TrainNodeCvSVM.h

// Support Vector Machines (based on OpenCV) training class interface
// Written by Sergey G. Kosov in 2017 for Project X
#pragma once

#include "TrainNode.h"

namespace DirectGraphicalModels
{
    class CSamplesAccumulator;

    typedef struct TrainNodeCvSVMParams {
        double  C;                          
        int     maxCount;                   
        double  epsilon;                    
        int     term_criteria_type;         
        size_t  maxSamples;                 

        TrainNodeCvSVMParams() {}
        TrainNodeCvSVMParams(double C, int maxCount, double epsilon, int term_criteria_type, int maxSamples) : C(C), maxCount(maxCount), epsilon(epsilon), term_criteria_type(term_criteria_type), maxSamples(maxSamples) {}
    } TrainNodeCvSVMParams;

    const TrainNodeCvSVMParams TRAIN_NODE_CV_SVM_PARAMS_DEFAULT =   TrainNodeCvSVMParams(
                                                                    0.4,    // Parameter C of a SVM optimization problem
                                                                    10000,  // The maximum number of iterations (time / accuracy)
                                                                    0.01,   // The desired accuracy or change in parameters at which the iterative algorithm stops 
                                                                    TermCriteria::MAX_ITER | TermCriteria::EPS, // Termination cirteria (according the the two previous parameters)
                                                                    0       // Maximum number of samples to be used in training. 0 means using all the samples
                                                                    );

    // ====================== OpenCV Support Vector Machines Train Class =====================
    class CTrainNodeCvSVM : public CTrainNode {
    public:
        DllExport CTrainNodeCvSVM(byte nStates, word nFeatures, TrainNodeCvSVMParams params = TRAIN_NODE_CV_SVM_PARAMS_DEFAULT);
        DllExport CTrainNodeCvSVM(byte nStates, word nFeatures, size_t maxSamples);
        DllExport virtual ~CTrainNodeCvSVM(void);

        DllExport void  reset(void);
        DllExport void  save(const std::string &path, const std::string &name = std::string(), short idx = -1) const;
        DllExport void  load(const std::string &path, const std::string &name = std::string(), short idx = -1);

        DllExport void  addFeatureVec(const Mat &featureVector, byte gt);

        DllExport void  train(bool doClean = false);


    protected:
        DllExport void  saveFile(FILE *pFile) const { }
        DllExport void  loadFile(FILE *pFile) { }
        DllExport void  calculateNodePotentials(const Mat &featureVector, Mat &potential, Mat &mask) const;


    private:
        void          init(TrainNodeCvSVMParams params);        // This function is called by both constructors


    protected:
        Ptr<ml::SVM>                  m_pSVM;                   
        CSamplesAccumulator         * m_pSamplesAcc;            
    };
}