ENH: train SVM classifier sample.edg non mandatory new option.

Applications/Classification/otbTrainSVMImagesClassifier.cxx

@@ -170,9 +170,9 @@ private:
     SetDefaultParameterInt("sample.mv", -1);
     SetParameterDescription("sample.mv", "Maximum size of the validation sample list (default = -1)");
 
-    // AddParameter(ParameterType_Int, "sample.b", "Balance and grow the training set");
-    // SetParameterDescription("sample.b", "Balance and grow the training set.");
-    // MandatoryOff("sample.b");
+    AddParameter(ParameterType_Empty, "sample.edg", "On edge pixel inclusion");
+    SetParameterDescription("sample.edg", "Take pixels on polygon edge into consideration when building training and validation samples.");
+    MandatoryOff("sample.edg");
         
     AddParameter(ParameterType_Float, "sample.vtr", "training and validation sample ratio");
     SetParameterDescription("sample.vtr",
@@ -238,6 +238,8 @@ private:
     FloatVectorImageListType* imageList = GetParameterImageList("io.il");
     VectorDataListType* vectorDataList = GetParameterVectorDataList("io.vd");
 
+    vdreproj = VectorDataReprojectionType::New();
+
     //Iterate over all input images
     for (unsigned int imgIndex = 0; imgIndex < imageList->Size(); ++imgIndex)
       {
@@ -253,7 +255,6 @@ private:
       VectorDataType::Pointer vectorData = vectorDataList->GetNthElement(imgIndex);
       vectorData->Update();
 
-      VectorDataReprojectionType::Pointer vdreproj = VectorDataReprojectionType::New();
       vdreproj->SetInputImage(image);
       vdreproj->SetInput(vectorData);
       vdreproj->SetUseOutputSpacingAndOriginFromImage(false);
@@ -287,8 +288,7 @@ private:
       //Sample list generator
       ListSampleGeneratorType::Pointer sampleGenerator = ListSampleGeneratorType::New();
 
-      //m_sampleGenerator = sampleGenerator;
-      //Set inputs of the sample generator
+
       sampleGenerator->SetInput(image);
       sampleGenerator->SetInputVectorData(vdreproj->GetOutput());
 
@@ -297,6 +297,12 @@ private:
       sampleGenerator->SetMaxValidationSize(GetParameterInt("sample.mv"));
       sampleGenerator->SetValidationTrainingProportion(GetParameterFloat("sample.vtr"));
 
+     // take pixel located on polygon edge into consideration
+     if (IsParameterEnabled("sample.edg"))
+     {
+       sampleGenerator->SetPolygonEdgeInclusion(true);
+     }
+
       sampleGenerator->Update();
 
       //Concatenate training and validation samples from the image
@@ -467,7 +473,7 @@ private:
 
 
   }
-
+  VectorDataReprojectionType::Pointer vdreproj;
 };
 
 }

Code/Learning/otbListSampleGenerator.h

@@ -99,6 +99,8 @@ public:
   /** Accessors */
   itkGetConstMacro(MaxTrainingSize, long int);
   itkSetMacro(MaxTrainingSize, long int);
+  itkGetConstMacro(PolygonEdgeInclusion, bool);
+  itkSetMacro(PolygonEdgeInclusion, bool);
   itkGetConstMacro(MaxValidationSize, long int);
   itkSetMacro(MaxValidationSize, long int);
   itkGetConstMacro(ValidationTrainingProportion, double);
@@ -153,6 +155,9 @@ private:
   double   m_ValidationTrainingProportion; // proportion of training vs validation
                                            // (0.0 = all training, 1.0 = all validation)
 
+  bool           m_PolygonEdgeInclusion; // if true take into consideration pixel which are on polygon edge
+                                           //  useful, when dealing with small polygon area (1 or two pixels)
+                                           // false by default
   unsigned short m_NumberOfClasses;
   std::string    m_ClassKey;
   double         m_ClassMinSize;

Code/Learning/otbListSampleGenerator.txx

@@ -64,6 +64,7 @@ ListSampleGenerator<TImage, TVectorData>
   m_MaxTrainingSize(-1),
   m_MaxValidationSize(-1),
   m_ValidationTrainingProportion(0.0),
+  m_PolygonEdgeInclusion(false),
   m_NumberOfClasses(0),
   m_ClassKey("Class"),
   m_ClassMinSize(-1)
@@ -183,12 +184,9 @@ ListSampleGenerator<TImage, TVectorData>
         otb::TransformPhysicalRegionToIndexRegion(itVector.Get()->GetPolygonExteriorRing()->GetBoundingRegion(),
                                                   image.GetPointer());
 
-      //std::cout << "Image region from polygon:\n" << polygonRegion <<  std::endl;
-      //std::cout << "Image largest possible region:\n" << image->GetLargestPossibleRegion() <<  std::endl;
       image->SetRequestedRegion(polygonRegion);
       image->PropagateRequestedRegion();
       image->UpdateOutputData();
-      //std::cout << "Image region requested:\n" << image->GetRequestedRegion() <<  std::endl;
 
       typedef itk::ImageRegionConstIteratorWithIndex<ImageType> IteratorType;
       IteratorType it(image, polygonRegion);
@@ -197,8 +195,8 @@ ListSampleGenerator<TImage, TVectorData>
         {
         itk::ContinuousIndex<double, 2> point;
         image->TransformIndexToPhysicalPoint(it.GetIndex(), point);
-        //std::cout << it.GetIndex() << " -> " << point << std::endl;
-        if (itVector.Get()->GetPolygonExteriorRing()->IsInside(point))
+        if (itVector.Get()->GetPolygonExteriorRing()->IsInside(point) ||
+             (itVector.Get()->GetPolygonExteriorRing()->IsOnEdge(point) && (this->GetPolygonEdgeInclusion())))
           {
           double randomValue = m_RandomGenerator->GetUniformVariate(0.0, 1.0);
           if (randomValue < m_ClassesProbTraining[itVector.Get()->GetFieldAsInt(m_ClassKey)])