otbMachineLearningModel.h

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/*
 * Copyright (C) 2005-2024 Centre National d'Etudes Spatiales (CNES)
 *
 * This file is part of Orfeo Toolbox
 *
 *     https://www.orfeo-toolbox.org/
 *
 * 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
 *
 * 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 otbMachineLearningModel_h
#define otbMachineLearningModel_h
 
#include "itkObject.h"
#include "itkListSample.h"
#include "otbMachineLearningModelTraits.h"
 
namespace otb
{
 
template <class TInputValue, class TTargetValue, class TConfidenceValue = double>
class ITK_EXPORT MachineLearningModel : public itk::Object
{
public:
  typedef MachineLearningModel          Self;
  typedef itk::Object                   Superclass;
  typedef itk::SmartPointer<Self>       Pointer;
  typedef itk::SmartPointer<const Self> ConstPointer;
 
  typedef typename MLMSampleTraits<TInputValue>::ValueType  InputValueType;
  typedef typename MLMSampleTraits<TInputValue>::SampleType InputSampleType;
  typedef itk::Statistics::ListSample<InputSampleType>      InputListSampleType;
 
  typedef typename MLMTargetTraits<TTargetValue>::ValueType  TargetValueType;
  typedef typename MLMTargetTraits<TTargetValue>::SampleType TargetSampleType;
  typedef itk::Statistics::ListSample<TargetSampleType>      TargetListSampleType;
 
  typedef typename MLMTargetTraits<TConfidenceValue>::ValueType  ConfidenceValueType;
  typedef typename MLMTargetTraits<TConfidenceValue>::SampleType ConfidenceSampleType;
  typedef itk::Statistics::ListSample<ConfidenceSampleType>      ConfidenceListSampleType;
 
 
  typedef itk::VariableLengthVector<double>            ProbaSampleType;
  typedef itk::Statistics::ListSample<ProbaSampleType> ProbaListSampleType;
 
  itkTypeMacro(MachineLearningModel, itk::Object);
 
  virtual void Train() = 0;
 
  TargetSampleType Predict(const InputSampleType& input, ConfidenceValueType* quality = nullptr, ProbaSampleType* proba = nullptr) const;
 
  itkSetMacro(Dimension, unsigned int);
  itkGetMacro(Dimension, unsigned int);
 
 
  typename TargetListSampleType::Pointer PredictBatch(const InputListSampleType* input, ConfidenceListSampleType* quality = nullptr,
                                                      ProbaListSampleType* proba = nullptr) const;
 
 
  virtual void Save(const std::string& filename, const std::string& name = "") = 0;
 
  virtual void Load(const std::string& filename, const std::string& name = "") = 0;
 
 
  virtual bool CanReadFile(const std::string&) = 0;
 
  virtual bool CanWriteFile(const std::string&) = 0;
 
  bool HasConfidenceIndex() const
  {
    return m_ConfidenceIndex;
  }
 
  bool HasProbaIndex() const
  {
    return m_ProbaIndex;
  }
 
  itkSetObjectMacro(InputListSample, InputListSampleType);
  itkGetObjectMacro(InputListSample, InputListSampleType);
  itkGetConstObjectMacro(InputListSample, InputListSampleType);
 
 
 
  itkSetObjectMacro(TargetListSample, TargetListSampleType);
 
  itkGetObjectMacro(TargetListSample, TargetListSampleType);
 
  itkGetObjectMacro(ConfidenceListSample, ConfidenceListSampleType);
 
  itkGetMacro(RegressionMode, bool);
  void SetRegressionMode(bool flag);
 
 
protected:
  MachineLearningModel();
 
  ~MachineLearningModel() override = default;
 
  void PrintSelf(std::ostream& os, itk::Indent indent) const override;
 
  typename InputListSampleType::Pointer m_InputListSample;
 
  typename InputListSampleType::Pointer m_ValidationListSample;
 
  typename TargetListSampleType::Pointer m_TargetListSample;
 
  typename ConfidenceListSampleType::Pointer m_ConfidenceListSample;
 
  bool m_RegressionMode;
 
  bool m_IsRegressionSupported;
 
  bool m_ConfidenceIndex;
 
  bool m_ProbaIndex;
 
  bool m_IsDoPredictBatchMultiThreaded;
 
  unsigned int m_Dimension;
 
private:
  virtual void DoPredictBatch(const InputListSampleType* input, const unsigned int& startIndex, const unsigned int& size, TargetListSampleType* target,
                              ConfidenceListSampleType* quality = nullptr, ProbaListSampleType* proba = nullptr) const;
 
  virtual TargetSampleType DoPredict(const InputSampleType& input, ConfidenceValueType* quality = nullptr, ProbaSampleType* proba = nullptr) const = 0;
 
  MachineLearningModel(const Self&) = delete;
  void operator=(const Self&) = delete;
};
} // end namespace otb
 
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbMachineLearningModel.hxx"
#endif
 
#endif