diff --git a/Modules/Applications/AppClassification/app/otbClassificationMapRegularization.cxx b/Modules/Applications/AppClassification/app/otbClassificationMapRegularization.cxx
index c5b0262be43c83ff560ec97ea3a418411ef5d17f..269a6f5bf5b7f9525380233d3a5414f6c9a82948 100644
--- a/Modules/Applications/AppClassification/app/otbClassificationMapRegularization.cxx
+++ b/Modules/Applications/AppClassification/app/otbClassificationMapRegularization.cxx
@@ -92,7 +92,7 @@ private:
SetParameterDescription("ip.radius", "The radius of the ball shaped structuring element (expressed in pixels). By default, 'ip.radius = 1 pixel'.");
SetDefaultParameterInt("ip.radius", 1.0);
- AddParameter(ParameterType_Empty, "ip.suvbool", "Multiple majority: Undecided(X)/Original");
+ AddParameter(ParameterType_Bool, "ip.suvbool", "Multiple majority: Undecided(X)/Original");
SetParameterDescription("ip.suvbool", "Pixels with more than 1 majority class are marked as Undecided if this parameter is checked (true), or keep their Original labels otherwise (false). Please note that the Undecided value must be different from existing labels in the input labeled image. By default, 'ip.suvbool = false'.");
AddParameter(ParameterType_Int, "ip.nodatalabel", "Label for the NoData class");
@@ -103,7 +103,7 @@ private:
SetParameterDescription("ip.undecidedlabel", "Label for the Undecided class. By default, 'ip.undecidedlabel = 0'.");
SetDefaultParameterInt("ip.undecidedlabel", 0.0);
- AddParameter(ParameterType_Empty, "ip.onlyisolatedpixels", "Process isolated pixels only");
+ AddParameter(ParameterType_Bool, "ip.onlyisolatedpixels", "Process isolated pixels only");
SetParameterDescription("ip.onlyisolatedpixels", "Only pixels whose label is unique in the neighbordhood will be processed. By default, 'ip.onlyisolatedpixels = false'.");
AddParameter(ParameterType_Int, "ip.isolatedthreshold", "Threshold for isolated pixels");
@@ -153,7 +153,7 @@ private:
m_NeighMajVotingFilter->SetLabelForUndecidedPixels(GetParameterInt("ip.undecidedlabel"));
// Set to Undecided label if NOT unique Majority Voting
- if (IsParameterEnabled("ip.suvbool"))
+ if (GetParameterInt("ip.suvbool"))
{
m_NeighMajVotingFilter->SetKeepOriginalLabelBool(false);
}
@@ -164,7 +164,7 @@ private:
}
// Process isolated pixels only
- if (IsParameterEnabled("ip.onlyisolatedpixels"))
+ if (GetParameterInt("ip.onlyisolatedpixels"))
{
m_NeighMajVotingFilter->SetOnlyIsolatedPixels(true);
m_NeighMajVotingFilter->SetIsolatedThreshold(GetParameterInt("ip.isolatedthreshold"));
diff --git a/Modules/Applications/AppClassification/app/otbDSFuzzyModelEstimation.cxx b/Modules/Applications/AppClassification/app/otbDSFuzzyModelEstimation.cxx
index e6343bf4b9654a41b82317f7c8d6412b87e2e940..3e19be7a515e280f0df6a03c1fbddf0e3dd3042c 100644
--- a/Modules/Applications/AppClassification/app/otbDSFuzzyModelEstimation.cxx
+++ b/Modules/Applications/AppClassification/app/otbDSFuzzyModelEstimation.cxx
@@ -164,9 +164,8 @@ private:
SetParameterDescription("maxnbit","Maximum number of optimizer iteration (default 200)");
SetParameterInt("maxnbit",200, false);
- AddParameter(ParameterType_Empty,"optobs","Optimizer Observer");
+ AddParameter(ParameterType_Bool,"optobs","Optimizer Observer");
SetParameterDescription("optobs","Activate the optimizer observer");
- MandatoryOff("optobs");
AddParameter(ParameterType_OutputFilename,"out","Output filename");
SetParameterDescription("out","Output model file name (xml file) contains the optimal model to perform information fusion.");
@@ -405,7 +404,7 @@ private:
// Create the Command observer and register it with the optimizer.
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
- if (IsParameterEnabled("optobs"))
+ if (GetParameterInt("optobs"))
{
m_Optimizer->AddObserver(itk::IterationEvent(), observer);
}
diff --git a/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx b/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx
index a5067bf9cdb782b5dd2d70e25a43c23f7d41baa8..67b86ac30eff4cbdb36c74ae51d8d6d241e54413 100644
--- a/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx
+++ b/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx
@@ -59,11 +59,10 @@ protected:
InitKMClassification();
// init at the end cleanup
- AddParameter( ParameterType_Empty, "cleanup", "Temporary files cleaning" );
- EnableParameter( "cleanup" );
+ AddParameter( ParameterType_Bool, "cleanup", "Temporary files cleaning" );
SetParameterDescription( "cleanup",
"If activated, the application will try to clean all temporary files it created" );
- MandatoryOff( "cleanup" );
+ SetParameterInt("cleanup", 1);
}
void InitKMSampling()
@@ -497,7 +496,7 @@ private:
Superclass::CreateOutMeansFile(GetParameterImage("in"), fileNames.modelFile, GetParameterInt("nc"));
// Remove all tempory files
- if( IsParameterEnabled( "cleanup" ) )
+ if( GetParameterInt( "cleanup" ) )
{
otbAppLogINFO( <<"Final clean-up ..." );
fileNames.clear();
diff --git a/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx b/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
index a76f81dce73870d4d6820f4931999d5253e9fed5..bb8b14c639818879aa27592699b418163adb5048 100644
--- a/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
+++ b/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
@@ -205,7 +205,7 @@ public:
TrainModel( imageList, fileNames.sampleTrainOutputs, fileNames.sampleValidOutputs );
// cleanup
- if( IsParameterEnabled( "cleanup" ) )
+ if( GetParameterInt( "cleanup" ) )
{
otbAppLogINFO( <<"Final clean-up ..." );
fileNames.clear();
diff --git a/Modules/Applications/AppClassification/app/otbTrainVectorClassifier.cxx b/Modules/Applications/AppClassification/app/otbTrainVectorClassifier.cxx
index f37eb3020f4934146d3ad4cfa9d402c19d058026..c1f6a9456ddf2ad5c419464d3fb557a6c75ca470 100644
--- a/Modules/Applications/AppClassification/app/otbTrainVectorClassifier.cxx
+++ b/Modules/Applications/AppClassification/app/otbTrainVectorClassifier.cxx
@@ -112,7 +112,7 @@ protected:
contingencyTableCalculator->Compute(performanceLabeledListSample->Begin(),
performanceLabeledListSample->End(),predictedListSample->Begin(), predictedListSample->End());
- if(IsParameterEnabled("v"))
+ if(GetParameterInt("v"))
{
otbAppLogINFO( "Training performances:" );
otbAppLogINFO(<<"Contingency table: reference labels (rows) vs. produced labels (cols)\n"
diff --git a/Modules/Applications/AppClassification/app/otbVectorClassifier.cxx b/Modules/Applications/AppClassification/app/otbVectorClassifier.cxx
index b8ecd88713eb985b25f935741268a17f8f955edf..9b996ed189ee9cba24128d0e79350e643ec54fc4 100644
--- a/Modules/Applications/AppClassification/app/otbVectorClassifier.cxx
+++ b/Modules/Applications/AppClassification/app/otbVectorClassifier.cxx
@@ -130,7 +130,7 @@ private:
SetParameterDescription("feat","List of field names in the input vector data used as features for training. "
"Put the same field names as the TrainVectorClassifier application.");
- AddParameter(ParameterType_Empty, "confmap", "Confidence map");
+ AddParameter(ParameterType_Bool, "confmap", "Confidence map");
SetParameterDescription( "confmap", "Confidence map of the produced classification. "
"The confidence index depends on the model : \n"
" - LibSVM : difference between the two highest probabilities "
@@ -145,7 +145,6 @@ private:
" * RandomForest : Confidence (proportion of votes for the majority class). "
"Margin (normalized difference of the votes of the 2 majority classes) is not available for now.\n"
" * SVM : distance to margin (only works for 2-class models).\n");
- MandatoryOff("confmap");
AddParameter(ParameterType_OutputFilename, "out", "Output vector data file containing class labels");
SetParameterDescription("out","Output vector data file storing sample values (OGR format)."
@@ -271,10 +270,10 @@ private:
ConfidenceListSampleType::Pointer quality;
- bool computeConfidenceMap(IsParameterEnabled("confmap") && m_Model->HasConfidenceIndex()
+ bool computeConfidenceMap(GetParameterInt("confmap") && m_Model->HasConfidenceIndex()
&& !m_Model->GetRegressionMode());
- if (!m_Model->HasConfidenceIndex() && IsParameterEnabled("confmap"))
+ if (!m_Model->HasConfidenceIndex() && GetParameterInt("confmap"))
{
otbAppLogWARNING("Confidence map requested but the classifier doesn't support it!");
}
diff --git a/Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx b/Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx
index 9803a91a7a8a03f46f9b5bd8443d3d12a112926a..0de1daea605733411f07485cf7c8b46c1f738c7e 100644
--- a/Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx
+++ b/Modules/Applications/AppClassification/include/otbTrainDecisionTree.txx
@@ -90,13 +90,13 @@ LearningApplicationBase<TInputValue,TOutputValue>
"is equal to cv_folds.");
//Use1seRule
- AddParameter(ParameterType_Empty, "classifier.dt.r", "Set Use1seRule flag to false");
+ AddParameter(ParameterType_Bool, "classifier.dt.r", "Set Use1seRule flag to false");
SetParameterDescription("classifier.dt.r",
"If true, then a pruning will be harsher. This will make a tree more compact and more "
"resistant to the training data noise but a bit less accurate.");
//TruncatePrunedTree
- AddParameter(ParameterType_Empty, "classifier.dt.t", "Set TruncatePrunedTree flag to false");
+ AddParameter(ParameterType_Bool, "classifier.dt.t", "Set TruncatePrunedTree flag to false");
SetParameterDescription("classifier.dt.t",
"If true, then pruned branches are physically removed from the tree.");
@@ -121,11 +121,11 @@ LearningApplicationBase<TInputValue,TOutputValue>
classifier->SetRegressionAccuracy(GetParameterFloat("classifier.dt.ra"));
classifier->SetMaxCategories(GetParameterInt("classifier.dt.cat"));
classifier->SetCVFolds(GetParameterInt("classifier.dt.f"));
- if (IsParameterEnabled("classifier.dt.r"))
+ if (GetParameterInt("classifier.dt.r"))
{
classifier->SetUse1seRule(false);
}
- if (IsParameterEnabled("classifier.dt.t"))
+ if (GetParameterInt("classifier.dt.t"))
{
classifier->SetTruncatePrunedTree(false);
}
diff --git a/Modules/Applications/AppClassification/include/otbTrainImagesBase.txx b/Modules/Applications/AppClassification/include/otbTrainImagesBase.txx
index a646cea9539fc3c8b6dcc5f013a6996ed7bf2a9d..2c8f60ee0d709dc20b6f184211512c11a4c91fef 100644
--- a/Modules/Applications/AppClassification/include/otbTrainImagesBase.txx
+++ b/Modules/Applications/AppClassification/include/otbTrainImagesBase.txx
@@ -39,11 +39,10 @@ void TrainImagesBase::InitIO()
SetParameterDescription( "io.vd", "A list of vector data to select the training samples." );
MandatoryOn( "io.vd" );
- AddParameter( ParameterType_Empty, "cleanup", "Temporary files cleaning" );
- EnableParameter( "cleanup" );
+ AddParameter( ParameterType_Bool, "cleanup", "Temporary files cleaning" );
SetParameterDescription( "cleanup",
"If activated, the application will try to clean all temporary files it created" );
- MandatoryOff( "cleanup" );
+ SetParameterInt( "cleanup", 1);
}
void TrainImagesBase::InitSampling()
diff --git a/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx b/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
index 18b9f4d39a8926abf645647bec30273d2b98e3b5..6ffd5faccc30e01262a918797fc79ed607fd68dc 100644
--- a/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
+++ b/Modules/Applications/AppClassification/include/otbTrainLibSVM.txx
@@ -105,11 +105,10 @@ namespace Wrapper
"the smoother the decision.");
// It seems that it miss a nu parameter for the nu-SVM use.
- AddParameter(ParameterType_Empty, "classifier.libsvm.opt", "Parameters optimization");
- MandatoryOff("classifier.libsvm.opt");
+ AddParameter(ParameterType_Bool, "classifier.libsvm.opt", "Parameters optimization");
SetParameterDescription("classifier.libsvm.opt", "SVM parameters optimization flag.");
- AddParameter(ParameterType_Empty, "classifier.libsvm.prob", "Probability estimation");
- MandatoryOff("classifier.libsvm.prob");
+
+ AddParameter(ParameterType_Bool, "classifier.libsvm.prob", "Probability estimation");
SetParameterDescription("classifier.libsvm.prob", "Probability estimation flag.");
if (this->m_RegressionFlag)
@@ -137,14 +136,8 @@ namespace Wrapper
libSVMClassifier->SetTargetListSample(trainingLabeledListSample);
//SVM Option
//TODO : Add other options ?
- if (IsParameterEnabled("classifier.libsvm.opt"))
- {
- libSVMClassifier->SetParameterOptimization(true);
- }
- if (IsParameterEnabled("classifier.libsvm.prob"))
- {
- libSVMClassifier->SetDoProbabilityEstimates(true);
- }
+ libSVMClassifier->SetParameterOptimization(GetParameterInt("classifier.libsvm.opt"));
+ libSVMClassifier->SetDoProbabilityEstimates(GetParameterInt("classifier.libsvm.prob"));
libSVMClassifier->SetNu(GetParameterFloat("classifier.libsvm.nu"));
libSVMClassifier->SetC(GetParameterFloat("classifier.libsvm.c"));
diff --git a/Modules/Applications/AppClassification/include/otbTrainSVM.txx b/Modules/Applications/AppClassification/include/otbTrainSVM.txx
index ac9524faa26de64a04e4a98b008b101f225cc8ca..8a748e49972f076e488a62ae71333a99502257bd 100644
--- a/Modules/Applications/AppClassification/include/otbTrainSVM.txx
+++ b/Modules/Applications/AppClassification/include/otbTrainSVM.txx
@@ -112,9 +112,8 @@ namespace Wrapper
SetParameterFloat("classifier.svm.degree",1.0, false);
SetParameterDescription("classifier.svm.degree",
"Parameter degree of a kernel function (POLY).");
- AddParameter(ParameterType_Empty, "classifier.svm.opt",
+ AddParameter(ParameterType_Bool, "classifier.svm.opt",
"Parameters optimization");
- MandatoryOff("classifier.svm.opt");
SetParameterDescription("classifier.svm.opt", "SVM parameters optimization flag.\n"
"-If set to True, then the optimal SVM parameters will be estimated. "
"Parameters are considered optimal by OpenCV when the cross-validation estimate of "
@@ -229,10 +228,7 @@ namespace Wrapper
SVMClassifier->SetCoef0(GetParameterFloat("classifier.svm.coef0"));
SVMClassifier->SetGamma(GetParameterFloat("classifier.svm.gamma"));
SVMClassifier->SetDegree(GetParameterFloat("classifier.svm.degree"));
- if (IsParameterEnabled("classifier.svm.opt"))
- {
- SVMClassifier->SetParameterOptimization(true);
- }
+ SVMClassifier->SetParameterOptimization(GetParameterInt("classifier.svm.opt"));
SVMClassifier->Train();
SVMClassifier->Save(modelPath);
diff --git a/Modules/Applications/AppClassification/include/otbTrainVectorBase.txx b/Modules/Applications/AppClassification/include/otbTrainVectorBase.txx
index 2c3575c2ead20381438f9f66d5cd9c65c1723132..453db3f3f02c29a23533ef26db67fb71d8cb6411 100644
--- a/Modules/Applications/AppClassification/include/otbTrainVectorBase.txx
+++ b/Modules/Applications/AppClassification/include/otbTrainVectorBase.txx
@@ -91,10 +91,9 @@ void TrainVectorBase::DoInit()
"The contingency table is output when we unsupervised algorithms is used otherwise the confusion matrix is output." );
MandatoryOff( "io.confmatout" );
- AddParameter(ParameterType_Empty, "v", "Verbose mode");
- EnableParameter("v");
+ AddParameter(ParameterType_Bool, "v", "Verbose mode");
SetParameterDescription("v", "Verbose mode, display the contingency table result.");
- MandatoryOff("v");
+ SetParameterInt("v", 1);
// Doc example parameter settings
SetDocExampleParameterValue( "io.vd", "vectorData.shp" );
diff --git a/Modules/Applications/AppDescriptors/app/otbHomologousPointsExtraction.cxx b/Modules/Applications/AppDescriptors/app/otbHomologousPointsExtraction.cxx
index 073e53727f6b194b27e49887c4cf8c70469c537f..04cf50df4d626be84da6288cdd740e9b2f10db55 100644
--- a/Modules/Applications/AppDescriptors/app/otbHomologousPointsExtraction.cxx
+++ b/Modules/Applications/AppDescriptors/app/otbHomologousPointsExtraction.cxx
@@ -135,10 +135,8 @@ private:
SetMinimumParameterFloatValue("threshold",0.0);
SetDefaultParameterFloat("threshold",0.6);
- AddParameter(ParameterType_Empty,"backmatching","Use back-matching to filter matches.");
+ AddParameter(ParameterType_Bool,"backmatching","Use back-matching to filter matches.");
SetParameterDescription("backmatching","If set to true, matches should be consistent in both ways.");
- MandatoryOff("backmatching");
- DisableParameter("backmatching");
AddParameter(ParameterType_Choice,"mode","Keypoints search mode");
@@ -177,10 +175,10 @@ private:
SetParameterDescription("precision","Estimated precision of the colocalisation function in pixels");
SetDefaultParameterFloat("precision",0.);
- AddParameter(ParameterType_Empty,"mfilter","Filter points according to geographical or sensor based colocalisation");
+ AddParameter(ParameterType_Bool,"mfilter","Filter points according to geographical or sensor based colocalisation");
SetParameterDescription("mfilter","If enabled, this option allows one to filter matches according to colocalisation from sensor or geographical information, using the given tolerancy expressed in pixels");
- AddParameter(ParameterType_Empty,"2wgs84","If enabled, points from second image will be exported in WGS84");
+ AddParameter(ParameterType_Bool,"2wgs84","If enabled, points from second image will be exported in WGS84");
// Elevation
ElevationParametersHandler::AddElevationParameters(this, "elev");
@@ -251,7 +249,7 @@ private:
matchingFilter->SetInput1(surf1->GetOutput());
matchingFilter->SetInput2(surf2->GetOutput());
matchingFilter->SetDistanceThreshold(GetParameterFloat("threshold"));
- matchingFilter->SetUseBackMatching(IsParameterEnabled("backmatching"));
+ matchingFilter->SetUseBackMatching(GetParameterInt("backmatching"));
}
try
@@ -276,7 +274,7 @@ private:
bool filtered = false;
- if(IsParameterEnabled("mfilter"))
+ if(GetParameterInt("mfilter"))
{
pprime1 = rsTransform->TransformPoint(point1);
error = vcl_sqrt((point2[0]-pprime1[0])*(point2[0]-pprime1[0])+(point2[1]-pprime1[1])*(point2[1]-pprime1[1]));
@@ -289,7 +287,7 @@ private:
if(!filtered)
{
- if(IsParameterEnabled("2wgs84"))
+ if(GetParameterInt("2wgs84"))
{
pprime2 = rsTransform2ToWGS84->TransformPoint(point2);
diff --git a/Modules/Applications/AppDimensionalityReduction/app/otbDimensionalityReduction.cxx b/Modules/Applications/AppDimensionalityReduction/app/otbDimensionalityReduction.cxx
index 686b78bb4cad81a332c249358998b59523fabdc6..1bf27acc11f46a3454b33c5dfe0621dbb49a9893 100644
--- a/Modules/Applications/AppDimensionalityReduction/app/otbDimensionalityReduction.cxx
+++ b/Modules/Applications/AppDimensionalityReduction/app/otbDimensionalityReduction.cxx
@@ -164,9 +164,8 @@ private:
MandatoryOff("nbcomp");
SetMinimumParameterIntValue("nbcomp", 0);
- AddParameter(ParameterType_Empty, "normalize", "Normalize.");
+ AddParameter(ParameterType_Bool, "normalize", "Normalize.");
SetParameterDescription("normalize", "center AND reduce data before Dimensionality reduction.");
- MandatoryOff("normalize");
AddParameter(ParameterType_OutputFilename, "outmatrix", "Transformation matrix output (text format)");
SetParameterDescription("outmatrix", "Filename to store the transformation matrix (csv format)");
@@ -237,7 +236,7 @@ private:
// Get Parameters
int nbComp = GetParameterInt("nbcomp");
- bool normalize = IsParameterEnabled("normalize");
+ bool normalize = GetParameterInt("normalize");
bool rescale = IsParameterEnabled("rescale");
bool invTransform = HasValue("outinv") && IsParameterEnabled("outinv");
diff --git a/Modules/Applications/AppDomainTransform/app/otbDomainTransform.cxx b/Modules/Applications/AppDomainTransform/app/otbDomainTransform.cxx
index 54dbe894f6520795efb9066b3d1546f89c991cd8..dbe4c4bce0bfea5e15ed9636d0c65dc8606f1540 100644
--- a/Modules/Applications/AppDomainTransform/app/otbDomainTransform.cxx
+++ b/Modules/Applications/AppDomainTransform/app/otbDomainTransform.cxx
@@ -134,7 +134,7 @@ private:
AddChoice("mode.fft", "FFT transform");
SetParameterDescription("mode.fft", "FFT transform");
- AddParameter(ParameterType_Empty, "mode.fft.shift", "Shift fft transform");
+ AddParameter(ParameterType_Bool, "mode.fft.shift", "Shift fft transform");
SetParameterDescription("mode.fft.shift", "Shift transform of fft filter");
AddChoice("mode.wavelet", "Wavelet");
@@ -263,7 +263,7 @@ private:
else
{
// fft ttransform
- bool shift = IsParameterEnabled( "mode.fft.shift");
+ bool shift = GetParameterInt( "mode.fft.shift");
typedef otb::Image< std::complex<OutputPixelType> > ComplexOutputImageType;
if (dir == 0 )
diff --git a/Modules/Applications/AppEdge/app/otbLineSegmentDetection.cxx b/Modules/Applications/AppEdge/app/otbLineSegmentDetection.cxx
index 45bc66c51d3562a5850bf83c269f8102e87828e0..588e8e1ff6af8a3497495c6962fd316147fb1888 100644
--- a/Modules/Applications/AppEdge/app/otbLineSegmentDetection.cxx
+++ b/Modules/Applications/AppEdge/app/otbLineSegmentDetection.cxx
@@ -85,11 +85,10 @@ private:
// Elevation
ElevationParametersHandler::AddElevationParameters(this, "elev");
- AddParameter(ParameterType_Empty, "norescale", "No rescaling in [0, 255]");
+ AddParameter(ParameterType_Bool, "norescale", "No rescaling in [0, 255]");
SetParameterDescription("norescale",
"By default, the input image amplitude is rescaled between [0,255]."
" Turn on this parameter to skip rescaling");
- MandatoryOff("norescale");
AddRAMParameter();
@@ -132,7 +131,7 @@ private:
= ShiftScaleImageFilterType::New();
// Default behavior is to do the rescaling
- if ( !IsParameterEnabled("norescale") )
+ if ( !GetParameterInt("norescale") )
{
stats->SetInput(amplitudeConverter->GetOutput());
stats->GetStreamer()->SetAutomaticAdaptativeStreaming(GetParameterInt("ram"));
diff --git a/Modules/Applications/AppFiltering/app/otbContrastEnhancement.cxx b/Modules/Applications/AppFiltering/app/otbContrastEnhancement.cxx
index 3c55bf6efaa3da250f6c0286c1dc1f7cb6e69045..0ec0c5628635b56bc7cdf7555db14ede8839c2fc 100644
--- a/Modules/Applications/AppFiltering/app/otbContrastEnhancement.cxx
+++ b/Modules/Applications/AppFiltering/app/otbContrastEnhancement.cxx
@@ -229,7 +229,7 @@ private:
SetParameterDescription("minmax.auto" , "Minimum and maximum value will "
"be computed on the image (nodata value won't be taken "
"into account) . Each band will have a minimum and a maximum.");
- AddParameter(ParameterType_Empty, "minmax.auto.global", "Global");
+ AddParameter(ParameterType_Bool, "minmax.auto.global", "Global");
SetParameterDescription("minmax.auto.global" , "Automatic"
"Min/max computation will result in the same minimum and maximum for "
"all the bands.");
@@ -488,7 +488,7 @@ private:
if ( m_MinMaxMode == "auto" )
{
oss << "automatic";
- if ( IsParameterEnabled( "minmax.auto.global" ) )
+ if ( GetParameterInt( "minmax.auto.global" ) )
{
oss << " and global";
}
@@ -584,7 +584,7 @@ private:
statFilter->Update();
min = statFilter->GetMinimum();
max = statFilter->GetMaximum();
- if ( IsParameterEnabled("minmax.auto.global") )
+ if ( GetParameterInt("minmax.auto.global") )
{
float temp(min[0]);
for ( unsigned int i = 1 ; i < min.GetSize() ; i++ )
@@ -602,7 +602,7 @@ private:
}
std::ostringstream oss;
oss<<"Minimum and maximum are for each channel : ";
- if ( IsParameterEnabled("minmax.auto.global") ||
+ if ( GetParameterInt("minmax.auto.global") ||
m_MinMaxMode == "manuel" )
{
oss<<std::endl<<min[0]<<" and "<<max[0];
diff --git a/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx b/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
index 439ba055904d6e1a3c8c5e72e367d2a27cc73771..744d8f049e51f39b7d43e400008c94ebda5725cf 100644
--- a/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
+++ b/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
@@ -79,10 +79,8 @@ private:
AddParameter(ParameterType_OutputImage, "out", "Output Image");
SetParameterDescription("out", "Output image");
- AddParameter(ParameterType_Empty,"usenan", "Consider NaN as no-data");
+ AddParameter(ParameterType_Bool,"usenan", "Consider NaN as no-data");
SetParameterDescription("usenan","If active, the application will consider NaN as no-data values as well");
- MandatoryOff("usenan");
- DisableParameter("usenan");
AddParameter(ParameterType_Choice,"mode","No-data handling mode");
SetParameterDescription("mode","Allows choosing between different no-data handling options");
@@ -138,12 +136,12 @@ private:
m_Filter = FilterType::New();
m_Filter->SetInsideValue(this->GetParameterFloat("mode.buildmask.inv"));
m_Filter->SetOutsideValue(this->GetParameterFloat("mode.buildmask.outv"));
- m_Filter->SetNaNIsNoData(IsParameterEnabled("usenan"));
+ m_Filter->SetNaNIsNoData(GetParameterInt("usenan"));
m_Filter->SetInput(inputPtr);
m_ChangeNoDataFilter = ChangeNoDataFilterType::New();
m_ChangeNoDataFilter->SetInput(inputPtr);
- m_ChangeNoDataFilter->SetNaNIsNoData(IsParameterEnabled("usenan"));
+ m_ChangeNoDataFilter->SetNaNIsNoData(GetParameterInt("usenan"));
std::vector<double> newNoData(inputPtr->GetNumberOfComponentsPerPixel(),GetParameterFloat("mode.changevalue.newv"));
diff --git a/Modules/Applications/AppImageUtils/app/otbMultiResolutionPyramid.cxx b/Modules/Applications/AppImageUtils/app/otbMultiResolutionPyramid.cxx
index d94f67b260a694de203b6814f20b67ce207b6c03..8117e4c165fd95ced9c8d2cec4485508b647d947 100644
--- a/Modules/Applications/AppImageUtils/app/otbMultiResolutionPyramid.cxx
+++ b/Modules/Applications/AppImageUtils/app/otbMultiResolutionPyramid.cxx
@@ -96,12 +96,11 @@ private:
SetParameterDescription( "vfactor", "Variance factor use in smoothing. It is multiplied by the subsampling factor of each level in the pyramid (default is 0.6).");
// Boolean Fast scheme
- AddParameter(ParameterType_Empty, "fast", "Use Fast Scheme");
+ AddParameter(ParameterType_Bool, "fast", "Use Fast Scheme");
std::ostringstream desc;
desc<<"If used, this option allows one to speed-up computation by iteratively"
<<" subsampling previous level of pyramid instead of processing the full input.";
SetParameterDescription("fast", desc.str());
- MandatoryOff("fast");
// Doc example parameter settings
SetDocExampleParameterValue("in", "QB_Toulouse_Ortho_XS.tif");
@@ -132,7 +131,7 @@ private:
unsigned int shrinkFactor = GetParameterInt("sfactor");
double varianceFactor = GetParameterFloat("vfactor");
- bool fastScheme = IsParameterEnabled("fast");
+ bool fastScheme = GetParameterInt("fast");
// Get the input image
FloatVectorImageType::Pointer inImage = GetParameterImage("in");
diff --git a/Modules/Applications/AppOpticalCalibration/app/otbOpticalCalibration.cxx b/Modules/Applications/AppOpticalCalibration/app/otbOpticalCalibration.cxx
index 87e7dc310fa0cc14efda2c900c0b29942d3feb11..7b7e5ef1e232e9b9e041689abf81b961f80dae51 100644
--- a/Modules/Applications/AppOpticalCalibration/app/otbOpticalCalibration.cxx
+++ b/Modules/Applications/AppOpticalCalibration/app/otbOpticalCalibration.cxx
@@ -199,16 +199,13 @@ private:
AddChoice("level.toc", "Image to Top Of Canopy reflectance (atmospheric corrections)");
SetParameterString("level", "toa", false);
- AddParameter(ParameterType_Empty, "milli", "Convert to milli reflectance");
+ AddParameter(ParameterType_Bool, "milli", "Convert to milli reflectance");
SetParameterDescription("milli", "Flag to use milli-reflectance instead of reflectance.\n"
"This allows saving the image with integer pixel type (in the range [0, 1000] instead of floating point in the range [0, 1]. In order to do that, use this option and set the output pixel type (-out filename double for example)");
- DisableParameter("milli");
- MandatoryOff("milli");
- AddParameter(ParameterType_Empty, "clamp", "Clamp of reflectivity values between [0, 1]");
+ AddParameter(ParameterType_Bool, "clamp", "Clamp of reflectivity values between [0, 1]");
SetParameterDescription("clamp", "Clamping in the range [0, 1]. It can be useful to preserve area with specular reflectance.");
- EnableParameter("clamp");
- MandatoryOff("clamp");
+ SetParameterInt("clamp",1);
//Acquisition parameters
AddParameter(ParameterType_Group,"acqui","Acquisition parameters");
@@ -751,12 +748,12 @@ private:
m_ImageToRadianceFilter->SetInput(inImage);
m_RadianceToReflectanceFilter->SetInput(m_ImageToRadianceFilter->GetOutput());
- if (IsParameterEnabled("clamp"))
+ if (GetParameterInt("clamp"))
{
GetLogger()->Info("Clamp values between [0, 100]\n");
}
- m_RadianceToReflectanceFilter->SetUseClamp(IsParameterEnabled("clamp"));
+ m_RadianceToReflectanceFilter->SetUseClamp(GetParameterInt("clamp"));
m_RadianceToReflectanceFilter->UpdateOutputInformation();
m_ScaleFilter->SetInput(m_RadianceToReflectanceFilter->GetOutput());
}
@@ -894,7 +891,7 @@ private:
}
//Rescale the surface reflectance in milli-reflectance
- if (!IsParameterEnabled("clamp"))
+ if (!GetParameterInt("clamp"))
{
if (!adjComputation)
m_ScaleFilter->SetInput(m_ReflectanceToSurfaceReflectanceFilter->GetOutput());
@@ -920,7 +917,7 @@ private:
// Output Image
double scale = 1.;
- if (IsParameterEnabled("milli"))
+ if (GetParameterInt("milli"))
{
GetLogger()->Info("Use milli-reflectance\n");
if ( (GetParameterInt("level") == Level_IM_TOA) || (GetParameterInt("level") == Level_TOC) )
diff --git a/Modules/Applications/AppProjection/app/otbOrthoRectification.cxx b/Modules/Applications/AppProjection/app/otbOrthoRectification.cxx
index 3c91403e47100f50b352f436f2a7583d648a14de..0ebf9ba0582d2b42175b895eb0bdabdb9763cd62 100644
--- a/Modules/Applications/AppProjection/app/otbOrthoRectification.cxx
+++ b/Modules/Applications/AppProjection/app/otbOrthoRectification.cxx
@@ -177,13 +177,13 @@ private:
MandatoryOff("outputs.lry");
MandatoryOff("outputs.ortho");
- AddParameter(ParameterType_Empty,"outputs.isotropic","Force isotropic spacing by default");
+ AddParameter(ParameterType_Bool,"outputs.isotropic","Force isotropic spacing by default");
std::ostringstream isotropOss;
isotropOss << "Default spacing (pixel size) values are estimated from the sensor modeling of the image. It can therefore result in a non-isotropic spacing. ";
isotropOss << "This option allows you to force default values to be isotropic (in this case, the minimum of spacing in both direction is applied. ";
isotropOss << "Values overridden by user are not affected by this option.";
SetParameterDescription("outputs.isotropic", isotropOss.str());
- EnableParameter("outputs.isotropic");
+ SetParameterInt("outputs.isotropic", 1);
AddParameter(ParameterType_Float, "outputs.default", "Default pixel value");
SetParameterDescription("outputs.default","Default value to write when outside of input image.");
@@ -259,7 +259,7 @@ private:
typedef otb::ImageToGenericRSOutputParameters<FloatVectorImageType> OutputParametersEstimatorType;
OutputParametersEstimatorType::Pointer genericRSEstimator = OutputParametersEstimatorType::New();
- if(IsParameterEnabled("outputs.isotropic"))
+ if(GetParameterInt("outputs.isotropic"))
{
genericRSEstimator->EstimateIsotropicSpacingOn();
}
diff --git a/Modules/Applications/AppSARCalibration/app/otbSARCalibration.cxx b/Modules/Applications/AppSARCalibration/app/otbSARCalibration.cxx
index 4a91dda2f5183e34a8bd470684302805b54d5609..07f4e0dadce61579cef63c40012c0190bdf1a6cf 100644
--- a/Modules/Applications/AppSARCalibration/app/otbSARCalibration.cxx
+++ b/Modules/Applications/AppSARCalibration/app/otbSARCalibration.cxx
@@ -68,9 +68,8 @@ private:
AddRAMParameter();
- AddParameter(ParameterType_Empty, "noise", "Disable Noise");
+ AddParameter(ParameterType_Bool, "noise", "Disable Noise");
SetParameterDescription("noise", "Flag to disable noise. For 5.2.0 release, the noise values are only read by TerraSARX product.");
- MandatoryOff("noise");
AddParameter(ParameterType_Choice, "lut", "Lookup table sigma /gamma/ beta/ DN.");
SetParameterDescription("lut", "Lookup table values are not available with all SAR products. Products that provide lookup table with metadata are: Sentinel1, Radarsat2.");
@@ -104,17 +103,8 @@ private:
// Set the filer input
m_CalibrationFilter = CalibrationFilterType::New();
m_CalibrationFilter->SetInput(floatComplexImage);
-
- if (IsParameterEnabled("noise"))
- {
- m_CalibrationFilter->SetEnableNoise(false);
- }
-
- short lut = 0;
-
- lut = GetParameterInt("lut");
-
- m_CalibrationFilter->SetLookupSelected(lut);
+ m_CalibrationFilter->SetEnableNoise( !bool(GetParameterInt("noise")) );
+ m_CalibrationFilter->SetLookupSelected(GetParameterInt("lut"));
// Set the output image
SetParameterOutputImage("out", m_CalibrationFilter->GetOutput());
diff --git a/Modules/Applications/AppSegmentation/app/otbLSMSSegmentation.cxx b/Modules/Applications/AppSegmentation/app/otbLSMSSegmentation.cxx
index 93694cc420dcc271c6dff0ac551d43d519acd2b4..280faee001b8f12462b2799e26a0e187572c4027 100644
--- a/Modules/Applications/AppSegmentation/app/otbLSMSSegmentation.cxx
+++ b/Modules/Applications/AppSegmentation/app/otbLSMSSegmentation.cxx
@@ -139,7 +139,7 @@ private:
void RemoveFile(std::string tile)
{
// Cleanup
- if(IsParameterEnabled("cleanup"))
+ if(GetParameterInt("cleanup"))
{
// Try to remove the geom file if existing
std::string geomfile = tile.substr(0,tile.size() - itksys::SystemTools::GetFilenameExtension(tile.c_str()).size()).append(".geom");
@@ -302,10 +302,9 @@ private:
MandatoryOff("tmpdir");
DisableParameter("tmpdir");
- AddParameter(ParameterType_Empty,"cleanup","Temporary files cleaning");
- EnableParameter("cleanup");
+ AddParameter(ParameterType_Bool,"cleanup","Temporary files cleaning");
SetParameterDescription("cleanup","If activated, the application will try to remove all temporary files it created.");
- MandatoryOff("cleanup");
+ SetParameterInt("cleanup",1);
// Doc example parameter settings
SetDocExampleParameterValue("in","smooth.tif");
@@ -724,7 +723,7 @@ private:
// Release input files
m_FinalReader = ITK_NULLPTR;
- if(IsParameterEnabled("cleanup"))
+ if(GetParameterInt("cleanup"))
{
otbAppLogINFO(<<"Final clean-up ...");
diff --git a/Modules/Applications/AppSegmentation/app/otbLargeScaleMeanShift.cxx b/Modules/Applications/AppSegmentation/app/otbLargeScaleMeanShift.cxx
index 27f8da837771c4eada660c43b6628e6fa32ec462..05ca673b6434030bab8d22067c9fcdc7219f4eaf 100644
--- a/Modules/Applications/AppSegmentation/app/otbLargeScaleMeanShift.cxx
+++ b/Modules/Applications/AppSegmentation/app/otbLargeScaleMeanShift.cxx
@@ -120,11 +120,10 @@ private:
"The output raster image",
"It corresponds to the output of the small region merging step.");
- AddParameter( ParameterType_Empty, "cleanup", "Temporary files cleaning" );
- EnableParameter( "cleanup" );
+ AddParameter( ParameterType_Bool, "cleanup", "Temporary files cleaning" );
SetParameterDescription( "cleanup",
"If activated, the application will try to clean all temporary files it created" );
- MandatoryOff( "cleanup" );
+ SetParameterInt("cleanup",1);
// Setup RAM
ShareParameter("ram","smoothing.ram");
diff --git a/Modules/Applications/AppSegmentation/app/otbMeanShiftSmoothing.cxx b/Modules/Applications/AppSegmentation/app/otbMeanShiftSmoothing.cxx
index 8f63bf13ef99f1062726c988b7c6b18a8aa236d5..d8980392b05ebf8fc2694057e59bda0554de7239 100644
--- a/Modules/Applications/AppSegmentation/app/otbMeanShiftSmoothing.cxx
+++ b/Modules/Applications/AppSegmentation/app/otbMeanShiftSmoothing.cxx
@@ -159,10 +159,8 @@ private:
SetMinimumParameterFloatValue("rangeramp", 0);
MandatoryOff("rangeramp");
- AddParameter(ParameterType_Empty, "modesearch", "Mode search.");
+ AddParameter(ParameterType_Bool, "modesearch", "Mode search.");
SetParameterDescription("modesearch", "If activated pixel iterative convergence is stopped if the path crosses an already converged pixel. Be careful, with this option, the result will slightly depend on thread number and the results will not be stable (see [4] for more details).");
- DisableParameter("modesearch");
-
// Doc example parameter settings
SetDocExampleParameterValue("in", "maur_rgb.png");
@@ -192,7 +190,7 @@ private:
m_Filter->SetThreshold(GetParameterFloat("thres"));
m_Filter->SetMaxIterationNumber(GetParameterInt("maxiter"));
m_Filter->SetRangeBandwidthRamp(GetParameterFloat("rangeramp"));
- m_Filter->SetModeSearch(IsParameterEnabled("modesearch"));
+ m_Filter->SetModeSearch(GetParameterInt("modesearch"));
//Compute the margin used to ensure exact results (tile wise smoothing)
//This margin is valid for the default uniform kernel used by the
@@ -211,7 +209,7 @@ private:
{
SetParameterOutputImage("foutpos", m_Filter->GetSpatialOutput());
}
- if(!IsParameterEnabled("modesearch"))
+ if(!GetParameterInt("modesearch"))
{
otbAppLogINFO(<<"Mode Search is disabled." << std::endl);
}
diff --git a/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx b/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx
index 5b3bfd2361f211e9dccf19b383542596fd1b994a..cbb1c0b9590b901034b097128a3a44a6b032689f 100644
--- a/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx
+++ b/Modules/Applications/AppSegmentation/app/otbSegmentation.cxx
@@ -282,17 +282,13 @@ private:
SetParameterDescription("mode.vector.inmask", "Only pixels whose mask value is strictly positive will be segmented.");
MandatoryOff("mode.vector.inmask");
- AddParameter(ParameterType_Empty, "mode.vector.neighbor", "8-neighbor connectivity");
+ AddParameter(ParameterType_Bool, "mode.vector.neighbor", "8-neighbor connectivity");
SetParameterDescription("mode.vector.neighbor",
"Activate 8-Neighborhood connectivity (default is 4).");
- MandatoryOff("mode.vector.neighbor");
- DisableParameter("mode.vector.neighbor");
-
- AddParameter(ParameterType_Empty,"mode.vector.stitch","Stitch polygons");
+ AddParameter(ParameterType_Bool,"mode.vector.stitch","Stitch polygons");
SetParameterDescription("mode.vector.stitch", "Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel.");
- MandatoryOff("mode.vector.stitch");
- EnableParameter("mode.vector.stitch");
+ SetParameterInt("mode.vector.stitch",1);
AddParameter(ParameterType_Int, "mode.vector.minsize", "Minimum object size");
SetParameterDescription("mode.vector.minsize",
@@ -365,7 +361,7 @@ private:
// Retrieve tile size parameter
const unsigned int tileSize = static_cast<unsigned int> (this->GetParameterInt("mode.vector.tilesize"));
// Retrieve the 8-connected option
- bool use8connected = IsParameterEnabled("mode.vector.neighbor");
+ bool use8connected = GetParameterInt("mode.vector.neighbor");
// Retrieve min object size parameter
const unsigned int minSize = static_cast<unsigned int> (this->GetParameterInt("mode.vector.minsize"));
@@ -673,7 +669,7 @@ private:
ogrDS->SyncToDisk();
// Stitching mode
- if (IsParameterEnabled("mode.vector.stitch"))
+ if (GetParameterInt("mode.vector.stitch"))
{
otbAppLogINFO(<<"Segmentation done, stiching polygons ...");
diff --git a/Modules/Applications/AppStereo/app/otbBlockMatching.cxx b/Modules/Applications/AppStereo/app/otbBlockMatching.cxx
index 2ec8f7e63a0c00d90c3156c390ea71ce3af63573..41c9257ac04acd9256df53ad382608a17f26110b 100644
--- a/Modules/Applications/AppStereo/app/otbBlockMatching.cxx
+++ b/Modules/Applications/AppStereo/app/otbBlockMatching.cxx
@@ -202,7 +202,7 @@ private:
DisableParameter("io.outmask");
MandatoryOff("io.outmask");
- AddParameter(ParameterType_Empty,"io.outmetric","Flag to output optimal "
+ AddParameter(ParameterType_Bool,"io.outmetric","Flag to output optimal "
"metric values as well");
SetParameterDescription("io.outmetric","If enabled, the output image will "
"have a third component with metric optimal values");
@@ -847,7 +847,7 @@ private:
m_OutputImageList->PushBack(hdispImage);
m_OutputImageList->PushBack(vdispImage);
- if(IsParameterEnabled("io.outmetric"))
+ if(GetParameterInt("io.outmetric"))
{
m_OutputImageList->PushBack(metricImage);
}
diff --git a/Modules/Applications/AppStereo/app/otbStereoFramework.cxx b/Modules/Applications/AppStereo/app/otbStereoFramework.cxx
index 279c09ad2f9734bf45a95cb612408edb36efb8b8..ee462306f8d85862e1bfe26550cfeb9cc3416ed1 100644
--- a/Modules/Applications/AppStereo/app/otbStereoFramework.cxx
+++ b/Modules/Applications/AppStereo/app/otbStereoFramework.cxx
@@ -525,20 +525,16 @@ private:
AddParameter(ParameterType_Group,"postproc","Postprocessing parameters");
SetParameterDescription("postproc","This group of parameters allow use optional filters.");
- AddParameter(ParameterType_Empty,"postproc.bij","Use bijection consistency"
+ AddParameter(ParameterType_Bool,"postproc.bij","Use bijection consistency"
" in block matching strategy");
SetParameterDescription("postproc.bij","Use bijection consistency. "
"Right to Left correlation is computed to validate Left to Right "
"disparities. If bijection is not found, the disparity is rejected.");
- MandatoryOff("postproc.bij");
- EnableParameter("postproc.bij");
+ SetParameterInt("postproc.bij", 1);
- AddParameter(ParameterType_Empty,"postproc.med","Use median disparities filtering");
+ AddParameter(ParameterType_Bool,"postproc.med","Use median disparities filtering");
SetParameterDescription("postproc.med","Disparity map can be filtered using"
" median post filtering (disabled by default).");
- MandatoryOff("postproc.med");
- DisableParameter("postproc.med");
-
AddParameter(ParameterType_Float,"postproc.metrict","Correlation metric threshold");
SetParameterDescription("postproc.metrict","Use block matching metric "
@@ -624,7 +620,7 @@ private:
}
else blockMatcherFilter->MinimizeOff();
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
invBlockMatcherFilter->SetLeftInput(rightImage);
invBlockMatcherFilter->SetRightInput(leftImage);
@@ -947,7 +943,7 @@ private:
m_Filters.push_back(lBandMathFilter.GetPointer());
BandMathFilterType::Pointer finalMaskFilter;
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
finalMaskFilter = BandMathFilterType::New();
finalMaskFilter->SetNthInput(0, lBandMathFilter->GetOutput(), "inmask");
@@ -992,7 +988,7 @@ private:
blockMatcherFilterPointer = SSDDivMeanBlockMatcherFilter.GetPointer();
m_Filters.push_back(blockMatcherFilterPointer);
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
//Reverse correlation
invSSDDivMeanBlockMatcherFilter = SSDDivMeanBlockMatchingFilterType::New();
@@ -1025,7 +1021,7 @@ private:
blockMatcherFilterPointer = SSDBlockMatcherFilter.GetPointer();
m_Filters.push_back(blockMatcherFilterPointer);
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
//Reverse correlation
invSSDBlockMatcherFilter = SSDBlockMatchingFilterType::New();
@@ -1056,7 +1052,7 @@ private:
blockMatcherFilterPointer = NCCBlockMatcherFilter.GetPointer();
m_Filters.push_back(blockMatcherFilterPointer);
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
//Reverse correlation
invNCCBlockMatcherFilter = NCCBlockMatchingFilterType::New();
@@ -1090,7 +1086,7 @@ private:
blockMatcherFilterPointer = LPBlockMatcherFilter.GetPointer();
m_Filters.push_back(blockMatcherFilterPointer);
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
//Reverse correlation
invLPBlockMatcherFilter = LPBlockMatchingFilterType::New();
@@ -1119,7 +1115,7 @@ private:
break;
}
- if (IsParameterEnabled("postproc.bij"))
+ if (GetParameterInt("postproc.bij"))
{
otbAppLogINFO(<<"Using reverse block-matching to filter incoherent disparity values.");
bijectFilter = BijectionFilterType::New();
@@ -1149,7 +1145,7 @@ private:
FloatImageType::Pointer hDispOutput = subPixelFilterPointer->GetOutput(0);
FloatImageType::Pointer finalMaskImage=finalMaskFilter->GetOutput();
- if (IsParameterEnabled("postproc.med"))
+ if (GetParameterInt("postproc.med"))
{
MedianFilterType::Pointer hMedianFilter = MedianFilterType::New();
hMedianFilter->SetInput(subPixelFilterPointer->GetOutput(0));
@@ -1183,7 +1179,7 @@ private:
FloatImageType::Pointer hDispOutput2 = disparityTranslateFilter->GetHorizontalDisparityMapOutput();
FloatImageType::Pointer vDispOutput2 = disparityTranslateFilter->GetVerticalDisparityMapOutput();
FloatImageType::Pointer translatedMaskImage = dispTranslateMaskFilter->GetOutput();
- if (IsParameterEnabled("postproc.med"))
+ if (GetParameterInt("postproc.med"))
{
MedianFilterType::Pointer hMedianFilter2 = MedianFilterType::New();
MedianFilterType::Pointer vMedianFilter2 = MedianFilterType::New();
diff --git a/Modules/Applications/AppTest/app/otbTestApplication.cxx b/Modules/Applications/AppTest/app/otbTestApplication.cxx
index a2e9ee940da3b473f8e69fbd152eda675c66256d..4407d76ed36a5da9f329b31edd215ba6ebcbaaca 100644
--- a/Modules/Applications/AppTest/app/otbTestApplication.cxx
+++ b/Modules/Applications/AppTest/app/otbTestApplication.cxx
@@ -56,7 +56,8 @@ private:
AddDocTag("Test");
//std::cout << "TestApplication::DoInit" << std::endl;
- AddParameter(ParameterType_Empty, "boolean", "Boolean");
+ AddParameter(ParameterType_Empty, "empty", "Boolean (old impl.)");
+ AddParameter(ParameterType_Bool, "boolean", "Boolean");
AddParameter(ParameterType_Int, "int", "Integer");
MandatoryOff("int");
AddParameter(ParameterType_Float, "float", "Float");
diff --git a/Modules/Applications/AppVectorUtils/app/otbOSMDownloader.cxx b/Modules/Applications/AppVectorUtils/app/otbOSMDownloader.cxx
index d55626ed0bb0f79d3696a4a2940c59a870038217..ba625b5f4862f0f0377ee4d0f082193dcd0815e7 100644
--- a/Modules/Applications/AppVectorUtils/app/otbOSMDownloader.cxx
+++ b/Modules/Applications/AppVectorUtils/app/otbOSMDownloader.cxx
@@ -98,11 +98,10 @@ private:
// Elevation
ElevationParametersHandler::AddElevationParameters(this, "elev");
- AddParameter(ParameterType_Empty, "printclasses", "Displays available key/value classes");
+ AddParameter(ParameterType_Bool, "printclasses", "Displays available key/value classes");
SetParameterDescription("printclasses","Print the key/value classes "
"available for the selected support image. If enabled, the OSM tag Key "
"(-key) and the output (-out) become optional" );
- MandatoryOff("printclasses");
// Doc example parameter settings
SetDocExampleParameterValue("support", "qb_RoadExtract.tif");
@@ -118,15 +117,15 @@ private:
// CASE: when the -print option is not required and the User
// does not set the option OSMKey or the option Output or does not
// set both of them
- if ( !this->HasValue("printclasses") )
+ if ( GetParameterInt("printclasses") )
{
- MandatoryOn("out");
- MandatoryOn("key");
+ MandatoryOff("out");
+ MandatoryOff("key");
}
else
{
- MandatoryOff("out");
- MandatoryOff("key");
+ MandatoryOn("out");
+ MandatoryOn("key");
}
}
@@ -178,7 +177,7 @@ private:
// If the user wants to print the Key/Values present in the XML file
// downloaded :
- if ( this->HasValue("printclasses"))
+ if ( GetParameterInt("printclasses"))
{
// Print the classes
VectorDataProviderType::KeyMapType keymap = m_VdOSMGenerator->GetKeysMap();