/usr/include/OTB-5.8/otbSOMMap.h is in libotb-dev 5.8.0+dfsg-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | /*=========================================================================
Program: ORFEO Toolbox
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
Copyright (c) Institut Telecom; Telecom Bretagne. All right reserved.
See IMTCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef otbSOMMap_h
#define otbSOMMap_h
#include "itkVariableLengthVector.h"
#include "itkEuclideanDistanceMetric.h"
#include "otbVectorImage.h"
namespace otb
{
/**
* \class SOMMap
* \brief This class represent a Self Organizing Map.
*
* The Self organizing map (or Kohonen map) is a type of neural networks. It is based on an analogy with
* the visual cortex, where similar inputs activate neighbor neurons.
*
* This class extends the Image object, where each pixel represents a neuron in the map.
* It is templated with a distance parameter used to compute the neuron response to an input.
* Thanks to the extension of the Image object, reading and writing is supported through standard image
* readers and writers.
*
* The training is done via the SOM class, and the activation map can be produced with the SOMActivationBuilder
* class.
*
* \sa SOM
* \sa SOMActivationBuilder
*
* \ingroup OTBSOM
*/
template <class TNeuron = itk::VariableLengthVector<double>,
class TDistance = itk::Statistics::EuclideanDistanceMetric<TNeuron>,
unsigned int VMapDimension = 2>
class ITK_EXPORT SOMMap
: public otb::VectorImage<typename TNeuron::ComponentType, VMapDimension>
{
public:
/** Standard typedefs */
typedef SOMMap Self;
typedef otb::VectorImage<typename TNeuron::ComponentType, VMapDimension> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Creation through object factory macro */
itkNewMacro(Self);
/**
* There is no runtime information macro since
* this class has to be considered to as a simple VectorImage
* // itkTypeMacro(SOMMap, VectorImage);
* */
/** Template parameters related typedefs */
typedef TNeuron NeuronType;
typedef TDistance DistanceType;
typedef typename DistanceType::Pointer DistancePointerType;
/** Superclass related typedefs */
typedef typename Superclass::IndexType IndexType;
typedef typename Superclass::SizeType SizeType;
typedef typename Superclass::DirectionType DirectionType;
typedef typename Superclass::RegionType RegionType;
typedef typename Superclass::SpacingType SpacingType;
typedef typename Superclass::PointType PointType;
/**
* Get The index of the winning neuron for a sample.
* \param sample the sample.
* \return The index of the winning neuron.
*/
IndexType GetWinner(const NeuronType& sample);
protected:
/** Constructor */
SOMMap();
/** Destructor */
~SOMMap() ITK_OVERRIDE;
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const ITK_OVERRIDE;
private:
SOMMap(const Self &); // purposely not implemented
void operator =(const Self&); // purposely not implemented
};
} // end namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbSOMMap.txx"
#endif
#endif
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