From 47fc69c1c4c20c981b80769ca36dd23898360175 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?C=C3=A9dric=20Traizet?= <traizetc@cesbio.cnes.fr>
Date: Fri, 30 Jun 2017 09:57:49 +0200
Subject: [PATCH] BUG : SOMModel now herits from
MachineLearningModel<TInput,...> instead of
MachineLearningModel<itk:variablelengthvector<TInput>,...>
---
app/cbDimensionalityReductionTrainer.cxx | 3 ++-
app/cbDimensionalityReductionVector.cxx | 19 +++++++++++++-
include/cbLearningApplicationBaseDR.h | 8 +++---
include/cbLearningApplicationBaseDR.txx | 32 ++++++++++++------------
4 files changed, 40 insertions(+), 22 deletions(-)
diff --git a/app/cbDimensionalityReductionTrainer.cxx b/app/cbDimensionalityReductionTrainer.cxx
index e83231428d..aee6fb3ed9 100644
--- a/app/cbDimensionalityReductionTrainer.cxx
+++ b/app/cbDimensionalityReductionTrainer.cxx
@@ -60,7 +60,8 @@ private:
AddParameter(ParameterType_OutputFilename, "io.out", "Output model");
SetParameterDescription("io.out", "Output file containing the model estimated (.txt format).");
-
+
+
AddParameter(ParameterType_InputFilename, "io.stats", "Input XML image statistics file");
MandatoryOff("io.stats");
SetParameterDescription("io.stats", "XML file containing mean and variance of each feature.");
diff --git a/app/cbDimensionalityReductionVector.cxx b/app/cbDimensionalityReductionVector.cxx
index 485f248b64..dbfd87d39a 100644
--- a/app/cbDimensionalityReductionVector.cxx
+++ b/app/cbDimensionalityReductionVector.cxx
@@ -116,6 +116,11 @@ class CbDimensionalityReductionVector : public Application
SetParameterDescription("pcadim","This optional parameter can be set to reduce the number of eignevectors used in the PCA model file."); //
MandatoryOff("pcadim");
+ AddParameter(ParameterType_String, "mode", "Writting mode"); //
+ SetParameterString("mode","overwrite", false);
+ SetParameterDescription("mode","This parameter determines if the output file is overwritten or updated [overwrite/update]"); //
+
+
// Doc example parameter settings
SetDocExampleParameterValue("in", "vectorData.shp");
SetDocExampleParameterValue("instat", "meanVar.xml");
@@ -262,7 +267,19 @@ class CbDimensionalityReductionVector : public Application
if (IsParameterEnabled("out") && HasValue("out"))
{
// Create new OGRDataSource
- output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Overwrite);
+ if (GetParameterString("mode")=="overwrite")
+ {
+ output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Overwrite);
+ }
+ else if (GetParameterString("mode")=="update")
+ {
+ output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Update_LayerCreateOnly );
+ }
+ else
+ {
+ otbAppLogFATAL(<< "Error when creating the output file" << GetParameterString("mode") << " : unsupported writting mode type [update/overwrite]");
+ }
+
otb::ogr::Layer newLayer = output->CreateLayer(GetParameterString("out"),
const_cast<OGRSpatialReference*>(layer.GetSpatialRef()),
layer.GetGeomType());
diff --git a/include/cbLearningApplicationBaseDR.h b/include/cbLearningApplicationBaseDR.h
index 9d0a6c6908..94c62d1b43 100644
--- a/include/cbLearningApplicationBaseDR.h
+++ b/include/cbLearningApplicationBaseDR.h
@@ -87,16 +87,16 @@ public:
// Dimensionality reduction models
- typedef SOMMap<itk::VariableLengthVector<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<itk::VariableLengthVector<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<itk::VariableLengthVector<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<itk::VariableLengthVector<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/cbLearningApplicationBaseDR.txx b/include/cbLearningApplicationBaseDR.txx
index a42ad73857..6e1635e24d 100644
--- a/include/cbLearningApplicationBaseDR.txx
+++ b/include/cbLearningApplicationBaseDR.txx
@@ -45,7 +45,7 @@ cbLearningApplicationBaseDR<TInputValue,TOutputValue>
AddDocTag(Tags::Learning);
// main choice parameter that will contain all dimensionality reduction options
- AddParameter(ParameterType_Choice, "model", "moddel to use for the training");
+ AddParameter(ParameterType_Choice, "model", "model to use for the training");
SetParameterDescription("model", "Choice of the dimensionality reduction model to use for the training.");
@@ -83,28 +83,28 @@ cbLearningApplicationBaseDR<TInputValue,TOutputValue>
if(modelName == "autoencoder")
{
- #ifdef OTB_USE_SHARK
- BeforeTrainAutoencoder(trainingListSample,modelPath);
- #else
- otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
- #endif
+ #ifdef OTB_USE_SHARK
+ BeforeTrainAutoencoder(trainingListSample,modelPath);
+ #else
+ otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
+ #endif
}
if(modelName == "tiedautoencoder")
{
- #ifdef OTB_USE_SHARK
- TrainAutoencoder<TiedAutoencoderModelType>(trainingListSample,modelPath);
- #else
- otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
- #endif
+ #ifdef OTB_USE_SHARK
+ TrainAutoencoder<TiedAutoencoderModelType>(trainingListSample,modelPath);
+ #else
+ otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
+ #endif
}
if(modelName == "pca")
{
- #ifdef OTB_USE_SHARK
- TrainPCA(trainingListSample,modelPath);
- #else
- otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
- #endif
+ #ifdef OTB_USE_SHARK
+ TrainPCA(trainingListSample,modelPath);
+ #else
+ otbAppLogFATAL("Module SharkLearning is not installed. You should consider turning OTB_USE_SHARK on during cmake configuration.");
+ #endif
}
}
--
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