Commit 3cd591c9 authored by Jonathan Guinet's avatar Jonathan Guinet
Browse files

DOC : KMeans Classification Qt application doc update.

parent abd9ee8d
......@@ -71,7 +71,18 @@ private:
KMeansClassification()
{
SetName("KMeansClassification");
SetDescription("Unsupervised KMeans image classification.");
SetDescription("Unsupervised KMeans image classification");
SetDocName("Unsupervised KMeans image classification Application");
SetDocLongDescription("Performs Unsupervised KMeans image classification.");
SetDocLimitations("None");
SetDocAuthors("OTB-Team");
SetDocSeeAlso(" ");
SetDocCLExample("otbApplicationLauncherCommandLine KMeansClassification "
"--in ${OTB-Data}/Input/poupees_sub.png --vm ${OTB-Data}/Input/mask_KMeans.png "
"--ts 100 --tp 0.6 --nc 5 --cp 0.9 --sl 100 --out ClassificationFilterOuptut.tif ");
AddDocTag("Classification");
}
virtual ~KMeansClassification()
......@@ -82,17 +93,25 @@ private:
{
AddParameter(ParameterType_InputImage, "in", "Input Image");
SetParameterDescription("in","Input image filename.");
AddParameter(ParameterType_OutputImage, "out", "Output Image");
SetParameterDescription("out","Output image filename.");
AddParameter(ParameterType_InputImage, "vm", "Validity Mask");
AddParameter(ParameterType_Int, "ts", "Size of the training set");
SetParameterDescription("vm","Validity mask. Only non-zero pixels will be used to estimate KMeans modes.");
AddParameter(ParameterType_Int, "ts", "Training set size");
SetParameterDescription("ts", "Size of the training set.");
SetParameterInt("ts", 100);
AddParameter(ParameterType_Float, "tp", "Probability for a sample to be selected in the training set");
AddParameter(ParameterType_Float, "tp", "Training set sample selection probability");
SetParameterDescription("tp", "Probability for a sample to be selected in the training set.");
SetParameterFloat("tp", 0.5);
AddParameter(ParameterType_Int, "nc", "Number of classes");
SetParameterDescription("nc","number of modes, which will be used to generate class membership.");
SetParameterInt("nc", 3);
AddParameter(ParameterType_Float, "cp", "Probability for a pixel to be selected as an initial class centroid");
AddParameter(ParameterType_Float, "cp", "Initial class centroid probability");
SetParameterDescription("cp", "Probability for a pixel to be selected as an initial class centroid");
SetParameterFloat("cp", 0.8);
AddParameter(ParameterType_Int, "sl", "Number of lines for each streaming block");
SetParameterDescription("sl","input image will be divided into sl lines.");
SetParameterInt("sl", 1000);
}
......
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