diff --git a/Code/UtilitiesAdapters/OpenCV/otbMachineLearningModelFactory.txx b/Code/UtilitiesAdapters/OpenCV/otbMachineLearningModelFactory.txx
index 1d8bf19db380cb80d00e598e892f9b2aa971db2d..003bf6cd1dc1a55317151cf0f8abf4f29996c255 100644
--- a/Code/UtilitiesAdapters/OpenCV/otbMachineLearningModelFactory.txx
+++ b/Code/UtilitiesAdapters/OpenCV/otbMachineLearningModelFactory.txx
@@ -25,6 +25,7 @@
#include "otbLibSVMMachineLearningModelFactory.h"
#include "otbBoostMachineLearningModelFactory.h"
#include "otbNeuralNetworkMachineLearningModelFactory.h"
+#include "otbNormalBayesMachineLearningModelFactory.h"
namespace otb
@@ -99,6 +100,7 @@ MachineLearningModelFactory<TInputValue,TOutputValue>
itk::ObjectFactoryBase::RegisterFactory(SVMMachineLearningModelFactory<TInputValue,TOutputValue>::New());
itk::ObjectFactoryBase::RegisterFactory(BoostMachineLearningModelFactory<TInputValue,TOutputValue>::New());
itk::ObjectFactoryBase::RegisterFactory(NeuralNetworkMachineLearningModelFactory<TInputValue,TOutputValue>::New());
+ itk::ObjectFactoryBase::RegisterFactory(NormalBayesMachineLearningModelFactory<TInputValue,TOutputValue>::New());
firstTime = false;
}
diff --git a/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModel.h b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModel.h
new file mode 100644
index 0000000000000000000000000000000000000000..2d080ee033327b5003bf91a1fd8d324255f18ac9
--- /dev/null
+++ b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModel.h
@@ -0,0 +1,99 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.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 __otbNormalBayesMachineLearningModel_h
+#define __otbNormalBayesMachineLearningModel_h
+
+#include "itkLightObject.h"
+#include "itkVariableLengthVector.h"
+#include "itkFixedArray.h"
+#include "itkListSample.h"
+#include "otbMachineLearningModel.h"
+
+
+class CvNormalBayesClassifier;
+
+namespace otb
+{
+template <class TInputValue, class TTargetValue>
+class ITK_EXPORT NormalBayesMachineLearningModel
+ : public MachineLearningModel <TInputValue, TTargetValue>
+{
+public:
+ /** Standard class typedefs. */
+ typedef NormalBayesMachineLearningModel Self;
+ typedef MachineLearningModel<TInputValue, TTargetValue> Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ // Input related typedefs
+ typedef TInputValue InputValueType;
+ typedef itk::VariableLengthVector<InputValueType> InputSampleType;
+ typedef itk::Statistics::ListSample<InputSampleType> InputListSampleType;
+
+ // Target related typedefs
+ typedef TTargetValue TargetValueType;
+ typedef itk::FixedArray<TargetValueType,1> TargetSampleType;
+ typedef itk::Statistics::ListSample<TargetSampleType> TargetListSampleType;
+
+ /** Run-time type information (and related methods). */
+ itkNewMacro(Self);
+ itkTypeMacro(NormalBayesMachineLearningModel, itk::MachineLearningModel);
+
+ /** Train the machine learning model */
+ virtual void Train();
+
+ /** Predict values using the model */
+ virtual TargetSampleType Predict(const InputSampleType & input) const;
+
+ /** Save the model to file */
+ virtual void Save(const std::string & filename, const std::string & name="");
+
+ /** Load the model from file */
+ virtual void Load(const std::string & filename, const std::string & name="");
+
+ /** Determine the file type. Returns true if this ImageIO can read the
+ * file specified. */
+ virtual bool CanReadFile(const std::string &);
+
+ /** Determine the file type. Returns true if this ImageIO can write the
+ * file specified. */
+ virtual bool CanWriteFile(const std::string &);
+
+protected:
+ /** Constructor */
+ NormalBayesMachineLearningModel();
+
+ /** Destructor */
+ virtual ~NormalBayesMachineLearningModel();
+
+ /** PrintSelf method */
+ void PrintSelf(std::ostream& os, itk::Indent indent) const;
+
+private:
+ NormalBayesMachineLearningModel(const Self &); //purposely not implemented
+ void operator =(const Self&); //purposely not implemented
+
+ CvNormalBayesClassifier * m_NormalBayesModel;
+};
+} // end namespace otb
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbNormalBayesMachineLearningModel.txx"
+#endif
+
+#endif
diff --git a/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModel.txx b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModel.txx
new file mode 100644
index 0000000000000000000000000000000000000000..102e9d9ab3fb105fe8c0c8d4e21870be18811883
--- /dev/null
+++ b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModel.txx
@@ -0,0 +1,152 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.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 __otbNormalBayesMachineLearningModel_txx
+#define __otbNormalBayesMachineLearningModel_txx
+
+#include "otbNormalBayesMachineLearningModel.h"
+#include "otbOpenCVUtils.h"
+
+#include <opencv2/opencv.hpp>
+
+namespace otb
+{
+
+template <class TInputValue, class TOutputValue>
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::NormalBayesMachineLearningModel()
+{
+ m_NormalBayesModel = new CvNormalBayesClassifier;
+}
+
+
+template <class TInputValue, class TOutputValue>
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::~NormalBayesMachineLearningModel()
+{
+ delete m_NormalBayesModel;
+}
+
+/** Train the machine learning model */
+template <class TInputValue, class TOutputValue>
+void
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::Train()
+{
+ //convert listsample to opencv matrix
+ cv::Mat samples;
+ otb::ListSampleToMat<InputListSampleType>(this->GetInputListSample(), samples);
+
+ cv::Mat labels;
+ otb::ListSampleToMat<TargetListSampleType>(this->GetTargetListSample(),labels);
+
+ m_NormalBayesModel->train(samples,labels,cv::Mat(),cv::Mat(),false);
+}
+
+template <class TInputValue, class TOutputValue>
+typename NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::TargetSampleType
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::Predict(const InputSampleType & input) const
+{
+ //convert listsample to Mat
+ cv::Mat sample;
+
+ otb::SampleToMat<InputSampleType>(input,sample);
+
+ cv::Mat missing = cv::Mat(1,input.Size(), CV_8U );
+ missing.setTo(0);
+ double result = m_NormalBayesModel->predict(sample);
+
+ TargetSampleType target;
+
+ target[0] = static_cast<TOutputValue>(result);
+
+ return target;
+}
+
+template <class TInputValue, class TOutputValue>
+void
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::Save(const std::string & filename, const std::string & name)
+{
+ if (name == "")
+ m_NormalBayesModel->save(filename.c_str(), 0);
+ else
+ m_NormalBayesModel->save(filename.c_str(), name.c_str());
+}
+
+template <class TInputValue, class TOutputValue>
+void
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::Load(const std::string & filename, const std::string & name)
+{
+ if (name == "")
+ m_NormalBayesModel->load(filename.c_str(), 0);
+ else
+ m_NormalBayesModel->load(filename.c_str(), name.c_str());
+}
+
+template <class TInputValue, class TOutputValue>
+bool
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::CanReadFile(const std::string & file)
+{
+ std::ifstream ifs;
+ ifs.open(file.c_str());
+
+ if(!ifs)
+ {
+ std::cerr<<"Could not read file "<<file<<std::endl;
+ return false;
+ }
+
+ while (!ifs.eof())
+ {
+ std::string line;
+ std::getline(ifs, line);
+
+ if (line.find(CV_TYPE_NAME_ML_NBAYES) != std::string::npos)
+ {
+ std::cout<<"Reading a "<<CV_TYPE_NAME_ML_NBAYES<<" model !!!"<<std::endl;
+ return true;
+ }
+ }
+ ifs.close();
+ return false;
+}
+
+template <class TInputValue, class TOutputValue>
+bool
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::CanWriteFile(const std::string & file)
+{
+ return false;
+}
+
+template <class TInputValue, class TOutputValue>
+void
+NormalBayesMachineLearningModel<TInputValue,TOutputValue>
+::PrintSelf(std::ostream& os, itk::Indent indent) const
+{
+ // Call superclass implementation
+ Superclass::PrintSelf(os,indent);
+}
+
+} //end namespace otb
+
+#endif
diff --git a/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModelFactory.h b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModelFactory.h
new file mode 100644
index 0000000000000000000000000000000000000000..4783350efd17b7c33099dd77e97937224ff05bd0
--- /dev/null
+++ b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModelFactory.h
@@ -0,0 +1,72 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.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 __otbNormalBayesMachineLearningModelFactory_h
+#define __otbNormalBayesMachineLearningModelFactory_h
+
+#include "itkObjectFactoryBase.h"
+#include "itkImageIOBase.h"
+
+namespace otb
+{
+/** \class NormalBayesMachineLearningModelFactory
+ * \brief Creation d'un instance d'un objet SVMMachineLearningModel utilisant les object factory.
+ */
+template <class TInputValue, class TTargetValue>
+class ITK_EXPORT NormalBayesMachineLearningModelFactory : public itk::ObjectFactoryBase
+{
+public:
+ /** Standard class typedefs. */
+ typedef NormalBayesMachineLearningModelFactory Self;
+ typedef itk::ObjectFactoryBase Superclass;
+ typedef itk::SmartPointer<Self> Pointer;
+ typedef itk::SmartPointer<const Self> ConstPointer;
+
+ /** Class methods used to interface with the registered factories. */
+ virtual const char* GetITKSourceVersion(void) const;
+ virtual const char* GetDescription(void) const;
+
+ /** Method for class instantiation. */
+ itkFactorylessNewMacro(Self);
+
+ /** Run-time type information (and related methods). */
+ itkTypeMacro(NormalBayesMachineLearningModelFactory, itk::ObjectFactoryBase);
+
+ /** Register one factory of this type */
+ static void RegisterOneFactory(void)
+ {
+ NormalBayesMachineLearningModelFactory::Pointer Factory = NormalBayesMachineLearningModelFactory::New();
+ itk::ObjectFactoryBase::RegisterFactory(Factory);
+ }
+
+protected:
+ NormalBayesMachineLearningModelFactory();
+ virtual ~NormalBayesMachineLearningModelFactory();
+
+private:
+ NormalBayesMachineLearningModelFactory(const Self &); //purposely not implemented
+ void operator =(const Self&); //purposely not implemented
+
+};
+
+} // end namespace otb
+
+#ifndef OTB_MANUAL_INSTANTIATION
+#include "otbNormalBayesMachineLearningModelFactory.txx"
+#endif
+
+#endif
diff --git a/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModelFactory.txx b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModelFactory.txx
new file mode 100644
index 0000000000000000000000000000000000000000..5060481e59da6c0215f9d023e4a97eae7ed919ae
--- /dev/null
+++ b/Code/UtilitiesAdapters/OpenCV/otbNormalBayesMachineLearningModelFactory.txx
@@ -0,0 +1,64 @@
+/*=========================================================================
+
+ Program: ORFEO Toolbox
+ Language: C++
+ Date: $Date$
+ Version: $Revision$
+
+
+ Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
+ See OTBCopyright.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.
+
+=========================================================================*/
+#include "otbNormalBayesMachineLearningModelFactory.h"
+
+#include "itkCreateObjectFunction.h"
+#include "otbNormalBayesMachineLearningModel.h"
+#include "itkVersion.h"
+
+namespace otb
+{
+
+template <class TInputValue, class TOutputValue>
+NormalBayesMachineLearningModelFactory<TInputValue,TOutputValue>
+::NormalBayesMachineLearningModelFactory()
+{
+
+ static std::string classOverride = std::string("otbMachineLearningModel");
+ static std::string subclass = std::string("otbNormalBayesMachineLearningModel");
+
+ this->RegisterOverride(classOverride.c_str(),
+ subclass.c_str(),
+ "Normal Bayes ML Model",
+ 1,
+ itk::CreateObjectFunction<NormalBayesMachineLearningModel<TInputValue,TOutputValue> >::New());
+}
+
+template <class TInputValue, class TOutputValue>
+NormalBayesMachineLearningModelFactory<TInputValue,TOutputValue>
+::~NormalBayesMachineLearningModelFactory()
+{
+}
+
+template <class TInputValue, class TOutputValue>
+const char*
+NormalBayesMachineLearningModelFactory<TInputValue,TOutputValue>
+::GetITKSourceVersion(void) const
+{
+ return ITK_SOURCE_VERSION;
+}
+
+template <class TInputValue, class TOutputValue>
+const char*
+NormalBayesMachineLearningModelFactory<TInputValue,TOutputValue>
+::GetDescription() const
+{
+ return "Normal Bayes machine learning model factory";
+}
+
+} // end namespace otb
diff --git a/Testing/Code/Learning/CMakeLists.txt b/Testing/Code/Learning/CMakeLists.txt
index 686221a969aeea30f384aac13bc625b099e52e69..023b8ccc19db8385b80a09393c7e1b143e5a110c 100644
--- a/Testing/Code/Learning/CMakeLists.txt
+++ b/Testing/Code/Learning/CMakeLists.txt
@@ -749,6 +749,15 @@ IF(OTB_USE_OPENCV)
${INPUTDATA}/letter.scale
${TEMP}/ANNMachineLearningModel.txt
)
+
+ ADD_TEST(leTvNormalBayesMachineLearningModel ${LEARNING_TESTS6}
+ #--compare-ascii ${NOTOL}
+ #${BASELINE_FILES}/NormalBayesMachineLearningModel.txt
+ #${TEMP}/NormalBayesMachineLearningModel.txt
+ otbNormalBayesMachineLearningModel
+ ${INPUTDATA}/letter.scale
+ ${TEMP}/NormalBayesMachineLearningModel.txt
+ )
ADD_TEST(leTuImageClassificationFilterNew ${LEARNING_TESTS6}
otbImageClassificationFilterNew)
@@ -799,6 +808,11 @@ IF(OTB_USE_OPENCV)
otbNeuralNetworkMachineLearningModelCanRead
${INPUTDATA}/NeuralNetworkMachineLearningModel.txt
)
+
+ ADD_TEST(leTuNormalBayesMachineLearningModelCanRead ${LEARNING_TESTS6}
+ otbNormalBayesMachineLearningModelCanRead
+ ${INPUTDATA}/NormalBayesMachineLearningModel.txt
+ )
ENDIF(OTB_USE_OPENCV)
diff --git a/Testing/Code/Learning/otbLearningTests6.cxx b/Testing/Code/Learning/otbLearningTests6.cxx
index 749102badb033dbfaf038d1701dc7f0096b6e5ae..5594144620a399cecb655168ca6e61ad774423b7 100644
--- a/Testing/Code/Learning/otbLearningTests6.cxx
+++ b/Testing/Code/Learning/otbLearningTests6.cxx
@@ -36,6 +36,8 @@ void RegisterTests()
REGISTER_TEST(otbBoostMachineLearningModel);
REGISTER_TEST(otbANNMachineLearningModelNew);
REGISTER_TEST(otbANNMachineLearningModel);
+ REGISTER_TEST(otbNormalBayesMachineLearningModelNew);
+ REGISTER_TEST(otbNormalBayesMachineLearningModel);
REGISTER_TEST(otbImageClassificationFilterNew);
REGISTER_TEST(otbImageClassificationFilter);
REGISTER_TEST(otbLibSVMMachineLearningModelCanRead);
@@ -43,4 +45,5 @@ void RegisterTests()
REGISTER_TEST(otbRandomForestsMachineLearningModelCanRead);
REGISTER_TEST(otbBoostMachineLearningModelCanRead);
REGISTER_TEST(otbNeuralNetworkMachineLearningModelCanRead);
+ REGISTER_TEST(otbNormalBayesMachineLearningModelCanRead);
}
diff --git a/Testing/Code/Learning/otbMachineLearningModelCanRead.cxx b/Testing/Code/Learning/otbMachineLearningModelCanRead.cxx
index 5cb62adee181bdc7885239442e0520b3a6730266..578fab35924458a8bf67a4d4bd2f7750298e8c35 100644
--- a/Testing/Code/Learning/otbMachineLearningModelCanRead.cxx
+++ b/Testing/Code/Learning/otbMachineLearningModelCanRead.cxx
@@ -22,6 +22,7 @@
#include "otbRandomForestsMachineLearningModel.h"
#include "otbBoostMachineLearningModel.h"
#include "otbNeuralNetworkMachineLearningModel.h"
+#include "otbNormalBayesMachineLearningModel.h"
#include <iostream>
typedef otb::MachineLearningModel<float,short> MachineLearningModelType;
@@ -162,4 +163,29 @@ int otbNeuralNetworkMachineLearningModelCanRead(int argc, char* argv[])
return EXIT_SUCCESS;
}
+int otbNormalBayesMachineLearningModelCanRead(int argc, char* argv[])
+{
+ if (argc != 2)
+ {
+ std::cerr << "Usage: " << argv[0]
+ << "<model>" << std::endl;
+ std::cerr << "Called here with " << argc << " arguments\n";
+ for (int i = 1; i < argc; ++i)
+ {
+ std::cerr << " - " << argv[i] << "\n";
+ }
+ return EXIT_FAILURE;
+ }
+ std::string filename(argv[1]);
+ typedef otb::NormalBayesMachineLearningModel<InputValueType, TargetValueType> NormalBayesType;
+ NormalBayesType::Pointer classifier = NormalBayesType::New();
+ bool lCanRead = classifier->CanReadFile(filename);
+ if (lCanRead == false)
+ {
+ std::cerr << "Erreur otb::NormalBayesMachineLearningModel : impossible to open the file " << filename << "." << std::endl;
+ return EXIT_FAILURE;
+ }
+
+ return EXIT_SUCCESS;
+}
diff --git a/Testing/Code/Learning/otbTrainMachineLearningModel.cxx b/Testing/Code/Learning/otbTrainMachineLearningModel.cxx
index ba2e3f29687e16ef8a40e3da5187aaf99cf8c880..3f11e9991ecc082de62d0a0bf102ada754047d98 100644
--- a/Testing/Code/Learning/otbTrainMachineLearningModel.cxx
+++ b/Testing/Code/Learning/otbTrainMachineLearningModel.cxx
@@ -27,6 +27,7 @@
#include "otbRandomForestsMachineLearningModel.h"
#include "otbBoostMachineLearningModel.h"
#include "otbNeuralNetworkMachineLearningModel.h"
+#include "otbNormalBayesMachineLearningModel.h"
#include "otbConfusionMatrixCalculator.h"
@@ -478,6 +479,58 @@ int otbANNMachineLearningModel(int argc, char * argv[])
return EXIT_SUCCESS;
}
+int otbNormalBayesMachineLearningModelNew(int argc, char * argv[])
+{
+ typedef otb::NormalBayesMachineLearningModel<InputValueType,TargetValueType> NormalBayesType;
+ NormalBayesType::Pointer classifier = NormalBayesType::New();
+ return EXIT_SUCCESS;
+}
+
+int otbNormalBayesMachineLearningModel(int argc, char * argv[])
+{
+ if (argc != 3 )
+ {
+ std::cout<<"Wrong number of arguments "<<std::endl;
+ std::cout<<"Usage : sample file, output file "<<std::endl;
+ return EXIT_FAILURE;
+ }
+
+ typedef otb::NormalBayesMachineLearningModel<InputValueType, TargetValueType> NormalBayesType;
+
+ InputListSampleType::Pointer samples = InputListSampleType::New();
+ TargetListSampleType::Pointer labels = TargetListSampleType::New();
+ TargetListSampleType::Pointer predicted = TargetListSampleType::New();
+
+ if(!ReadDataFile(argv[1],samples,labels))
+ {
+ std::cout<<"Failed to read samples file "<<argv[1]<<std::endl;
+ return EXIT_FAILURE;
+ }
+
+ NormalBayesType::Pointer classifier = NormalBayesType::New();
+ classifier->SetInputListSample(samples);
+ classifier->SetTargetListSample(labels);
+ classifier->Train();
+
+ classifier->SetTargetListSample(predicted);
+ classifier->PredictAll();
+
+ classifier->Save(argv[2]);
+
+ ConfusionMatrixCalculatorType::Pointer cmCalculator = ConfusionMatrixCalculatorType::New();
+
+ cmCalculator->SetProducedLabels(predicted);
+ cmCalculator->SetReferenceLabels(labels);
+ cmCalculator->Compute();
+
+ std::cout<<"Confusion matrix: "<<std::endl;
+ std::cout<<cmCalculator->GetConfusionMatrix()<<std::endl;
+ std::cout<<"Kappa: "<<cmCalculator->GetKappaIndex()<<std::endl;
+ std::cout<<"Overall Accuracy: "<<cmCalculator->GetOverallAccuracy()<<std::endl;
+
+ return EXIT_SUCCESS;
+}
+