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Gaetano Raffaele authored6005eb7d
/*=========================================================================
Copyright (c) 2018-2019 IRSTEA
Copyright (c) 2020-2021 INRAE
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#include "itkFixedArray.h"
#include "itkObjectFactory.h"
// Elevation handler
#include "otbWrapperElevationParametersHandler.h"
#include "otbWrapperApplicationFactory.h"
#include "otbWrapperCompositeApplication.h"
// Application engine
#include "otbStandardFilterWatcher.h"
#include "itkFixedArray.h"
// TF (used to get the environment variable for the number of inputs)
#include "otbTensorflowCommon.h"
namespace otb
{
namespace Wrapper
{
class ImageClassifierFromDeepFeatures : public CompositeApplication
{
public:
/** Standard class typedefs. */
typedef ImageClassifierFromDeepFeatures Self;
typedef Application Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
/** Standard macro */
itkNewMacro(Self);
itkTypeMacro(ImageClassifierFromDeepFeatures, otb::Wrapper::CompositeApplication);
private:
//
// Add an input source, which includes:
// -an input image list
// -an input patchsize (dimensions of samples)
//
void AddAnInputImage(int inputNumber = 0)
{
inputNumber++;
// Create keys and descriptions
std::stringstream ss_key_group, ss_desc_group;
ss_key_group << "source" << inputNumber;
ss_desc_group << "Parameters for source " << inputNumber;
// Populate group
ShareParameter(ss_key_group.str(), "tfmodel." + ss_key_group.str(), ss_desc_group.str());
}
void DoInit()
{
SetName("ImageClassifierFromDeepFeatures");
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SetDescription("Classify image using features from a deep net and an OTB machine learning classification model");
// Documentation
SetDocLongDescription("See ImageClassifier application");
SetDocLimitations("None");
SetDocAuthors("Remi Cresson");
SetDocSeeAlso(" ");
AddDocTag(Tags::Learning);
ClearApplications();
// Add applications
AddApplication("ImageClassifier", "classif", "Images classifier" );
AddApplication("TensorflowModelServe", "tfmodel", "Serve the TF model" );
// Model shared parameters
AddAnInputImage();
for (int i = 1; i < tf::GetNumberOfSources() ; i++)
{
AddAnInputImage(i);
}
ShareParameter("deepmodel", "tfmodel.model",
"Deep net model parameters", "Deep net model parameters");
ShareParameter("output", "tfmodel.output",
"Deep net outputs parameters",
"Deep net outputs parameters");
ShareParameter("optim", "tfmodel.optim",
"This group of parameters allows optimization of processing time",
"This group of parameters allows optimization of processing time");
// Classify shared parameters
ShareParameter("model" , "classif.model" , "Model file" , "Model file" );
ShareParameter("imstat" , "classif.imstat" , "Statistics file" , "Statistics file" );
ShareParameter("nodatalabel", "classif.nodatalabel", "Label mask value" , "Label mask value" );
ShareParameter("out" , "classif.out" , "Output image" , "Output image" );
ShareParameter("confmap" , "classif.confmap" , "Confidence map image", "Confidence map image");
ShareParameter("ram" , "classif.ram" , "Ram" , "Ram" );
}
void DoUpdateParameters()
{
UpdateInternalParameters("classif");
}
void DoExecute()
{
ExecuteInternal("tfmodel");
GetInternalApplication("classif")->SetParameterInputImage("in", GetInternalApplication("tfmodel")->GetParameterOutputImage("out"));
UpdateInternalParameters("classif");
ExecuteInternal("classif");
}
};
} // namespace Wrapper
} // namespace otb
OTB_APPLICATION_EXPORT( otb::Wrapper::ImageClassifierFromDeepFeatures )