diff --git a/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx b/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx index 9284616399bb38d0c01401ef5af36f9f2feac229..aac361024a1e79d39af40f4089e49bc63c7e5ca9 100644 --- a/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx +++ b/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx @@ -77,7 +77,8 @@ protected: MandatoryOff("ts"); AddParameter(ParameterType_Int, "maxit", "Maximum number of iterations"); - SetParameterDescription("maxit", "Maximum number of iterations for the learning step."); + SetParameterDescription("maxit", "Maximum number of iterations for the learning step." + " If this parameter is set to 0, the KMeans algorithm will not stop until convergence"); SetDefaultParameterInt("maxit", 1000); MandatoryOff("maxit"); @@ -86,7 +87,9 @@ protected: "Group of parameters for centroids IO." ); AddParameter(ParameterType_InputFilename, "centroids.in", "input centroids text file"); - SetParameterDescription("centroids.in", "Input text file containing centroid posistions."); + SetParameterDescription("centroids.in", "Input text file containing centroid posistions used to initialize the algorithm." + " The file must contain one centroid per line, and each centroid value must be separated by a space. The number of" + " centroids in this file must match the number of classes (nc parameter)."); MandatoryOff("centroids.in"); ShareKMSamplingParameters(); diff --git a/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx b/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx index 872391ee73f28bf6633958d0c0ed1d9670871177..7abbbe72163b6f437beaf29bab93e547ec1e8cac 100644 --- a/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx +++ b/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx @@ -46,14 +46,15 @@ void LearningApplicationBase<TInputValue, TOutputValue>::InitSharkKMeansParams() SetParameterDescription("classifier.sharkkm.k", "The number of classes used for the kmeans algorithm. Default set to 2 class"); SetMinimumParameterIntValue("classifier.sharkkm.k", 2); - + // Centroid IO AddParameter( ParameterType_Group, "classifier.sharkkm.centroids", "Centroids IO parameters" ); SetParameterDescription( "classifier.sharkkm.centroids", "Group of parameters for centroids IO." ); - // Input centroids AddParameter(ParameterType_InputFilename, "classifier.sharkkm.centroids.in", "User definied input centroids"); - SetParameterDescription("classifier.sharkkm.centroids", "Text file containing input centroids."); + SetParameterDescription("classifier.sharkkm.centroids.in", "Input text file containing centroid posistions used to initialize the algorithm." + " The file must contain one centroid per line, and each centroid value must be separated by a space. The number of" + " centroids in this file must match the number of classes (classifier.sharkkm.k)."); MandatoryOff("classifier.sharkkm.centroids"); // Centroid statistics @@ -62,7 +63,7 @@ void LearningApplicationBase<TInputValue, TOutputValue>::InitSharkKMeansParams() "and reduce the centroids before the KMeans algorithm, produced by ComputeImagesStatistics application."); MandatoryOff("classifier.sharkkm.centroids.stats"); - // output centroids + // Output centroids AddParameter(ParameterType_OutputFilename, "classifier.sharkkm.centroids.out", "Output centroids text file"); SetParameterDescription("classifier.sharkkm.centroids.out", "Output text file containing centroids after the kmean algorithm."); MandatoryOff("classifier.sharkkm.centroids.out");