diff --git a/Applications/Segmentation/otbSegmentation.cxx b/Applications/Segmentation/otbSegmentation.cxx
index ed914a1e9607341fd01ca4585d11437420a8c449..b44b191d81e11fdb561ee632b6a485f27c376706 100644
--- a/Applications/Segmentation/otbSegmentation.cxx
+++ b/Applications/Segmentation/otbSegmentation.cxx
@@ -128,24 +128,24 @@ private:
void DoInit()
{
SetName("Segmentation");
- SetDescription("Performs segmentation of an image, with an optional large scale mode to handle large images.");
+ SetDescription("Performs segmentation of an image, and output either a raster or a vector file. In vector mode, large input datasets are supported.");
// Documentation
SetDocName("Segmentation");
SetDocLongDescription("This application allows to perform various segmentation algorithm on an multispectral image. "
- "Available segmentation algorithms are two different version of Mean-Shift segmentation algorithm (one beeing multi-threaded),"
+ "Available segmentation algorithms are two different version of Mean-Shift segmentation algorithm (one being multi-threaded),"
" simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity "
- "(norm of spectral bands vector). The application has two different modes that affects the nature of its output.\n\nIn normal mode,"
+ "(norm of spectral bands vector). The application has two different modes that affects the nature of its output.\n\nIn raster mode,"
" the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the "
- " ColorMapping application to render regions with contrasted colors. Please note that this mode loads the whole input image into memory, and as such "
- " can not handle large images. \n\nTo segment large data, one can use the largescale mode. In this case, the output of the application is a "
- " vector file or database. The input image is splitted into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented "
- " with the chosen algorithm, vectorized, and writen into the output file or database. This piece-wise behaviour ensure that memory will never get overloaded, "
- " and that images of any size can be processed. There are few more options in the largescale mode. The simplify option allows to simplify the geometry "
+ " ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such "
+ " can not handle large images. \n\nTo segment large data, one can use the vector mode. In this case, the output of the application is a "
+ " vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented "
+ " with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behaviour ensure that memory will never get overloaded, "
+ " and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows to simplify the geometry "
" (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option allows to application to try to stitch together polygons corresponding "
" to segmented region that may have been splitted by the tiling scheme. ");
- SetDocLimitations("In normal mode, the application can not handle large input images. Stiching step of largescale mode might become slow with very large input images.");
+ SetDocLimitations("In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images.");
SetDocAuthors("OTB-Team");
SetDocSeeAlso("MeanShiftSegmentation");
@@ -224,83 +224,83 @@ private:
SetMaximumParameterFloatValue("filter.watershed.level",1);
AddParameter(ParameterType_Choice, "mode", "Processing mode");
- SetParameterDescription("mode", "Choice of processing mode, either normal or large-scale.");
+ SetParameterDescription("mode", "Choice of processing mode, either raster or large-scale.");
- AddChoice("mode.largescale", "Tile-based large-scale segmentation with vector output");
- SetParameterDescription("mode.largescale","In this mode, the application will output a vector file or database, and process the input image piecewise. This allows to perform segmentation of very large images.");
+ AddChoice("mode.vector", "Tile-based large-scale segmentation with vector output");
+ SetParameterDescription("mode.vector","In this mode, the application will output a vector file or database, and process the input image piecewise. This allows to perform segmentation of very large images.");
- AddChoice("mode.normal", "Standard segmentation with labeled raster output");
- SetParameterDescription("mode.normal","In this mode, the application will output a standard labeled raster. This mode can not handle large data.");
+ AddChoice("mode.raster", "Standard segmentation with labeled raster output");
+ SetParameterDescription("mode.raster","In this mode, the application will output a standard labeled raster. This mode can not handle large data.");
- //Normal mode parameters
- AddParameter(ParameterType_OutputImage, "mode.normal.lout", "Output labeled image");
- SetParameterDescription( "mode.normal.lout", "The output labeled image.");
+ //Raster mode parameters
+ AddParameter(ParameterType_OutputImage, "mode.raster.out", "Output labeled image");
+ SetParameterDescription( "mode.raster.out", "The output labeled image.");
//Streaming vectorization parameters
- AddParameter(ParameterType_OutputFilename, "mode.largescale.outvd", "Output vector file");
- SetParameterDescription("mode.largescale.outvd", "The output vector file or database (name can be anything understood by OGR)");
+ AddParameter(ParameterType_OutputFilename, "mode.vector.out", "Output vector file");
+ SetParameterDescription("mode.vector.out", "The output vector file or database (name can be anything understood by OGR)");
- AddParameter(ParameterType_InputImage, "mode.largescale.inmask", "Mask Image");
- SetParameterDescription("mode.largescale.inmask", "Only pixels whose mask value is strictly positive will be segmented.");
- MandatoryOff("mode.largescale.inmask");
+ AddParameter(ParameterType_InputImage, "mode.vector.inmask", "Mask Image");
+ SetParameterDescription("mode.vector.inmask", "Only pixels whose mask value is strictly positive will be segmented.");
+ MandatoryOff("mode.vector.inmask");
- AddParameter(ParameterType_Empty, "mode.largescale.neighbor", "8-neighbor connectivity");
- SetParameterDescription("mode.largescale.neighbor",
+ AddParameter(ParameterType_Empty, "mode.vector.neighbor", "8-neighbor connectivity");
+ SetParameterDescription("mode.vector.neighbor",
"Activate 8-Neighbourhood connectivity (default is 4).");
- MandatoryOff("mode.largescale.neighbor");
- EnableParameter("mode.largescale.neighbor");
+ MandatoryOff("mode.vector.neighbor");
+ EnableParameter("mode.vector.neighbor");
- AddParameter(ParameterType_Empty,"mode.largescale.stitch","Stitch polygons");
- SetParameterDescription("mode.largescale.stitch", "Scan polygons on each side of tiles and stitch polygons which connect by more than one pixel.");
- MandatoryOff("mode.largescale.stitch");
- EnableParameter("mode.largescale.stitch");
+ AddParameter(ParameterType_Empty,"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");
- AddParameter(ParameterType_Int, "mode.largescale.minsize", "Minimum object size");
- SetParameterDescription("mode.largescale.minsize",
+ AddParameter(ParameterType_Int, "mode.vector.minsize", "Minimum object size");
+ SetParameterDescription("mode.vector.minsize",
"Objects whose size is below the minimum object size (area in pixels) will be ignored during vectorization.");
- SetDefaultParameterInt("mode.largescale.minsize", 1);
- SetMinimumParameterIntValue("mode.largescale.minsize", 1);
- MandatoryOff("mode.largescale.minsize");
- DisableParameter("mode.largescale.minsize");
+ SetDefaultParameterInt("mode.vector.minsize", 1);
+ SetMinimumParameterIntValue("mode.vector.minsize", 1);
+ MandatoryOff("mode.vector.minsize");
+ DisableParameter("mode.vector.minsize");
- AddParameter(ParameterType_Float, "mode.largescale.simplify", "Simplify polygons");
- SetParameterDescription("mode.largescale.simplify",
+ AddParameter(ParameterType_Float, "mode.vector.simplify", "Simplify polygons");
+ SetParameterDescription("mode.vector.simplify",
"Simplify polygons according to a given tolerance (in pixel). This option allows to reduce the size of the output file or database.");
- SetDefaultParameterFloat("mode.largescale.simplify",0.1);
- MandatoryOff("mode.largescale.simplify");
+ SetDefaultParameterFloat("mode.vector.simplify",0.1);
+ MandatoryOff("mode.vector.simplify");
- AddParameter(ParameterType_String, "mode.largescale.layername", "Layer name");
- SetParameterDescription("mode.largescale.layername", "Name of the layer in the vector file or database (default is Layer).");
- SetParameterString("mode.largescale.layername", "layer");
+ AddParameter(ParameterType_String, "mode.vector.layername", "Layer name");
+ SetParameterDescription("mode.vector.layername", "Name of the layer in the vector file or database (default is Layer).");
+ SetParameterString("mode.vector.layername", "layer");
- AddParameter(ParameterType_String, "mode.largescale.fieldname", "Geometry index field name");
- SetParameterDescription("mode.largescale.fieldname", "Name of the field holding the geometry index in the output vector file or database.");
- SetParameterString("mode.largescale.fieldname", "DN");
+ AddParameter(ParameterType_String, "mode.vector.fieldname", "Geometry index field name");
+ SetParameterDescription("mode.vector.fieldname", "Name of the field holding the geometry index in the output vector file or database.");
+ SetParameterString("mode.vector.fieldname", "DN");
- AddParameter(ParameterType_Int, "mode.largescale.tilesize", "Tiles size");
- SetParameterDescription("mode.largescale.tilesize",
+ AddParameter(ParameterType_Int, "mode.vector.tilesize", "Tiles size");
+ SetParameterDescription("mode.vector.tilesize",
"User defined tiles size for tile-based segmentation. Optimal tile size is selected according to available RAM if null.");
- SetDefaultParameterInt("mode.largescale.tilesize",1024);
- SetMinimumParameterIntValue("mode.largescale.tilesize",0);
+ SetDefaultParameterInt("mode.vector.tilesize",1024);
+ SetMinimumParameterIntValue("mode.vector.tilesize",0);
- AddParameter(ParameterType_Int, "mode.largescale.startlabel", "Starting geometry index");
- SetParameterDescription("mode.largescale.startlabel", "Starting value of the geometry index field");
- SetDefaultParameterInt("mode.largescale.startlabel", 1);
- SetMinimumParameterIntValue("mode.largescale.startlabel", 1);
+ AddParameter(ParameterType_Int, "mode.vector.startlabel", "Starting geometry index");
+ SetParameterDescription("mode.vector.startlabel", "Starting value of the geometry index field");
+ SetDefaultParameterInt("mode.vector.startlabel", 1);
+ SetMinimumParameterIntValue("mode.vector.startlabel", 1);
// Doc example parameter settings
SetExampleComment("Example of use with vector mode and watershed segmentation",0);
SetDocExampleParameterValue("in", "QB_Toulouse_Ortho_PAN.tif");
- SetDocExampleParameterValue("mode","largescale");
- SetDocExampleParameterValue("mode.largescale.outvd", "SegmentationVectorData.sqlite");
+ SetDocExampleParameterValue("mode","vector");
+ SetDocExampleParameterValue("mode.vector.out", "SegmentationVector.sqlite");
SetDocExampleParameterValue("filter", "watershed");
AddExample("Example of use with raster mode and mean-shift segmentation");
SetDocExampleParameterValue("in", "QB_Toulouse_Ortho_PAN.tif",1);
- SetDocExampleParameterValue("mode","normal",1);
- SetDocExampleParameterValue("mode.normal.lout", "SegmentationVectorData.tif uint16",1);
+ SetDocExampleParameterValue("mode","raster",1);
+ SetDocExampleParameterValue("mode.raster.out", "SegmentationRaster.tif uint16",1);
SetDocExampleParameterValue("filter", "meanshift",1);
}
@@ -321,20 +321,20 @@ private:
SegmentationFilterType> StreamingVectorizedSegmentationOGRType;
// Retrieve tile size parameter
- const unsigned int tileSize = static_cast<unsigned int> (this->GetParameterInt("mode.largescale.tilesize"));
+ const unsigned int tileSize = static_cast<unsigned int> (this->GetParameterInt("mode.vector.tilesize"));
// Retrieve the 8-connected option
- bool use8connected = IsParameterEnabled("mode.largescale.neighbor");
+ bool use8connected = IsParameterEnabled("mode.vector.neighbor");
// Retrieve min object size parameter
- const unsigned int minSize = static_cast<unsigned int> (this->GetParameterInt("mode.largescale.minsize"));
+ const unsigned int minSize = static_cast<unsigned int> (this->GetParameterInt("mode.vector.minsize"));
// Switch on segmentation mode
const std::string segModeType = (dynamic_cast <ChoiceParameter *> (this->GetParameterByKey("mode")))->GetChoiceKey(GetParameterInt("mode"));
streamingVectorizedFilter->SetInput(inputImage);
- if (HasValue("mode.largescale.inmask"))
+ if (HasValue("mode.vector.inmask"))
{
- streamingVectorizedFilter->SetInputMask(this->GetParameterUInt32Image("mode.largescale.inmask"));
+ streamingVectorizedFilter->SetInputMask(this->GetParameterUInt32Image("mode.vector.inmask"));
otbAppLogINFO(<<"Use a mask as input." << std::endl);
}
streamingVectorizedFilter->SetOGRDataSource(ogrDS);
@@ -361,20 +361,20 @@ private:
streamingVectorizedFilter->SetMinimumObjectSize(minSize);
}
- const std::string layerName = this->GetParameterString("mode.largescale.layername");
- const std::string fieldName = this->GetParameterString("mode.largescale.fieldname");
+ const std::string layerName = this->GetParameterString("mode.vector.layername");
+ const std::string fieldName = this->GetParameterString("mode.vector.fieldname");
// Retrieve start label parameter
- const unsigned int startLabel = this->GetParameterInt("mode.largescale.startlabel");
+ const unsigned int startLabel = this->GetParameterInt("mode.vector.startlabel");
streamingVectorizedFilter->SetLayerName(layerName);
streamingVectorizedFilter->SetFieldName(fieldName);
streamingVectorizedFilter->SetStartLabel(startLabel);
- if(IsParameterEnabled("mode.largescale.simplify"))
+ if(IsParameterEnabled("mode.vector.simplify"))
{
streamingVectorizedFilter->SetSimplify(true);
- streamingVectorizedFilter->SetSimplificationTolerance(GetParameterFloat("mode.largescale.simplify"));
+ streamingVectorizedFilter->SetSimplificationTolerance(GetParameterFloat("mode.vector.simplify"));
otbAppLogINFO(<<"Simplify the geometry." << std::endl);
}
else
@@ -382,7 +382,7 @@ private:
streamingVectorizedFilter->SetSimplify(false);
}
- if (segModeType == "largescale")
+ if (segModeType == "vector")
{
otbAppLogINFO(<<"Large scale segmentation mode which output vector data" << std::endl);
AddProcess(streamingVectorizedFilter->GetStreamer(), "Computing " + (dynamic_cast <ChoiceParameter *> (this->GetParameterByKey("filter")))->GetChoiceKey(GetParameterInt("filter")) + " segmentation");
@@ -390,14 +390,14 @@ private:
streamingVectorizedFilter->Initialize(); //must be called !
streamingVectorizedFilter->Update(); //must be called !
}
- else if (segModeType == "normal")
+ else if (segModeType == "raster")
{
otbAppLogINFO(<<"Segmentation mode which output label image" << std::endl);
streamingVectorizedFilter->GetSegmentationFilter()->SetInput(inputImage);
- SetParameterOutputImage<UInt32ImageType> ("mode.normal.lout", dynamic_cast<UInt32ImageType *> (streamingVectorizedFilter->GetSegmentationFilter()->GetOutputs().at(outputNb).GetPointer()));
- //TODO add progress reporting in normal mode
- // AddProcess(dynamic_cast <OutputImageParameter *> (GetParameterByKey("mode.normal.lout"))->GetWriter(),
+ SetParameterOutputImage<UInt32ImageType> ("mode.raster.out", dynamic_cast<UInt32ImageType *> (streamingVectorizedFilter->GetSegmentationFilter()->GetOutputs().at(outputNb).GetPointer()));
+ //TODO add progress reporting in raster mode
+ // AddProcess(dynamic_cast <OutputImageParameter *> (GetParameterByKey("mode.raster.out"))->GetWriter(),
// "Computing " + (dynamic_cast <ChoiceParameter *>
// (this->GetParameterByKey("filter")))->GetChoiceKey(GetParameterInt("filter"))
// + " segmentation");
@@ -415,10 +415,10 @@ private:
otb::ogr::DataSource::Pointer ogrDS;
- if(segModeType=="largescale")
+ if(segModeType=="vector")
{
// Retrieve output filename as well as layer names
- std::string dataSourceName = GetParameterString("mode.largescale.outvd");
+ std::string dataSourceName = GetParameterString("mode.vector.out");
ogrDS = otb::ogr::DataSource::New(dataSourceName, otb::ogr::DataSource::Modes::write);
}
@@ -431,9 +431,9 @@ private:
ConnectedComponentStreamingVectorizedSegmentationOGRType::Pointer
ccVectorizationFilter = ConnectedComponentStreamingVectorizedSegmentationOGRType::New();
- if (HasValue("mode.largescale.inmask"))
+ if (HasValue("mode.vector.inmask"))
{
- ccVectorizationFilter->GetSegmentationFilter()->SetMaskImage(this->GetParameterUInt32Image("mode.largescale.inmask"));
+ ccVectorizationFilter->GetSegmentationFilter()->SetMaskImage(this->GetParameterUInt32Image("mode.vector.inmask"));
}
ccVectorizationFilter->GetSegmentationFilter()->GetFunctor().SetExpression(
@@ -513,15 +513,15 @@ private:
otbAppLogFATAL(<<"non defined filtering method "<<GetParameterInt("filter")<<std::endl);
}
- if (segModeType == "largescale" )
+ if (segModeType == "vector" )
{
ogrDS->SyncToDisk();
// Stitching mode
- if(IsParameterEnabled("mode.largescale.stitch"))
+ if(IsParameterEnabled("mode.vector.stitch"))
{
otbAppLogINFO(<<"Segmentation done, stiching polygons ...");
- const std::string layerName = this->GetParameterString("mode.largescale.layername");
+ const std::string layerName = this->GetParameterString("mode.vector.layername");
FusionFilterType::Pointer fusionFilter = FusionFilterType::New();
fusionFilter->SetInput(GetParameterFloatVectorImage("in"));
@@ -533,7 +533,7 @@ private:
fusionFilter->GenerateData();
}
}
- else if (segModeType == "normal")
+ else if (segModeType == "raster")
{
otbAppLogINFO(<<"implementation in progress..." << std::endl);
}