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otbImageClassifierFromDeepFeatures.cxx 4.12 KiB
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/*=========================================================================
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     Copyright (c) 2018-2019 IRSTEA
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     Copyright (c) 2020-2021 INRAE
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     This software is distributed WITHOUT ANY WARRANTY; without even
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     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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     PURPOSE.  See the above copyright notices for more information.
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=========================================================================*/
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#include "itkFixedArray.h"
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#include "itkObjectFactory.h"
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// Elevation handler
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#include "otbWrapperElevationParametersHandler.h"
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#include "otbWrapperApplicationFactory.h"
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#include "otbWrapperCompositeApplication.h"
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// Application engine
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#include "otbStandardFilterWatcher.h"
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#include "itkFixedArray.h"
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// TF (used to get the environment variable for the number of inputs)
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#include "otbTensorflowCommon.h"
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namespace otb
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{
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namespace Wrapper
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{
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class ImageClassifierFromDeepFeatures : public CompositeApplication
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{
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public:
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  /** Standard class typedefs. */
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  typedef ImageClassifierFromDeepFeatures              Self;
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  typedef Application                         Superclass;
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  typedef itk::SmartPointer<Self>             Pointer;
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  typedef itk::SmartPointer<const Self>       ConstPointer;
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  /** Standard macro */
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  itkNewMacro(Self);
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  itkTypeMacro(ImageClassifierFromDeepFeatures, otb::Wrapper::CompositeApplication);
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private:
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  //
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  // Add an input source, which includes:
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  // -an input image list
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  // -an input patchsize (dimensions of samples)
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  //
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  void AddAnInputImage(int inputNumber = 0)
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  {
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    inputNumber++;
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    // Create keys and descriptions
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    std::stringstream ss_key_group, ss_desc_group;
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    ss_key_group << "source" << inputNumber;
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    ss_desc_group << "Parameters for source " << inputNumber;
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    // Populate group
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    ShareParameter(ss_key_group.str(), "tfmodel." + ss_key_group.str(), ss_desc_group.str());
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  }
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  void DoInit()
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  {
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    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 )