sitkCannySegmentationLevelSetImageFilter.h

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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
*
*         http://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 sitkCannySegmentationLevelSetImageFilter_h
#define sitkCannySegmentationLevelSetImageFilter_h
 
/*
 * WARNING: DO NOT EDIT THIS FILE!
 * THIS FILE IS AUTOMATICALLY GENERATED BY THE SIMPLEITK BUILD PROCESS.
 * Please look at sitkImageFilterTemplate.h.jinja to make changes.
 */
 
#include <memory>
 
#include "sitkBasicFilters.h"
#include "sitkImageFilter.h"
#include "sitkProcessObjectDeleter.h"
 
namespace itk::simple {

class SITKBasicFilters_EXPORT CannySegmentationLevelSetImageFilter : public ImageFilter {
public:
  using Self = CannySegmentationLevelSetImageFilter;

  virtual ~CannySegmentationLevelSetImageFilter();

  CannySegmentationLevelSetImageFilter();

  using PixelIDTypeList = RealPixelIDTypeList;
 
 
 

  void
  SetThreshold(double Threshold )
    { this->m_Threshold = Threshold; }

  double
  GetThreshold() const { return this->m_Threshold; }
 

  void
  SetVariance(double Variance )
    { this->m_Variance = Variance; }

  double
  GetVariance() const { return this->m_Variance; }
 

  void
  SetMaximumRMSError(double MaximumRMSError )
    { this->m_MaximumRMSError = MaximumRMSError; }

  double
  GetMaximumRMSError() const { return this->m_MaximumRMSError; }
 

  void
  SetPropagationScaling(double PropagationScaling )
    { this->m_PropagationScaling = PropagationScaling; }

  double
  GetPropagationScaling() const { return this->m_PropagationScaling; }
 

  void
  SetCurvatureScaling(double CurvatureScaling )
    { this->m_CurvatureScaling = CurvatureScaling; }

  double
  GetCurvatureScaling() const { return this->m_CurvatureScaling; }
 

  void
  SetAdvectionScaling(double AdvectionScaling )
    { this->m_AdvectionScaling = AdvectionScaling; }

  double
  GetAdvectionScaling() const { return this->m_AdvectionScaling; }
 

  void
  SetNumberOfIterations(uint32_t NumberOfIterations )
    { this->m_NumberOfIterations = NumberOfIterations; }

  uint32_t
  GetNumberOfIterations() const { return this->m_NumberOfIterations; }
 

  void
  SetReverseExpansionDirection(bool ReverseExpansionDirection )
    { this->m_ReverseExpansionDirection = ReverseExpansionDirection; }

  void
  ReverseExpansionDirectionOn() { return this->SetReverseExpansionDirection(true); }
  void
  ReverseExpansionDirectionOff() { return this->SetReverseExpansionDirection(false); }
  bool
  GetReverseExpansionDirection() const { return this->m_ReverseExpansionDirection; }
 

  void
  SetIsoSurfaceValue(double IsoSurfaceValue )
    { this->m_IsoSurfaceValue = IsoSurfaceValue; }

  double
  GetIsoSurfaceValue() const { return this->m_IsoSurfaceValue; }
 

  uint32_t GetElapsedIterations() const { return this->m_ElapsedIterations; }

  double GetRMSChange() const { return this->m_RMSChange; }

  Image GetCannyImage() const { return this->m_CannyImage; }

  std::string GetName() const { return std::string("CannySegmentationLevelSetImageFilter"); }

  std::string ToString() const;
 

#ifndef SWIG
    Image Execute(Image &&initialImage, const Image &featureImage);
#endif
  Image Execute(const Image &initialImage, const Image &featureImage);
 
 
private:
  using MemberFunctionType = Image (Self::*)(const Image *
    initialImage, const Image *
    featureImage);
  template <class TImageType> Image ExecuteInternal(const Image *
    initialImage, const Image *
    featureImage);
    friend struct detail::MemberFunctionAddressor<MemberFunctionType>;
    static const detail::MemberFunctionFactory<MemberFunctionType> &GetMemberFunctionFactory();
 
 
    double m_Threshold{ 0.0 };
 
    double m_Variance{ 0.0 };
 
  /* Value of RMS change below which the filter should stop. This is a convergence criterion. */
    double m_MaximumRMSError{ 0.02 };
 
  /* Weight of direct propagation contribution to the speed term */
    double m_PropagationScaling{ 1.0 };
 
  /* Weight of the curvature contribution to the speed term */
    double m_CurvatureScaling{ 1.0 };
 
  /* Weight of the advection contribution to the speed term */
    double m_AdvectionScaling{ 1.0 };
 
  /* Number of iterations to run */
    uint32_t m_NumberOfIterations{ 1000u };
 
  /* Turn On/Off the flag which determines whether Positive or Negative speed terms will cause surface expansion.  If set to TRUE then negative speed terms will cause the surface to expand and positive speed terms will cause the surface to contract.  If set to FALSE (default) then positive speed terms will cause the surface to expand and negative speed terms will cause the surface to contract.  This method can be safely used to reverse the expansion/contraction as appropriate to a particular application or data set. */
    bool m_ReverseExpansionDirection{ false };
 
    double m_IsoSurfaceValue{ 0.0 };
 
 
 
    uint32_t m_ElapsedIterations{ 0 };
    double m_RMSChange{ 0.0 };
    Image m_CannyImage{ Image() };
 
 
 
 
      bool m_InPlace{false};
 
};
 

#ifndef SWIG
SITKBasicFilters_EXPORT Image CannySegmentationLevelSet(
    Image &&initialImage, const Image &featureImage, double threshold = 0.0, double variance = 0.0, double maximumRMSError = 0.02, double propagationScaling = 1.0, double curvatureScaling = 1.0, double advectionScaling = 1.0, uint32_t numberOfIterations = 1000u, bool reverseExpansionDirection = false, double isoSurfaceValue = 0.0
);
 
 
#endif
SITKBasicFilters_EXPORT Image CannySegmentationLevelSet(
    const Image &initialImage, const Image &featureImage, double threshold = 0.0, double variance = 0.0, double maximumRMSError = 0.02, double propagationScaling = 1.0, double curvatureScaling = 1.0, double advectionScaling = 1.0, uint32_t numberOfIterations = 1000u, bool reverseExpansionDirection = false, double isoSurfaceValue = 0.0
);

 
}
#endif