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3cd591c9
Commit
3cd591c9
authored
Oct 24, 2011
by
Jonathan Guinet
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DOC : KMeans Classification Qt application doc update.
parent
abd9ee8d
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23 additions
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4 deletions
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-4
Applications/Classification/otbKMeansClassification.cxx
Applications/Classification/otbKMeansClassification.cxx
+23
-4
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Applications/Classification/otbKMeansClassification.cxx
View file @
3cd591c9
...
...
@@ -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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