diff --git a/app/cbDimensionalityReductionVector.cxx b/app/cbDimensionalityReductionVector.cxx
index dbfd87d39af701a0010bea61b7c322175bd2b5ec..ce4e1fa1ca35437a92762a8bab2297faba3fe3b3 100644
--- a/app/cbDimensionalityReductionVector.cxx
+++ b/app/cbDimensionalityReductionVector.cxx
@@ -237,7 +237,6 @@ class CbDimensionalityReductionVector : public Application
{
int dimension = GetParameterInt("pcadim");
m_Model->SetDimension(dimension );
- std::cout << "yo" << std::endl;
}
@@ -270,26 +269,41 @@ class CbDimensionalityReductionVector : public Application
if (GetParameterString("mode")=="overwrite")
{
output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Overwrite);
+ otb::ogr::Layer newLayer = output->CreateLayer(GetParameterString("out"),
+ const_cast<OGRSpatialReference*>(layer.GetSpatialRef()),
+ layer.GetGeomType());
+ // Copy existing fields
+ OGRFeatureDefn &inLayerDefn = layer.GetLayerDefn();
+ for (int k=0 ; k<inLayerDefn.GetFieldCount()-nbBands ; k++) // we don't copy the original bands
+ {
+ OGRFieldDefn fieldDefn(inLayerDefn.GetFieldDefn(k));
+ newLayer.CreateField(fieldDefn);
+ }
}
else if (GetParameterString("mode")=="update")
{
- output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Update_LayerCreateOnly );
+ //output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Update_LayerCreateOnly);
+ // Update mode
+ otb::ogr::DataSource::Pointer source_output = otb::ogr::DataSource::New(GetParameterString("out"), otb::ogr::DataSource::Modes::Read);
+ layer = source_output->GetLayer(0);
+ updateMode = true;
+ otbAppLogINFO("Update input vector data.");
+
+ // fill temporary buffer for the transfer
+ otb::ogr::Layer inputLayer = layer;
+ layer = buffer->CopyLayer(inputLayer, std::string("Buffer"));
+ // close input data source
+ source_output->Clear();
+ // Re-open input data source in update mode
+ output = otb::ogr::DataSource::New(GetParameterString("out"), otb::ogr::DataSource::Modes::Update_LayerUpdate);
+
}
else
{
- otbAppLogFATAL(<< "Error when creating the output file" << GetParameterString("mode") << " : unsupported writting mode type [update/overwrite]");
+ otbAppLogFATAL(<< "Error when creating the output file" << GetParameterString("mode") << " : unsupported writting mode type");
}
- otb::ogr::Layer newLayer = output->CreateLayer(GetParameterString("out"),
- const_cast<OGRSpatialReference*>(layer.GetSpatialRef()),
- layer.GetGeomType());
- // Copy existing fields
- OGRFeatureDefn &inLayerDefn = layer.GetLayerDefn();
- for (int k=0 ; k<inLayerDefn.GetFieldCount()-nbBands ; k++) // we don't copy the original bands
- {
- OGRFieldDefn fieldDefn(inLayerDefn.GetFieldDefn(k));
- newLayer.CreateField(fieldDefn);
- }
+
}
/*
@@ -309,6 +323,7 @@ class CbDimensionalityReductionVector : public Application
otb::ogr::Layer outLayer = output->GetLayer(0);
+
OGRErr errStart = outLayer.ogr().StartTransaction();
if (errStart != OGRERR_NONE)
@@ -337,10 +352,11 @@ class CbDimensionalityReductionVector : public Application
}
// Add an ID field. (The ID already contained in the layer refers to the polygon)
+ /*
OGRFieldDefn IDField("ID_point", OFTInteger);
ogr::FieldDefn IDFieldDef(IDField);
outLayer.CreateField(IDFieldDef);
-
+ */
// Fill output layer
unsigned int count=0;
@@ -351,12 +367,18 @@ class CbDimensionalityReductionVector : public Application
for( ; it!=itEnd ; ++it, ++count)
{
ogr::Feature dstFeature(outLayer.GetLayerDefn());
- dstFeature.SetFrom( *it , TRUE);
- dstFeature.SetFID(it->GetFID());
+ /*
+ if (GetParameterString("mode")=="overwrite")
+ {*/
+ dstFeature.SetFrom( *it , TRUE);
+ dstFeature.SetFID(it->GetFID());
+ //}
+
+
for (std::size_t i=0; i<classfieldname.size(); ++i){
dstFeature[classfieldname[i]].SetValue<ValueType>(target->GetMeasurementVector(count)[i]);
}
- dstFeature["ID_point"].SetValue<int>(id);
+ //dstFeature["ID_point"].SetValue<int>(id);
if (updateMode)
{
outLayer.SetFeature(dstFeature);
diff --git a/include/SOMModel.h b/include/SOMModel.h
index 88209ed24e0efc5df0c06cd8a3fa7b571e2cdd83..a5752ac5c9c5797a865980bea98a71f2842bdc16 100644
--- a/include/SOMModel.h
+++ b/include/SOMModel.h
@@ -46,6 +46,7 @@ public:
typedef SOMMap<itk::VariableLengthVector<TInputValue>,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, MapDimension> MapType;
typedef typename MapType::SizeType SizeType;
typedef typename MapType::SpacingType SpacingType;
+ //typedef otb::SOM<InputListSampleType, MapType> EstimatorType;
typedef otb::SOM<InputListSampleType, MapType> EstimatorType;
typedef Functor::CzihoSOMLearningBehaviorFunctor SOMLearningBehaviorFunctorType;
diff --git a/include/SOMModel.txx b/include/SOMModel.txx
index 7afbd6f501935b86af55569461e561b733b367d9..b0b2229ac75600ae0ac4661fb016183a4b7c616e 100644
--- a/include/SOMModel.txx
+++ b/include/SOMModel.txx
@@ -22,7 +22,7 @@ namespace otb
template <class TInputValue, unsigned int MapDimension>
SOMModel<TInputValue, MapDimension>::SOMModel()
{
- //m_Dimension = typename MapType::ImageDimension;
+ this->m_Dimension = MapType::ImageDimension;
}
@@ -46,12 +46,9 @@ void SOMModel<TInputValue, MapDimension>::Train()
estimator->SetBetaEnd(m_BetaEnd);
estimator->SetMaxWeight(m_MaxWeight);
//AddProcess(estimator,"Learning");
-
estimator->Update();
-
m_SOMMap = estimator->GetOutput();
- std::cout << "dr of the first sample : " << m_SOMMap->GetWinner(m_ListSample->GetMeasurementVector(0)) << std::endl;
-}
+ }
@@ -100,7 +97,7 @@ void SOMModel<TInputValue, MapDimension>::Save(const std::string & filename, con
inputIterator.GoToBegin();
std::ofstream ofs(filename, std::ios::binary);
binary_write_string(ofs,"som");
- binary_write(ofs,static_cast<int>(MapDimension));
+ binary_write(ofs,static_cast<unsigned int>(MapDimension));
SizeType size = m_SOMMap->GetLargestPossibleRegion().GetSize() ;
for (size_t i=0;i<MapDimension;i++){
binary_write(ofs,size[i]);
@@ -129,12 +126,10 @@ void SOMModel<TInputValue, MapDimension>::Load(const std::string & filename, con
binary_read(ifs,s[i]);
}
std::string modelType(s);
-
/** Read the dimension of the map (should be equal to MapDimension) */
- int dimension;
+ unsigned int dimension;
binary_read(ifs,dimension);
-
if (modelType != "som" || dimension != MapDimension){
itkExceptionMacro(<< "Error opening " << filename.c_str() );
}
@@ -146,10 +141,8 @@ void SOMModel<TInputValue, MapDimension>::Load(const std::string & filename, con
binary_read(ifs,size[i]);
index[i]=0;
}
-
unsigned int numberOfElements;
binary_read(ifs,numberOfElements);
-
m_SOMMap = MapType::New();
typename MapType::RegionType region;
region.SetSize( size );
@@ -165,13 +158,15 @@ void SOMModel<TInputValue, MapDimension>::Load(const std::string & filename, con
InputSampleType vect(numberOfElements);
for (int i=0 ; i<numberOfElements; i++)
{
- binary_read(ifs,vect[i]);
+ float v; // InputValue type is not the same during training anddimredvector.
+ binary_read(ifs,v);
+ vect[i] = static_cast<double>(v);
}
outputIterator.Set(vect);
++outputIterator;
}
-
ifs.close();
+
this->m_Dimension = MapType::ImageDimension;
}
@@ -180,15 +175,14 @@ template <class TInputValue, unsigned int MapDimension>
typename SOMModel<TInputValue, MapDimension>::TargetSampleType
SOMModel<TInputValue, MapDimension>::DoPredict(const InputSampleType & value, ConfidenceValueType * quality) const
{
- unsigned int dimension =MapType::ImageDimension;
TargetSampleType target;
- target.SetSize(dimension);
+ target.SetSize(this->m_Dimension);
auto winner =m_SOMMap->GetWinner(value);
- for (int i=0; i< dimension ;i++) {
+ for (int i=0; i< this->m_Dimension ;i++) {
target[i] = winner.GetElement(i);
}
-
+
return target;
}
diff --git a/include/cbLearningApplicationBaseDR.h b/include/cbLearningApplicationBaseDR.h
index 94c62d1b433a06fa6189742868b75e2e5f62d073..3d90432fa95899e21de67a0695f6067dc6d81502 100644
--- a/include/cbLearningApplicationBaseDR.h
+++ b/include/cbLearningApplicationBaseDR.h
@@ -87,16 +87,16 @@ public:
// Dimensionality reduction models
- typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 2> Map2DType;
+ //typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 2> Map2DType;
typedef otb::SOMModel<InputValueType, 2> SOM2DModelType;
- typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 3> Map3DType;
+ //typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 3> Map3DType;
typedef otb::SOMModel<InputValueType, 3> SOM3DModelType;
- typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 4> Map4DType;
+ //typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 4> Map4DType;
typedef otb::SOMModel<InputValueType, 4> SOM4DModelType;
- typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 5> Map5DType;
+ //typedef SOMMap<TInputValue,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, 5> Map5DType;
typedef otb::SOMModel<InputValueType, 5> SOM5DModelType;
diff --git a/include/cbTrainSOM.txx b/include/cbTrainSOM.txx
index 9ac28dd9060d6abd89f1d6d8d99a40d4d16feb88..538ccea03c4d6895b0b12bff9fda3edc596b8f10 100644
--- a/include/cbTrainSOM.txx
+++ b/include/cbTrainSOM.txx
@@ -117,6 +117,7 @@ void cbLearningApplicationBaseDR<TInputValue,TOutputValue>
using TemplateEstimatorType = typename somchoice::EstimatorType;
typename somchoice::Pointer dimredTrainer = somchoice::New();
unsigned int dim = dimredTrainer->GetDimension();
+ std::cout << dim << std::endl;
dimredTrainer->SetNumberOfIterations(GetParameterInt("model.som.ni"));
dimredTrainer->SetBetaInit(GetParameterFloat("model.som.bi"));
dimredTrainer->SetBetaEnd(GetParameterFloat("model.som.bf"));