From dded43e347a7a5553d8c8fe697d6e70ad185c2b1 Mon Sep 17 00:00:00 2001
From: Jonathan Guinet <jonathan.guinet@c-s.fr>
Date: Tue, 25 Oct 2011 11:37:38 +0200
Subject: [PATCH] DOC: Train SVM Images Classifier Doc update.
---
.../otbTrainSVMImagesClassifier.cxx | 29 ++++++++++++++-----
1 file changed, 22 insertions(+), 7 deletions(-)
diff --git a/Applications/Classification/otbTrainSVMImagesClassifier.cxx b/Applications/Classification/otbTrainSVMImagesClassifier.cxx
index 1fef88e97c..95018a25e8 100644
--- a/Applications/Classification/otbTrainSVMImagesClassifier.cxx
+++ b/Applications/Classification/otbTrainSVMImagesClassifier.cxx
@@ -131,6 +131,21 @@ private:
{
SetName("TrainSVMImagesClassifier");
SetDescription("Perform SVM training from multiple input images and multiple vector data.");
+
+ // Documentation
+ SetDocName("Train SVM images Application");
+ SetDocLongDescription("This application performs SVM training from multiple input images and multiple vector data.");
+ SetDocLimitations("None");
+ SetDocAuthors("OTB-Team");
+ SetDocSeeAlso(" ");
+ SetDocCLExample("otbApplicationLauncherCommandLine TrainSVMImagesClassifier ${OTB-BIN}/bin"
+ "--il ${OTB-DATA}/Classification/QB_1_ortho.tif "
+ "--vd ${OTB-DATA}/Classification/ectorData_QB1.shp"
+ "--imstat ${OTB-Data}/Baseline/OTB-Applications/Files/clImageStatisticsQB1.xml"
+ "--b 2 --mv 100 --vtr 0.5 --opt true -out svmModelQB1_allOpt.svm");
+ AddDocTag("Classification");
+ AddDocTag("Training");
+ AddDocTag("SVM");
}
virtual ~TrainSVMImagesClassifier()
@@ -143,7 +158,7 @@ private:
AddParameter(ParameterType_InputImageList, "il", "Input Image List");
SetParameterDescription("il", "a list of input images.");
AddParameter(ParameterType_InputVectorDataList, "vd", "Vector Data List");
- SetParameterDescription("vd", "a list of vector data sample used to train the estimator.");
+ SetParameterDescription("vd", "A list of vector data sample used to train the estimator.");
AddParameter(ParameterType_Filename, "dem", "DEM repository");
MandatoryOff("dem");
SetParameterDescription("dem", "path to SRTM repository");
@@ -154,9 +169,9 @@ private:
SetParameterDescription("out", "Output SVM model");
AddParameter(ParameterType_Float, "m", "Margin for SVM learning");
MandatoryOff("m");
- SetParameterDescription("m", "Margin for SVM learning");
+ SetParameterDescription("m", "Margin for SVM learning.");
AddParameter(ParameterType_Int, "b", "Balance and grow the training set");
- SetParameterDescription("b", "Balance and grow the training set");
+ SetParameterDescription("b", "Balance and grow the training set.");
MandatoryOff("b");
AddParameter(ParameterType_Choice, "k", "SVM Kernel Type");
MandatoryOff("k");
@@ -165,18 +180,18 @@ private:
AddChoice("k.poly", "Polynomial");
AddChoice("k.sigmoid", "Sigmoid");
SetParameterString("k", "linear");
- SetParameterDescription("k", "SVM Kernel Type");
+ SetParameterDescription("k", "SVM Kernel Type.");
AddParameter(ParameterType_Int, "mt", "Maximum training sample size");
MandatoryOff("mt");
SetParameterInt("mt", -1);
- SetParameterDescription("mt", "Maximum size of the training sample (default = -1)");
+ SetParameterDescription("mt", "Maximum size of the training sample (default = -1).");
AddParameter(ParameterType_Int, "mv", "Maximum validation sample size");
MandatoryOff("mv");
SetParameterInt("mv", -1);
SetParameterDescription("mv", "Maximum size of the validation sample (default = -1)");
AddParameter(ParameterType_Float, "vtr", "training and validation sample ratio");
SetParameterDescription("vtr",
- "Ratio between training and validation sample (0.0 = all training, 1.0 = all validation) default = 0.5");
+ "Ratio between training and validation sample (0.0 = all training, 1.0 = all validation) default = 0.5.");
MandatoryOff("vtr");
SetParameterFloat("vtr", 0.5);
AddParameter(ParameterType_Empty, "opt", "parameters optimization");
@@ -184,7 +199,7 @@ private:
SetParameterDescription("opt", "SVM parameters optimization");
AddParameter(ParameterType_Filename, "vfn", "Name of the discrimination field");
MandatoryOff("vfn");
- SetParameterDescription("vfn", "Name of the field using to discriminate class in the vector data files");
+ SetParameterDescription("vfn", "Name of the field using to discriminate class in the vector data files.");
SetParameterString("vfn", "Class");
}
--
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