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  • Manuel Grizonnet's avatar
    ENH: rename files with txx extension to hxx · 3a1fd1fc
    Manuel Grizonnet authored 
    OTB followed since the beginning the ITK convention and use .txx extension for all
template classes. Nevertheless, some development tools do not recognize .txx
file extension. Other tool like GitHub can't do in-browser syntax highlighting for
txx files I think.

The root problem is the use of the txx which should be changed to hxx (or hpp).

In 2011, after an in-depth discussion near April 20, 2011 on the
Insight-Developers mailing list, ITK rename all txx files to hxx (and event
prevent the push of .txx files with a pre-commit hook). It happens is major release v4.

You can find some arguments in the discussion about the change and also in other
projects related to ITK which applied the same modification, see for instance VXL:

https://github.com/vxl/vxl/issues/209

This commit apply now the same modification for OTB.

I understand that it will change some habit for developers and don't bring new
features but I think that in general it is better to stay align with ITK guidelines.

In my opinion, it always facilitate the use of OTB and ITK together if we share
when we can the same code architecture, directory organization, naming
conventions...
    3a1fd1fc
otbTrainKNN.hxx 3.26 KiB
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/*
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 * Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
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 *
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 * This file is part of Orfeo Toolbox
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 *
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 *     https://www.orfeo-toolbox.org/
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 *
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 * Licensed under the Apache License, Version 2.0 (the "License");
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 * you may not use this file except in compliance with the License.
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 * You may obtain a copy of the License at
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 *
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 *     http://www.apache.org/licenses/LICENSE-2.0
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 *
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 * Unless required by applicable law or agreed to in writing, software
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 * distributed under the License is distributed on an "AS IS" BASIS,
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 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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 * See the License for the specific language governing permissions and
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 * limitations under the License.
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 */
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#ifndef otbTrainKNN_txx
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#define otbTrainKNN_txx
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#include "otbLearningApplicationBase.h"
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#include "otbKNearestNeighborsMachineLearningModel.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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  template <class TInputValue, class TOutputValue>
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  void
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  LearningApplicationBase<TInputValue,TOutputValue>
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  ::InitKNNParams()
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  {
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    AddChoice("classifier.knn", "KNN classifier");
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    SetParameterDescription("classifier.knn", "This group of parameters allows setting KNN classifier parameters. "
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        "See complete documentation here \\url{http://docs.opencv.org/modules/ml/doc/k_nearest_neighbors.html}.");
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    //K parameter
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    AddParameter(ParameterType_Int, "classifier.knn.k", "Number of Neighbors");
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    SetParameterInt("classifier.knn.k",32);
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    SetParameterDescription("classifier.knn.k","The number of neighbors to use.");
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    if (this->m_RegressionFlag)
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      {
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      // Decision rule : mean / median
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      AddParameter(ParameterType_Choice, "classifier.knn.rule", "Decision rule");
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      SetParameterDescription("classifier.knn.rule", "Decision rule for regression output");
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      AddChoice("classifier.knn.rule.mean", "Mean of neighbors values");
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      SetParameterDescription("classifier.knn.rule.mean","Returns the mean of neighbors values");
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      AddChoice("classifier.knn.rule.median", "Median of neighbors values");
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      SetParameterDescription("classifier.knn.rule.median","Returns the median of neighbors values");
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      }
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  }
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  template <class TInputValue, class TOutputValue>
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  void
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  LearningApplicationBase<TInputValue,TOutputValue>
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  ::TrainKNN(typename ListSampleType::Pointer trainingListSample,
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             typename TargetListSampleType::Pointer trainingLabeledListSample,
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             std::string modelPath)
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  {
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    typedef otb::KNearestNeighborsMachineLearningModel<InputValueType, OutputValueType> KNNType;
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    typename KNNType::Pointer knnClassifier = KNNType::New();
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    knnClassifier->SetRegressionMode(this->m_RegressionFlag);
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    knnClassifier->SetInputListSample(trainingListSample);
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    knnClassifier->SetTargetListSample(trainingLabeledListSample);
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knnClassifier->SetK(GetParameterInt("classifier.knn.k")); if (this->m_RegressionFlag) { std::string decision = this->GetParameterString("classifier.knn.rule"); if (decision == "mean") { knnClassifier->SetDecisionRule(KNNType::KNN_MEAN); } else if (decision == "median") { knnClassifier->SetDecisionRule(KNNType::KNN_MEDIAN); } } knnClassifier->Train(); knnClassifier->Save(modelPath); } } //end namespace wrapper } //end namespace otb #endif