diff --git a/Modules/Learning/LearningBase/include/otbMachineLearningModel.h b/Modules/Learning/LearningBase/include/otbMachineLearningModel.h
index c5fb59f28c9fa5931351921309b5ac35cbf46b48..552880cb9a83a4e43b7e29ae75689613633e5ef0 100644
--- a/Modules/Learning/LearningBase/include/otbMachineLearningModel.h
+++ b/Modules/Learning/LearningBase/include/otbMachineLearningModel.h
@@ -22,8 +22,8 @@
#define otbMachineLearningModel_h
#include "itkObject.h"
-#include "itkVariableLengthVector.h"
#include "itkListSample.h"
+#include "otbMachineLearningModelTraits.h"
namespace otb
{
@@ -66,6 +66,7 @@ namespace otb
*
* \ingroup OTBLearningBase
*/
+
template <class TInputValue, class TTargetValue, class TConfidenceValue = double >
class ITK_EXPORT MachineLearningModel
: public itk::Object
@@ -81,22 +82,22 @@ public:
/**\name Input related typedefs */
//@{
- typedef TInputValue InputValueType;
- typedef itk::VariableLengthVector<InputValueType> InputSampleType;
- typedef itk::Statistics::ListSample<InputSampleType> InputListSampleType;
+ typedef typename MLMSampleTraits<TInputValue>::ValueType InputValueType;
+ typedef typename MLMSampleTraits<TInputValue>::SampleType InputSampleType;
+ typedef itk::Statistics::ListSample<InputSampleType> InputListSampleType;
//@}
/**\name Target related typedefs */
//@{
- typedef TTargetValue TargetValueType;
- typedef itk::FixedArray<TargetValueType,1> TargetSampleType;
- typedef itk::Statistics::ListSample<TargetSampleType> TargetListSampleType;
+ typedef typename MLMTargetTraits<TTargetValue>::ValueType TargetValueType;
+ typedef typename MLMTargetTraits<TTargetValue>::SampleType TargetSampleType;
+ typedef itk::Statistics::ListSample<TargetSampleType> TargetListSampleType;
//@}
/**\name Confidence value typedef */
- typedef TConfidenceValue ConfidenceValueType;
- typedef itk::FixedArray<ConfidenceValueType,1> ConfidenceSampleType;
- typedef itk::Statistics::ListSample<ConfidenceSampleType> ConfidenceListSampleType;
+ typedef typename MLMTargetTraits<TConfidenceValue>::ValueType ConfidenceValueType;
+ typedef typename MLMTargetTraits<TConfidenceValue>::SampleType ConfidenceSampleType;
+ typedef itk::Statistics::ListSample<ConfidenceSampleType> ConfidenceListSampleType;
/**\name Standard macros */
//@{
diff --git a/Modules/Learning/LearningBase/include/otbMachineLearningModelTraits.h b/Modules/Learning/LearningBase/include/otbMachineLearningModelTraits.h
new file mode 100644
index 0000000000000000000000000000000000000000..e9bc4cec29b9b3b45891e0265d63009bff34b76e
--- /dev/null
+++ b/Modules/Learning/LearningBase/include/otbMachineLearningModelTraits.h
@@ -0,0 +1,104 @@
+/*
+ * Copyright (C) 2005-2017 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 otbMachineLearningModelTraits_h
+#define otbMachineLearningModelTraits_h
+
+
+#include "itkVariableLengthVector.h"
+#include "itkFixedArray.h"
+#include "itkIsNumber.h"
+#include "itkMetaProgrammingLibrary.h"
+
+namespace otb
+{
+
+/**
+ * This is the struct defining the sample implementation for
+ * MachineLearningModel. It offers two type definitions: SampleType
+ * and ValueType.
+ *
+ * \tparam TInput : input sample type (can be either a scalar type or
+ * a VariableLenghtVector
+ * \tparam isNumber either TrueType or FalseType for partial
+ * specialization
+
+ */
+template <typename TInput, typename isNumber> struct MLMSampleTraitsImpl;
+
+
+/// \cond SPECIALIZATION_IMPLEMENTATION
+// For Numbers
+template <typename TInput> struct MLMSampleTraitsImpl<TInput, itk::mpl::TrueType> {
+ typedef TInput ValueType;
+ typedef itk::VariableLengthVector<TInput> SampleType;
+};
+
+// For Vectors
+template <typename TInput> struct MLMSampleTraitsImpl<TInput, itk::mpl::FalseType> {
+ typedef typename TInput::ValueType ValueType;
+ typedef TInput SampleType;
+};
+/// \endcond
+
+/**
+ * Simplified implementation of SampleTraits using MLMSampleTraitsImpl
+ */
+template <typename TInput> using MLMSampleTraits = MLMSampleTraitsImpl< TInput, typename itk::mpl::IsNumber<TInput>::Type >;
+
+
+/**
+ * This is the struct defining the sample implementation for
+ * MachineLearningModel. It offers two type definitions: TargetType
+ * and ValueType.
+ *
+ * \tparam TInput : input sample type (can be either a scalar type or
+ * a VariableLenghtVector or a FixedArray
+ * \tparam isNumber either TrueType or FalseType for partial
+ * specialization
+
+ */
+template <typename TInput, typename isNumber> struct MLMTargetTraitsImpl;
+
+
+/// \cond SPECIALIZATION_IMPLEMENTATION
+// For Numbers
+template <typename TInput> struct MLMTargetTraitsImpl<TInput, itk::mpl::TrueType> {
+ typedef TInput ValueType;
+ typedef itk::FixedArray<TInput,1> SampleType;
+};
+
+// For Vectors
+template <typename TInput> struct MLMTargetTraitsImpl<TInput, itk::mpl::FalseType> {
+ typedef typename TInput::ValueType ValueType;
+ typedef TInput SampleType;
+};
+/// \endcond
+
+/**
+ * Simplified implementation of TargetTraits using MLMTargetTraitsImpl
+ */
+template <typename TInput> using MLMTargetTraits = MLMTargetTraitsImpl< TInput, typename itk::mpl::IsNumber<TInput>::Type >;
+
+
+} // End namespace otb
+
+#endif
diff --git a/Modules/Learning/LearningBase/test/CMakeLists.txt b/Modules/Learning/LearningBase/test/CMakeLists.txt
index 74a67d44dddd939201c134f28be152281b85a7a2..d1d16c3e65801e606c6e6903538b65264a4483a6 100644
--- a/Modules/Learning/LearningBase/test/CMakeLists.txt
+++ b/Modules/Learning/LearningBase/test/CMakeLists.txt
@@ -29,6 +29,7 @@ otbDecisionTreeWithRealValues.cxx
otbSEMClassifierNew.cxx
otbDecisionTreeNew.cxx
otbKMeansImageClassificationFilterNew.cxx
+otbMachineLearningModelTemplates.cxx
)
add_executable(otbLearningBaseTestDriver ${OTBLearningBaseTests})
diff --git a/Modules/Learning/LearningBase/test/otbMachineLearningModelTemplates.cxx b/Modules/Learning/LearningBase/test/otbMachineLearningModelTemplates.cxx
new file mode 100644
index 0000000000000000000000000000000000000000..96d35e014394d6b0d6836a90ddcbf3a2303db4bf
--- /dev/null
+++ b/Modules/Learning/LearningBase/test/otbMachineLearningModelTemplates.cxx
@@ -0,0 +1,40 @@
+/*
+ * Copyright (C) 2005-2017 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.
+ */
+
+#include <otbMachineLearningModel.h>
+
+typedef otb::MachineLearningModel<float,short> MachineLearningModelType1;
+typedef MachineLearningModelType1::InputValueType InputValueType1;
+typedef MachineLearningModelType1::InputSampleType InputSampleType1;
+typedef MachineLearningModelType1::InputListSampleType InputListSampleType1;
+typedef MachineLearningModelType1::TargetValueType TargetValueType1;
+typedef MachineLearningModelType1::TargetSampleType TargetSampleType1;
+typedef MachineLearningModelType1::TargetListSampleType TargetListSampleType1;
+
+typedef otb::MachineLearningModel<float,itk::VariableLengthVector<double> > MachineLearningModelType2;
+typedef MachineLearningModelType2::InputValueType InputValueType2;
+typedef MachineLearningModelType2::InputSampleType InputSampleType2;
+typedef MachineLearningModelType2::InputListSampleType InputListSampleType2;
+typedef MachineLearningModelType2::TargetValueType TargetValueType2;
+typedef MachineLearningModelType2::TargetSampleType TargetSampleType2;
+typedef MachineLearningModelType2::TargetListSampleType TargetListSampleType2;
+
+
+