static std::shared_ptr<CTrainNode> create(byte nodeRandomModel, byte nStates, word nFeatures);
        DllExport void          addFeatureVecs(const Mat &featureVectors, const Mat &gt);
        DllExport void          addFeatureVecs(const vec_mat_t &featureVectors, const Mat &gt);
        DllExport virtual void  addFeatureVec(const Mat &featureVector, byte gt) = 0;   
        DllExport virtual void  train(bool doClean = false) {}
        DllExport Mat           getNodePotentials(const Mat &featureVectors, const Mat &weights = Mat(), float Z = 0.0f) const;
        DllExport Mat           getNodePotentials(const vec_mat_t &featureVectors, const Mat &weights = Mat(), float Z = 0.0f) const;
        DllExport Mat           getNodePotentials(const Mat &featureVector, float weight, float Z = 0.0f) const;


    protected:
        DllExport virtual void calculateNodePotentials(const Mat &featureVector, Mat &potential, Mat &mask) const = 0;
        

    private:
        Mat m_mask;
    };
}