From f3dbbd3804a428b020f94853ca9630009c372bdb Mon Sep 17 00:00:00 2001
From: Guillaume Pasero <guillaume.pasero@c-s.fr>
Date: Wed, 13 Dec 2017 18:52:22 +0100
Subject: [PATCH] ENH: no support for tied autoencoder yet
---
.../app/otbTrainDimensionalityReduction.cxx | 5 ++--
...imensionalityReductionTrainAutoencoder.txx | 23 +------------------
2 files changed, 3 insertions(+), 25 deletions(-)
diff --git a/Modules/Applications/AppDimensionalityReduction/app/otbTrainDimensionalityReduction.cxx b/Modules/Applications/AppDimensionalityReduction/app/otbTrainDimensionalityReduction.cxx
index fa3dd7bdcb..df735345a1 100644
--- a/Modules/Applications/AppDimensionalityReduction/app/otbTrainDimensionalityReduction.cxx
+++ b/Modules/Applications/AppDimensionalityReduction/app/otbTrainDimensionalityReduction.cxx
@@ -73,7 +73,7 @@ private:
SetName("TrainDimensionalityReduction");
SetDescription("Trainer for the dimensionality reduction algorithms used in"
" the ImageDimensionalityReduction and VectorDimensionalityReduction applications.");
-
+
AddParameter(ParameterType_Group, "io", "Input and output data");
SetParameterDescription("io", "This group of parameters allows setting input and output data.");
@@ -83,8 +83,7 @@ private:
AddParameter(ParameterType_OutputFilename, "io.out", "Output model");
SetParameterDescription("io.out", "Output file containing the estimated model (.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/Modules/Applications/AppDimensionalityReduction/include/otbDimensionalityReductionTrainAutoencoder.txx b/Modules/Applications/AppDimensionalityReduction/include/otbDimensionalityReductionTrainAutoencoder.txx
index 6f073353f3..f474167e38 100644
--- a/Modules/Applications/AppDimensionalityReduction/include/otbDimensionalityReductionTrainAutoencoder.txx
+++ b/Modules/Applications/AppDimensionalityReduction/include/otbDimensionalityReductionTrainAutoencoder.txx
@@ -33,22 +33,11 @@ void
TrainDimensionalityReductionApplicationBase<TInputValue,TOutputValue>
::InitAutoencoderParams()
{
- AddChoice("algorithm.tiedautoencoder", "Shark Tied Autoencoder");
AddChoice("algorithm.autoencoder", "Shark Autoencoder");
SetParameterDescription("algorithm.autoencoder",
"This group of parameters allows setting Shark autoencoder parameters. "
);
- //Tied Autoencoder
- AddParameter(ParameterType_Choice, "algorithm.autoencoder.istied",
- "tied weighth <tied/untied>");
- SetParameterDescription(
- "algorithm.autoencoder.istied",
- "Parameter that determine if the weights are tied or not <tied/untied>");
-
- AddChoice("algorithm.autoencoder.istied.yes","Tied weigths");
- AddChoice("algorithm.autoencoder.istied.no","Untied weights");
-
//Number Of Iterations
AddParameter(ParameterType_Int, "algorithm.autoencoder.nbiter",
"Maximum number of iterations during training");
@@ -116,17 +105,7 @@ TrainDimensionalityReductionApplicationBase<TInputValue,TOutputValue>
{
typedef shark::LogisticNeuron NeuronType;
typedef otb::AutoencoderModel<InputValueType, NeuronType> AutoencoderModelType;
- std::string TiedWeigth = GetParameterString("algorithm.autoencoder.istied");
- std::cout << TiedWeigth << std::endl;
-
- if(TiedWeigth == "no")
- {
- TrainAutoencoder<AutoencoderModelType>(trainingListSample,modelPath);
- }
- if(TiedWeigth != "yes" && TiedWeigth != "no")
- {
- std::cerr << "istied : invalid choice <yes/no>" << std::endl;
- }
+ TrainAutoencoder<AutoencoderModelType>(trainingListSample,modelPath);
}
template <class TInputValue, class TOutputValue>
--
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