text: #ifndef _OPENCV_BOOST_H_
  #define _OPENCV_BOOST_H_
  
  #include "features.h"
  #include "ml.h"
  
  struct CvCascadeBoostParams : CvBoostParams
  {
      float minHitRate;
      float maxFalseAlarm;
      
      CvCascadeBoostParams();
      CvCascadeBoostParams( int _boostType, float _minHitRate, float _maxFalseAlarm,
                            double _weightTrimRate, int _maxDepth, int _maxWeakCount );
      virtual ~CvCascadeBoostParams() {}
      void write( FileStorage &fs ) const;
      bool read( const FileNode &node );
      virtual void printDefaults() const;
      virtual void printAttrs() const;
      virtual bool scanAttr( const String prmName, const String val);
  };
  
  struct CvCascadeBoostTrainData : CvDTreeTrainData
  {
      CvCascadeBoostTrainData( const CvFeatureEvaluator* _featureEvaluator,
                               const CvDTreeParams& _params );
      CvCascadeBoostTrainData( const CvFeatureEvaluator* _featureEvaluator,
                               int _numSamples, int _precalcValBufSize, int _precalcIdxBufSize,
                               const CvDTreeParams& _params = CvDTreeParams() );
      virtual void setData( const CvFeatureEvaluator* _featureEvaluator,
                            int _numSamples, int _precalcValBufSize, int _precalcIdxBufSize,
                            const CvDTreeParams& _params=CvDTreeParams() );
      void precalculate();
  
      virtual void get_class_labels( CvDTreeNode* n, int* labelsBuf, const int** labels );
      virtual void get_cv_labels( CvDTreeNode* n, int* labelsBuf, const int** labels );
      virtual void get_sample_indices( CvDTreeNode* n, int* indicesBuf, const int** labels );
      
      virtual int get_ord_var_data( CvDTreeNode* n, int vi, float* ordValuesBuf, int* indicesBuf,
                                    const float** ordValues, const int** indices );
      virtual int get_cat_var_data( CvDTreeNode* n, int vi, int* catValuesBuf, const int** catValues );
      virtual float getVarValue( int vi, int si );
      virtual void free_train_data();
  
      const CvFeatureEvaluator* featureEvaluator;
      Mat valCache; // precalculated feature values (CV_32FC1)
      CvMat _resp; // for casting
      int numPrecalcVal, numPrecalcIdx;
  };
  
  class CvCascadeBoostTree : public CvBoostTree
  {
  public:
      virtual CvDTreeNode* predict( int sampleIdx ) const;
      void write( FileStorage &fs, const Mat& featureMap );
      void read( const FileNode &node, CvBoost* _ensemble, CvDTreeTrainData* _data );
      void markFeaturesInMap( Mat& featureMap );
  protected:
      virtual void split_node_data( CvDTreeNode* n );
  };
  
  class CvCascadeBoost : public CvBoost
  {
  public:
      virtual bool train( const CvFeatureEvaluator* _featureEvaluator,
                          int _numSamples, int _precalcValBufSize, int _precalcIdxBufSize,
                          const CvCascadeBoostParams& _params=CvCascadeBoostParams() );
      virtual float predict( int sampleIdx, bool returnSum = false ) const;
  
      float getThreshold() const { return threshold; }; 
      void write( FileStorage &fs, const Mat& featureMap ) const;
      bool read( const FileNode &node, const CvFeatureEvaluator* _featureEvaluator,
                 const CvCascadeBoostParams& _params );
      void markUsedFeaturesInMap( Mat& featureMap );
  protected:
      virtual bool set_params( const CvBoostParams& _params );
      virtual void update_weights( CvBoostTree* tree );
      virtual bool isErrDesired();
  
      float threshold;
      float minHitRate, maxFalseAlarm;
  };
  
  #endif
  