292 lines
11 KiB
C++
292 lines
11 KiB
C++
/***********************************************************
|
|
* File generated by the HALCON-Compiler hcomp version 20.11
|
|
* Usage: Interface to C++
|
|
*
|
|
* Software by: MVTec Software GmbH, www.mvtec.com
|
|
***********************************************************/
|
|
|
|
|
|
#ifndef HCPP_HCLASSGMM
|
|
#define HCPP_HCLASSGMM
|
|
|
|
namespace HalconCpp
|
|
{
|
|
|
|
// Represents an instance of a Gaussian mixture model.
|
|
class LIntExport HClassGmm : public HHandle
|
|
{
|
|
|
|
public:
|
|
|
|
// Create an uninitialized instance
|
|
HClassGmm():HHandle() {}
|
|
|
|
// Copy constructor
|
|
HClassGmm(const HClassGmm& source) : HHandle(source) {}
|
|
|
|
// Copy constructor
|
|
HClassGmm(const HHandle& handle);
|
|
|
|
// Create HClassGmm from handle, taking ownership
|
|
explicit HClassGmm(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_gmm')!
|
|
virtual void AssertType(Hphandle handle) const;
|
|
|
|
public:
|
|
|
|
// Deep copy of all data represented by this object instance
|
|
HClassGmm Clone() const;
|
|
|
|
|
|
|
|
/*****************************************************************************
|
|
* Operator-based class constructors
|
|
*****************************************************************************/
|
|
|
|
// read_class_gmm: Read a Gaussian Mixture Model from a file.
|
|
explicit HClassGmm(const HString& FileName);
|
|
|
|
// read_class_gmm: Read a Gaussian Mixture Model from a file.
|
|
explicit HClassGmm(const char* FileName);
|
|
|
|
#ifdef _WIN32
|
|
// read_class_gmm: Read a Gaussian Mixture Model from a file.
|
|
explicit HClassGmm(const wchar_t* FileName);
|
|
#endif
|
|
|
|
// create_class_gmm: Create a Gaussian Mixture Model for classification
|
|
explicit HClassGmm(Hlong NumDim, Hlong NumClasses, const HTuple& NumCenters, const HString& CovarType, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
|
|
// create_class_gmm: Create a Gaussian Mixture Model for classification
|
|
explicit HClassGmm(Hlong NumDim, Hlong NumClasses, Hlong NumCenters, const HString& CovarType, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
|
|
// create_class_gmm: Create a Gaussian Mixture Model for classification
|
|
explicit HClassGmm(Hlong NumDim, Hlong NumClasses, Hlong NumCenters, const char* CovarType, const char* Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
|
|
#ifdef _WIN32
|
|
// create_class_gmm: Create a Gaussian Mixture Model for classification
|
|
explicit HClassGmm(Hlong NumDim, Hlong NumClasses, Hlong NumCenters, const wchar_t* CovarType, const wchar_t* Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
#endif
|
|
|
|
|
|
|
|
|
|
/***************************************************************************
|
|
* Operators *
|
|
***************************************************************************/
|
|
|
|
// Classify an image with a Gaussian Mixture Model.
|
|
HRegion ClassifyImageClassGmm(const HImage& Image, double RejectionThreshold) const;
|
|
|
|
// Add training samples from an image to the training data of a Gaussian Mixture Model.
|
|
void AddSamplesImageClassGmm(const HImage& Image, const HRegion& ClassRegions, double Randomize) const;
|
|
|
|
// Get the training data of a Gaussian Mixture Model (GMM).
|
|
HClassTrainData GetClassTrainDataGmm() const;
|
|
|
|
// Add training data to a Gaussian Mixture Model (GMM).
|
|
void AddClassTrainDataGmm(const HClassTrainData& ClassTrainDataHandle) const;
|
|
|
|
// Selects an optimal combination from a set of features to classify the provided data.
|
|
HTuple SelectFeatureSetGmm(const HClassTrainData& ClassTrainDataHandle, const HString& SelectionMethod, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score);
|
|
|
|
// Selects an optimal combination from a set of features to classify the provided data.
|
|
HTuple SelectFeatureSetGmm(const HClassTrainData& ClassTrainDataHandle, const HString& SelectionMethod, const HString& GenParamName, double GenParamValue, HTuple* Score);
|
|
|
|
// Selects an optimal combination from a set of features to classify the provided data.
|
|
HTuple SelectFeatureSetGmm(const HClassTrainData& ClassTrainDataHandle, const char* SelectionMethod, const char* GenParamName, double GenParamValue, HTuple* Score);
|
|
|
|
#ifdef _WIN32
|
|
// Selects an optimal combination from a set of features to classify the provided data.
|
|
HTuple SelectFeatureSetGmm(const HClassTrainData& ClassTrainDataHandle, const wchar_t* SelectionMethod, const wchar_t* GenParamName, double GenParamValue, HTuple* Score);
|
|
#endif
|
|
|
|
// Create a look-up table using a gaussian mixture model to classify byte images.
|
|
HClassLUT CreateClassLutGmm(const HTuple& GenParamName, const HTuple& GenParamValue) const;
|
|
|
|
// Clear a Gaussian Mixture Model.
|
|
static void ClearClassGmm(const HClassGmmArray& GMMHandle);
|
|
|
|
// Clear a Gaussian Mixture Model.
|
|
void ClearClassGmm() const;
|
|
|
|
// Clear the training data of a Gaussian Mixture Model.
|
|
static void ClearSamplesClassGmm(const HClassGmmArray& GMMHandle);
|
|
|
|
// Clear the training data of a Gaussian Mixture Model.
|
|
void ClearSamplesClassGmm() const;
|
|
|
|
// Deserialize a serialized Gaussian Mixture Model.
|
|
void DeserializeClassGmm(const HSerializedItem& SerializedItemHandle);
|
|
|
|
// Serialize a Gaussian Mixture Model (GMM).
|
|
HSerializedItem SerializeClassGmm() const;
|
|
|
|
// Read a Gaussian Mixture Model from a file.
|
|
void ReadClassGmm(const HString& FileName);
|
|
|
|
// Read a Gaussian Mixture Model from a file.
|
|
void ReadClassGmm(const char* FileName);
|
|
|
|
#ifdef _WIN32
|
|
// Read a Gaussian Mixture Model from a file.
|
|
void ReadClassGmm(const wchar_t* FileName);
|
|
#endif
|
|
|
|
// Write a Gaussian Mixture Model to a file.
|
|
void WriteClassGmm(const HString& FileName) const;
|
|
|
|
// Write a Gaussian Mixture Model to a file.
|
|
void WriteClassGmm(const char* FileName) const;
|
|
|
|
#ifdef _WIN32
|
|
// Write a Gaussian Mixture Model to a file.
|
|
void WriteClassGmm(const wchar_t* FileName) const;
|
|
#endif
|
|
|
|
// Read the training data of a Gaussian Mixture Model from a file.
|
|
void ReadSamplesClassGmm(const HString& FileName) const;
|
|
|
|
// Read the training data of a Gaussian Mixture Model from a file.
|
|
void ReadSamplesClassGmm(const char* FileName) const;
|
|
|
|
#ifdef _WIN32
|
|
// Read the training data of a Gaussian Mixture Model from a file.
|
|
void ReadSamplesClassGmm(const wchar_t* FileName) const;
|
|
#endif
|
|
|
|
// Write the training data of a Gaussian Mixture Model to a file.
|
|
void WriteSamplesClassGmm(const HString& FileName) const;
|
|
|
|
// Write the training data of a Gaussian Mixture Model to a file.
|
|
void WriteSamplesClassGmm(const char* FileName) const;
|
|
|
|
#ifdef _WIN32
|
|
// Write the training data of a Gaussian Mixture Model to a file.
|
|
void WriteSamplesClassGmm(const wchar_t* FileName) const;
|
|
#endif
|
|
|
|
// Calculate the class of a feature vector by a Gaussian Mixture Model.
|
|
HTuple ClassifyClassGmm(const HTuple& Features, Hlong Num, HTuple* ClassProb, HTuple* Density, HTuple* KSigmaProb) const;
|
|
|
|
// Evaluate a feature vector by a Gaussian Mixture Model.
|
|
HTuple EvaluateClassGmm(const HTuple& Features, double* Density, double* KSigmaProb) const;
|
|
|
|
// Train a Gaussian Mixture Model.
|
|
HTuple TrainClassGmm(Hlong MaxIter, double Threshold, const HString& ClassPriors, double Regularize, HTuple* Iter) const;
|
|
|
|
// Train a Gaussian Mixture Model.
|
|
HTuple TrainClassGmm(Hlong MaxIter, double Threshold, const char* ClassPriors, double Regularize, HTuple* Iter) const;
|
|
|
|
#ifdef _WIN32
|
|
// Train a Gaussian Mixture Model.
|
|
HTuple TrainClassGmm(Hlong MaxIter, double Threshold, const wchar_t* ClassPriors, double Regularize, HTuple* Iter) const;
|
|
#endif
|
|
|
|
// Compute the information content of the preprocessed feature vectors of a GMM.
|
|
HTuple GetPrepInfoClassGmm(const HString& Preprocessing, HTuple* CumInformationCont) const;
|
|
|
|
// Compute the information content of the preprocessed feature vectors of a GMM.
|
|
HTuple GetPrepInfoClassGmm(const char* Preprocessing, HTuple* CumInformationCont) const;
|
|
|
|
#ifdef _WIN32
|
|
// Compute the information content of the preprocessed feature vectors of a GMM.
|
|
HTuple GetPrepInfoClassGmm(const wchar_t* Preprocessing, HTuple* CumInformationCont) const;
|
|
#endif
|
|
|
|
// Return the number of training samples stored in the training data of a Gaussian Mixture Model (GMM).
|
|
Hlong GetSampleNumClassGmm() const;
|
|
|
|
// Return a training sample from the training data of a Gaussian Mixture Models (GMM).
|
|
HTuple GetSampleClassGmm(Hlong NumSample, Hlong* ClassID) const;
|
|
|
|
// Add a training sample to the training data of a Gaussian Mixture Model.
|
|
void AddSampleClassGmm(const HTuple& Features, Hlong ClassID, double Randomize) const;
|
|
|
|
// Return the parameters of a Gaussian Mixture Model.
|
|
Hlong GetParamsClassGmm(Hlong* NumClasses, HTuple* MinCenters, HTuple* MaxCenters, HString* CovarType) const;
|
|
|
|
// Create a Gaussian Mixture Model for classification
|
|
void CreateClassGmm(Hlong NumDim, Hlong NumClasses, const HTuple& NumCenters, const HString& CovarType, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
|
|
// Create a Gaussian Mixture Model for classification
|
|
void CreateClassGmm(Hlong NumDim, Hlong NumClasses, Hlong NumCenters, const HString& CovarType, const HString& Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
|
|
// Create a Gaussian Mixture Model for classification
|
|
void CreateClassGmm(Hlong NumDim, Hlong NumClasses, Hlong NumCenters, const char* CovarType, const char* Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
|
|
#ifdef _WIN32
|
|
// Create a Gaussian Mixture Model for classification
|
|
void CreateClassGmm(Hlong NumDim, Hlong NumClasses, Hlong NumCenters, const wchar_t* CovarType, const wchar_t* Preprocessing, Hlong NumComponents, Hlong RandSeed);
|
|
#endif
|
|
|
|
};
|
|
|
|
// forward declarations and types for internal array implementation
|
|
|
|
template<class T> class HSmartPtr;
|
|
template<class T> class HHandleBaseArrayRef;
|
|
|
|
typedef HHandleBaseArrayRef<HClassGmm> HClassGmmArrayRef;
|
|
typedef HSmartPtr< HClassGmmArrayRef > HClassGmmArrayPtr;
|
|
|
|
|
|
// Represents multiple tool instances
|
|
class LIntExport HClassGmmArray : public HHandleBaseArray
|
|
{
|
|
|
|
public:
|
|
|
|
// Create empty array
|
|
HClassGmmArray();
|
|
|
|
// Create array from native array of tool instances
|
|
HClassGmmArray(HClassGmm* classes, Hlong length);
|
|
|
|
// Copy constructor
|
|
HClassGmmArray(const HClassGmmArray &tool_array);
|
|
|
|
// Destructor
|
|
virtual ~HClassGmmArray();
|
|
|
|
// Assignment operator
|
|
HClassGmmArray &operator=(const HClassGmmArray &tool_array);
|
|
|
|
// Clears array and all tool instances
|
|
virtual void Clear();
|
|
|
|
// Get array of native tool instances
|
|
const HClassGmm* 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
|
|
HClassGmmArrayPtr *mArrayPtr;
|
|
};
|
|
|
|
}
|
|
|
|
#endif
|