handleaiuinew/env/halcon/include/halconcpp/HClassSvm.h

/***********************************************************
 * File generated by the HALCON-Compiler hcomp version 20.11
 * Usage: Interface to C++
 *
 * Software by: MVTec Software GmbH, www.mvtec.com
 ***********************************************************/


#ifndef HCPP_HCLASSSVM
#define HCPP_HCLASSSVM

namespace HalconCpp
{

// Represents an instance of a support vector machine.
class LIntExport HClassSvm : public HHandle
{

public:

  // Create an uninitialized instance
  HClassSvm():HHandle() {}

  // Copy constructor
  HClassSvm(const HClassSvm& source) : HHandle(source) {}

  // Copy constructor
  HClassSvm(const HHandle& handle);

  // Create HClassSvm from handle, taking ownership
  explicit HClassSvm(Hlong handle);

  bool operator==(const HHandle& obj) const
  {
    return HHandleBase::operator==(obj);
  }

  bool operator!=(const HHandle& obj) const
  {
    return HHandleBase::operator!=(obj);
  }

protected:

  // Verify matching semantic type ('class_svm')!
  virtual void AssertType(Hphandle handle) const;

public:

  // Deep copy of all data represented by this object instance
  HClassSvm Clone() const;



/*****************************************************************************
 * Operator-based class constructors
 *****************************************************************************/

  // read_class_svm: Read a support vector machine from a file.
  explicit HClassSvm(const HString& FileName);

  // read_class_svm: Read a support vector machine from a file.
  explicit HClassSvm(const char* FileName);

#ifdef _WIN32
  // read_class_svm: Read a support vector machine from a file.
  explicit HClassSvm(const wchar_t* FileName);
#endif

  // create_class_svm: Create a support vector machine for pattern classification.
  explicit HClassSvm(Hlong NumFeatures, const HString& KernelType, double KernelParam, double Nu, Hlong NumClasses, const HString& Mode, const HString& Preprocessing, Hlong NumComponents);

  // create_class_svm: Create a support vector machine for pattern classification.
  explicit HClassSvm(Hlong NumFeatures, const char* KernelType, double KernelParam, double Nu, Hlong NumClasses, const char* Mode, const char* Preprocessing, Hlong NumComponents);

#ifdef _WIN32
  // create_class_svm: Create a support vector machine for pattern classification.
  explicit HClassSvm(Hlong NumFeatures, const wchar_t* KernelType, double KernelParam, double Nu, Hlong NumClasses, const wchar_t* Mode, const wchar_t* Preprocessing, Hlong NumComponents);
#endif




  /***************************************************************************
   * Operators                                                               *
   ***************************************************************************/

  // Classify an image with a support vector machine.
  HRegion ClassifyImageClassSvm(const HImage& Image) const;

  // Add training samples from an image to the training data of a support vector machine.
  void AddSamplesImageClassSvm(const HImage& Image, const HRegion& ClassRegions) const;

  // Get the training data of a support vector machine (SVM).
  HClassTrainData GetClassTrainDataSvm() const;

  // Add training data to a support vector machine (SVM).
  void AddClassTrainDataSvm(const HClassTrainData& ClassTrainDataHandle) const;

  // Selects an optimal combination of features to classify the provided data.
  HTuple SelectFeatureSetSvm(const HClassTrainData& ClassTrainDataHandle, const HString& SelectionMethod, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score);

  // Selects an optimal combination of features to classify the provided data.
  HTuple SelectFeatureSetSvm(const HClassTrainData& ClassTrainDataHandle, const HString& SelectionMethod, const HString& GenParamName, double GenParamValue, HTuple* Score);

  // Selects an optimal combination of features to classify the provided data.
  HTuple SelectFeatureSetSvm(const HClassTrainData& ClassTrainDataHandle, const char* SelectionMethod, const char* GenParamName, double GenParamValue, HTuple* Score);

#ifdef _WIN32
  // Selects an optimal combination of features to classify the provided data.
  HTuple SelectFeatureSetSvm(const HClassTrainData& ClassTrainDataHandle, const wchar_t* SelectionMethod, const wchar_t* GenParamName, double GenParamValue, HTuple* Score);
#endif

  // Create a look-up table using a Support-Vector-Machine to classify byte images.
  HClassLUT CreateClassLutSvm(const HTuple& GenParamName, const HTuple& GenParamValue) const;

  // Clear a support vector machine.
  static void ClearClassSvm(const HClassSvmArray& SVMHandle);

  // Clear a support vector machine.
  void ClearClassSvm() const;

  // Clear the training data of a support vector machine.
  static void ClearSamplesClassSvm(const HClassSvmArray& SVMHandle);

  // Clear the training data of a support vector machine.
  void ClearSamplesClassSvm() const;

  // Deserialize a serialized support vector machine (SVM).
  void DeserializeClassSvm(const HSerializedItem& SerializedItemHandle);

  // Serialize a support vector machine (SVM).
  HSerializedItem SerializeClassSvm() const;

  // Read a support vector machine from a file.
  void ReadClassSvm(const HString& FileName);

  // Read a support vector machine from a file.
  void ReadClassSvm(const char* FileName);

#ifdef _WIN32
  // Read a support vector machine from a file.
  void ReadClassSvm(const wchar_t* FileName);
#endif

  // Write a support vector machine to a file.
  void WriteClassSvm(const HString& FileName) const;

  // Write a support vector machine to a file.
  void WriteClassSvm(const char* FileName) const;

#ifdef _WIN32
  // Write a support vector machine to a file.
  void WriteClassSvm(const wchar_t* FileName) const;
#endif

  // Read the training data of a support vector machine from a file.
  void ReadSamplesClassSvm(const HString& FileName) const;

  // Read the training data of a support vector machine from a file.
  void ReadSamplesClassSvm(const char* FileName) const;

#ifdef _WIN32
  // Read the training data of a support vector machine from a file.
  void ReadSamplesClassSvm(const wchar_t* FileName) const;
#endif

  // Write the training data of a support vector machine to a file.
  void WriteSamplesClassSvm(const HString& FileName) const;

  // Write the training data of a support vector machine to a file.
  void WriteSamplesClassSvm(const char* FileName) const;

#ifdef _WIN32
  // Write the training data of a support vector machine to a file.
  void WriteSamplesClassSvm(const wchar_t* FileName) const;
#endif

  // Evaluate a feature vector by a support vector machine.
  HTuple EvaluateClassSvm(const HTuple& Features) const;

  // Classify a feature vector by a support vector machine.
  HTuple ClassifyClassSvm(const HTuple& Features, const HTuple& Num) const;

  // Approximate a trained support vector machine by a reduced support vector machine for faster classification.
  HClassSvm ReduceClassSvm(const HString& Method, Hlong MinRemainingSV, double MaxError) const;

  // Approximate a trained support vector machine by a reduced support vector machine for faster classification.
  HClassSvm ReduceClassSvm(const char* Method, Hlong MinRemainingSV, double MaxError) const;

#ifdef _WIN32
  // Approximate a trained support vector machine by a reduced support vector machine for faster classification.
  HClassSvm ReduceClassSvm(const wchar_t* Method, Hlong MinRemainingSV, double MaxError) const;
#endif

  // Train a support vector machine.
  void TrainClassSvm(double Epsilon, const HTuple& TrainMode) const;

  // Train a support vector machine.
  void TrainClassSvm(double Epsilon, const HString& TrainMode) const;

  // Train a support vector machine.
  void TrainClassSvm(double Epsilon, const char* TrainMode) const;

#ifdef _WIN32
  // Train a support vector machine.
  void TrainClassSvm(double Epsilon, const wchar_t* TrainMode) const;
#endif

  // Compute the information content of the preprocessed feature vectors of a support vector machine
  HTuple GetPrepInfoClassSvm(const HString& Preprocessing, HTuple* CumInformationCont) const;

  // Compute the information content of the preprocessed feature vectors of a support vector machine
  HTuple GetPrepInfoClassSvm(const char* Preprocessing, HTuple* CumInformationCont) const;

#ifdef _WIN32
  // Compute the information content of the preprocessed feature vectors of a support vector machine
  HTuple GetPrepInfoClassSvm(const wchar_t* Preprocessing, HTuple* CumInformationCont) const;
#endif

  // Return the number of support vectors of a support vector machine.
  Hlong GetSupportVectorNumClassSvm(HTuple* NumSVPerSVM) const;

  // Return the index of a support vector from a trained support vector machine.
  double GetSupportVectorClassSvm(Hlong IndexSupportVector) const;

  // Return the number of training samples stored in the training data of a support vector machine.
  Hlong GetSampleNumClassSvm() const;

  // Return a training sample from the training data of a support vector machine.
  HTuple GetSampleClassSvm(Hlong IndexSample, Hlong* Target) const;

  // Add a training sample to the training data of a support vector machine.
  void AddSampleClassSvm(const HTuple& Features, const HTuple& Class) const;

  // Add a training sample to the training data of a support vector machine.
  void AddSampleClassSvm(const HTuple& Features, Hlong Class) const;

  // Return the parameters of a support vector machine.
  Hlong GetParamsClassSvm(HString* KernelType, double* KernelParam, double* Nu, Hlong* NumClasses, HString* Mode, HString* Preprocessing, Hlong* NumComponents) const;

  // Create a support vector machine for pattern classification.
  void CreateClassSvm(Hlong NumFeatures, const HString& KernelType, double KernelParam, double Nu, Hlong NumClasses, const HString& Mode, const HString& Preprocessing, Hlong NumComponents);

  // Create a support vector machine for pattern classification.
  void CreateClassSvm(Hlong NumFeatures, const char* KernelType, double KernelParam, double Nu, Hlong NumClasses, const char* Mode, const char* Preprocessing, Hlong NumComponents);

#ifdef _WIN32
  // Create a support vector machine for pattern classification.
  void CreateClassSvm(Hlong NumFeatures, const wchar_t* KernelType, double KernelParam, double Nu, Hlong NumClasses, const wchar_t* Mode, const wchar_t* Preprocessing, Hlong NumComponents);
#endif

};

// forward declarations and types for internal array implementation

template<class T> class HSmartPtr;
template<class T> class HHandleBaseArrayRef;

typedef HHandleBaseArrayRef<HClassSvm> HClassSvmArrayRef;
typedef HSmartPtr< HClassSvmArrayRef > HClassSvmArrayPtr;


// Represents multiple tool instances
class LIntExport HClassSvmArray : public HHandleBaseArray
{

public:

  // Create empty array
  HClassSvmArray();

  // Create array from native array of tool instances
  HClassSvmArray(HClassSvm* classes, Hlong length);

  // Copy constructor
  HClassSvmArray(const HClassSvmArray &tool_array);

  // Destructor
  virtual ~HClassSvmArray();

  // Assignment operator
  HClassSvmArray &operator=(const HClassSvmArray &tool_array);

  // Clears array and all tool instances
  virtual void Clear();

  // Get array of native tool instances
  const HClassSvm* Tools() const;

  // Get number of tools
  virtual Hlong Length() const;

  // Create tool array from tuple of handles
  virtual void SetFromTuple(const HTuple& handles);

  // Get tuple of handles for tool array
  virtual HTuple ConvertToTuple() const;

protected:

// Smart pointer to internal data container
   HClassSvmArrayPtr *mArrayPtr;
};

}

#endif