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/*
* Copyright (C) 2005-2020 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 otbBoostMachineLearningModel_h
#define otbBoostMachineLearningModel_h
#include "otbRequiresOpenCVCheck.h"
#include "itkLightObject.h"
#include "itkFixedArray.h"
#include "otbMachineLearningModel.h"
#include "otbOpenCVUtils.h"
namespace otb
{
template <class TInputValue, class TTargetValue>
class ITK_EXPORT BoostMachineLearningModel : public MachineLearningModel<TInputValue, TTargetValue>
{
public:
/** Standard class typedefs. */
typedef BoostMachineLearningModel Self;
typedef MachineLearningModel<TInputValue, TTargetValue> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef typename Superclass::InputValueType InputValueType;
typedef typename Superclass::InputSampleType InputSampleType;
typedef typename Superclass::InputListSampleType InputListSampleType;
typedef typename Superclass::TargetValueType TargetValueType;
typedef typename Superclass::TargetSampleType TargetSampleType;
typedef typename Superclass::TargetListSampleType TargetListSampleType;
typedef typename Superclass::ConfidenceValueType ConfidenceValueType;
typedef typename Superclass::ProbaSampleType ProbaSampleType;
/** Run-time type information (and related methods). */
itkNewMacro(Self);
itkTypeMacro(BoostMachineLearningModel, MachineLearningModel);
/** Setters/Getters to the Boost type
* It can be CvBoost::DISCRETE, CvBoost::REAL, CvBoost::LOGIT, CvBoost::GENTLE
* Default is CvBoost::REAL.
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams
*/
itkGetMacro(BoostType, int);
itkSetMacro(BoostType, int);
/** Setters/Getters to the number of weak classifiers.
* Default is 100.
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams
*/
itkGetMacro(WeakCount, int);
itkSetMacro(WeakCount, int);
/** Setters/Getters to the threshold WeightTrimRate.
* A threshold between 0 and 1 used to save computational time.
* Samples with summary weight \f$ w \leq 1 - WeightTrimRate \f$ do not participate in the next iteration of training.
* Set this parameter to 0 to turn off this functionality.
* Default is 0.95
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams
*/
itkGetMacro(WeightTrimRate, double);
itkSetMacro(WeightTrimRate, double);
/** Setters/Getters to the maximum depth of the tree.
* Default is 1
* \see http://docs.opencv.org/modules/ml/doc/decision_trees.html#CvDTreeParams::CvDTreeParams%28%29
*/
itkGetMacro(MaxDepth, int);
itkSetMacro(MaxDepth, int);
/** Train the machine learning model */
void Train() override;
/** Save the model to file */
void Save(const std::string& filename, const std::string& name = "") override;
/** Load the model from file */
void Load(const std::string& filename, const std::string& name = "") override;
/**\name Classification model file compatibility tests */
//@{
/** Is the input model file readable and compatible with the corresponding classifier ? */
bool CanReadFile(const std::string&) override;
/** Is the input model file writable and compatible with the corresponding classifier ? */
bool CanWriteFile(const std::string&) override;
//@}
protected:
/** Constructor */
BoostMachineLearningModel();
/** Destructor */
~BoostMachineLearningModel() override = default;
/** Predict values using the model */
TargetSampleType DoPredict(const InputSampleType& input, ConfidenceValueType* quality = nullptr, ProbaSampleType* proba = nullptr) const override;
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const override;
private:
BoostMachineLearningModel(const Self&) = delete;
void operator=(const Self&) = delete;
cv::Ptr<cv::ml::Boost> m_BoostModel;
int m_BoostType;
int m_WeakCount;
double m_WeightTrimRate;
int m_MaxDepth;
};
} // end namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbBoostMachineLearningModel.hxx"
#endif
#endif
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