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/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkImageModelEstimatorBase_h
#define itkImageModelEstimatorBase_h
#include "itkLightProcessObject.h"
namespace itk
{
/**
* \class ImageModelEstimatorBase
* \brief Base class for model estimation from images used for classification.
*
* itkImageModelEstimatorBase is the base class for the ImageModelEstimator
* objects. It provides the basic function definitions that are inherent to
* ImageModelEstimator objects.
*
* This is the Superclass for the ImageModelEstimator framework. This is an
* abstract class defining an interface for all such objects
* available through the ImageModelEstimator framework in the ITK toolkit.
*
* The basic functionality of the ImageModelEstimator framework base class is to
* generate the models used in classification applications. It requires input
* images and a training image to be provided by the user.
* This object supports data handling of multiband images. The object
* accepts the input image in vector format only, where each pixel is a
* vector and each element of the vector corresponds to an entry from
* 1 particular band of a multiband dataset. A single band image is treated
* as a vector image with a single element for every vector. The classified
* image is treated as a single band scalar image.
*
* EstimateModels() is a pure virtual function making this an abstract class.
* The template parameter is the type of membership function the
* ImageModelEstimator populates.
*
* A membership function represents a specific knowledge about
* a class. In other words, it should tell us how "likely" is that a
* measurement vector (pattern) belong to the class.
*
* As the method name indicates, you can have more than one membership
* function. One for each classes. The order of the membership
* calculator becomes the class label for the class that is represented
* by the membership calculator.
*
* \ingroup ClassificationFilters
* \ingroup ITKClassifiers
*/
template <typename TInputImage, typename TMembershipFunction>
class ITK_TEMPLATE_EXPORT ImageModelEstimatorBase : public LightProcessObject
{
public:
ITK_DISALLOW_COPY_AND_MOVE(ImageModelEstimatorBase);
/** Standard class type aliases. */
using Self = ImageModelEstimatorBase;
using Superclass = LightProcessObject;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(ImageModelEstimatorBase);
/** Set the number of classes. */
itkSetMacro(NumberOfModels, unsigned int);
/** Get the number of classes. */
itkGetConstReferenceMacro(NumberOfModels, unsigned int);
/** Type definitions for the membership function . */
using MembershipFunctionPointer = typename TMembershipFunction::Pointer;
using MembershipFunctionPointerVector = std::vector<MembershipFunctionPointer>;
/** Type definitions for the training image. */
using InputImageType = TInputImage;
using InputImagePointer = typename TInputImage::Pointer;
/** Type definitions for the training image. */
// using TrainingImagePointer = typename TTrainingImage::Pointer;
/** Get/Set the input image. */
itkSetObjectMacro(InputImage, InputImageType);
itkGetModifiableObjectMacro(InputImage, InputImageType);
/** Set the classified image. */
void
SetMembershipFunctions(MembershipFunctionPointerVector membershipFunctions)
{
m_MembershipFunctions = membershipFunctions;
}
/** Method to get mean */
const MembershipFunctionPointerVector
GetMembershipFunctions() const
{
return m_MembershipFunctions;
}
/** Method to number of membership functions */
unsigned int
GetNumberOfMembershipFunctions()
{
return static_cast<unsigned int>(m_MembershipFunctions.size());
}
/** Method to reset the membership function mean */
void
DeleteAllMembershipFunctions()
{
m_MembershipFunctions.resize(0);
}
/** Add a membership function corresponding to the class index.
*
* Stores a MembershipCalculator of a class in its internal vector.
*/
unsigned int
AddMembershipFunction(MembershipFunctionPointer function);
/** Define a virtual function to perform model generation from the input data
*/
void
Update();
protected:
ImageModelEstimatorBase();
~ImageModelEstimatorBase() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
void
GenerateData() override;
private:
unsigned int m_NumberOfModels{ 0 };
/** Container to hold the membership functions */
MembershipFunctionPointerVector m_MembershipFunctions{};
/**Container for holding the training image */
InputImagePointer m_InputImage{};
/** The core virtual function to perform modeling of the input data */
virtual void
EstimateModels() = 0;
}; // class ImageModelEstimator
} // namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkImageModelEstimatorBase.hxx"
#endif
#endif
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