LabelFilteringAnalysis
Computes measurements on objects and filters them from a label image.
Access to parameter description
For an introduction:
The input filter contains the criteria to preserve objects from the input label image. These criteria are defined by one or several analysis measurements ranges.
If the label input image has a coordinate system unit defined in its calibration property, the filter limit values and analysis results are expressed in this coordinate system unit.
See also
Access to parameter description
For an introduction:
- section Image Analysis
- section Label Filtering
The input filter contains the criteria to preserve objects from the input label image. These criteria are defined by one or several analysis measurements ranges.
If the label input image has a coordinate system unit defined in its calibration property, the filter limit values and analysis results are expressed in this coordinate system unit.
See also
Function Syntax
This function returns a LabelFilteringAnalysisOutput structure containing outputAnalysis and outputLabelImage.
// Output structure of the labelFilteringAnalysis function. struct LabelFilteringAnalysisOutput { /// The output label image. Its dimensions and type are forced to the same values as the input. std::shared_ptr< iolink::ImageView > outputLabelImage; /// The output analysis. AnalysisMsr::Ptr outputAnalysis; }; // Function prototype
LabelFilteringAnalysisOutput labelFilteringAnalysis( std::shared_ptr< iolink::ImageView > inputLabelImage, std::shared_ptr< iolink::ImageView > inputIntensityImage, std::string inputFilter, AnalysisMsr::Ptr outputAnalysis = NULL, std::shared_ptr< iolink::ImageView > outputLabelImage = NULL );
This function returns a tuple containing output_analysis and output_label_image.
// Function prototype. label_filtering_analysis( input_label_image, input_intensity_image, input_filter = "", output_analysis = None, output_label_image = None )
This function returns a LabelFilteringAnalysisOutput structure containing outputAnalysis and outputLabelImage.
/// Output structure of the LabelFilteringAnalysis function. public struct LabelFilteringAnalysisOutput { /// /// The output label image. Its dimensions and type are forced to the same values as the input. /// public IOLink.ImageView outputLabelImage; /// The output analysis. public AnalysisMsr outputAnalysis; }; // Function prototype. public static LabelFilteringAnalysisOutput LabelFilteringAnalysis( IOLink.ImageView inputLabelImage, IOLink.ImageView inputIntensityImage, string inputFilter = "", AnalysisMsr outputAnalysis = null, IOLink.ImageView outputLabelImage = null );
Class Syntax
Parameters
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
inputLabelImage |
The label input image | Image | Label | nullptr | |
inputIntensityImage |
The intensity input image. If it equals null, the label input image will be used as the intensity input image. | Image | Binary, Label, Grayscale or Multispectral | nullptr | |
inputFilter |
The input filter formula.
The Label Filtering section details how to create a filter. |
Filter | "" | ||
outputLabelImage |
The output label image. Its dimensions and type are forced to the same values as the input. | Image | nullptr | ||
outputAnalysis |
The output analysis. | AnalysisMsr | nullptr |
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
input_label_image |
The label input image | image | Label | None | |
input_intensity_image |
The intensity input image. If it equals null, the label input image will be used as the intensity input image. | image | Binary, Label, Grayscale or Multispectral | None | |
input_filter |
The input filter formula.
The Label Filtering section details how to create a filter. |
filter | "" | ||
output_label_image |
The output label image. Its dimensions and type are forced to the same values as the input. | image | None | ||
output_analysis |
The output analysis. | AnalysisMsr | None |
Parameter Name | Description | Type | Supported Values | Default Value | |
---|---|---|---|---|---|
inputLabelImage |
The label input image | Image | Label | null | |
inputIntensityImage |
The intensity input image. If it equals null, the label input image will be used as the intensity input image. | Image | Binary, Label, Grayscale or Multispectral | null | |
inputFilter |
The input filter formula.
The Label Filtering section details how to create a filter. |
Filter | "" | ||
outputLabelImage |
The output label image. Its dimensions and type are forced to the same values as the input. | Image | null | ||
outputAnalysis |
The output analysis. | AnalysisMsr | null |
Object Examples
auto polystyrene_sep_label = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene_sep_label.vip" ); std::shared_ptr< iolink::ImageView > polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" ); AnalysisMsr::Ptr analysis= AnalysisMsr::read( std::string( IMAGEDEVDATA_OBJECTS_FOLDER ) + "analysis.vip" ); LabelFilteringAnalysis labelFilteringAnalysisAlgo; labelFilteringAnalysisAlgo.setInputLabelImage( polystyrene_sep_label ); labelFilteringAnalysisAlgo.setInputIntensityImage( polystyrene ); labelFilteringAnalysisAlgo.setInputFilter( "Area>=3000" ); labelFilteringAnalysisAlgo.setOutputAnalysis( analysis ); labelFilteringAnalysisAlgo.execute(); std::cout << "Area2d: " << labelFilteringAnalysisAlgo.outputAnalysis()->get( NativeMeasurements::area2d )->value( 0 ) ; std::cout << "outputLabelImage:" << labelFilteringAnalysisAlgo.outputLabelImage()->toString();
polystyrene_sep_label = imagedev.read_vip_image(imagedev_data.get_image_path("polystyrene_sep_label.vip")) polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif")) analysis = imagedev.AnalysisMsr.read(imagedev_data.get_object_path("analysis.vip")) label_filtering_analysis_algo = imagedev.LabelFilteringAnalysis() label_filtering_analysis_algo.input_label_image = polystyrene_sep_label label_filtering_analysis_algo.input_intensity_image = polystyrene label_filtering_analysis_algo.input_filter = "Area>=3000" label_filtering_analysis_algo.output_analysis = analysis label_filtering_analysis_algo.execute() print( "Area2d: ", str( label_filtering_analysis_algo.output_analysis.get(imagedev.native_measurements.Area2d).value( 0 ) ) ) print( "output_label_image:", str( label_filtering_analysis_algo.output_label_image ) )
ImageView polystyrene_sep_label = Data.ReadVipImage( @"Data/images/polystyrene_sep_label.vip" ); ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" ); AnalysisMsr analysis = AnalysisMsr.Read( @"Data/objects/analysis.vip" ); LabelFilteringAnalysis labelFilteringAnalysisAlgo = new LabelFilteringAnalysis { inputLabelImage = polystyrene_sep_label, inputIntensityImage = polystyrene, inputFilter = "Area>=3000", outputAnalysis = analysis }; labelFilteringAnalysisAlgo.Execute(); Console.WriteLine( "Area2d: " + labelFilteringAnalysisAlgo.outputAnalysis.Get( NativeMeasurements.Area2d ).Value( 0 ) ); Console.WriteLine( "outputLabelImage:" + labelFilteringAnalysisAlgo.outputLabelImage.ToString() );
Function Examples
auto polystyrene_sep_label = readVipImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene_sep_label.vip" ); std::shared_ptr< iolink::ImageView > polystyrene = ioformat::readImage( std::string( IMAGEDEVDATA_IMAGES_FOLDER ) + "polystyrene.tif" ); AnalysisMsr::Ptr analysis= AnalysisMsr::read( std::string( IMAGEDEVDATA_OBJECTS_FOLDER ) + "analysis.vip" ); auto result = labelFilteringAnalysis( polystyrene_sep_label, polystyrene, "Area>=3000", analysis ); std::cout << "Area2d: " << result.outputAnalysis->get( NativeMeasurements::area2d )->value( 0 ) ; std::cout << "outputLabelImage:" << result.outputLabelImage->toString();
polystyrene_sep_label = imagedev.read_vip_image(imagedev_data.get_image_path("polystyrene_sep_label.vip")) polystyrene = ioformat.read_image(imagedev_data.get_image_path("polystyrene.tif")) analysis = imagedev.AnalysisMsr.read(imagedev_data.get_object_path("analysis.vip")) result_output_analysis, result_output_label_image = imagedev.label_filtering_analysis( polystyrene_sep_label, polystyrene, "Area>=3000", analysis ) print( "Area2d: ", str( result_output_analysis.get(imagedev.native_measurements.Area2d).value( 0 ) ) ) print( "output_label_image:", str( result_output_label_image ) )
ImageView polystyrene_sep_label = Data.ReadVipImage( @"Data/images/polystyrene_sep_label.vip" ); ImageView polystyrene = ViewIO.ReadImage( @"Data/images/polystyrene.tif" ); AnalysisMsr analysis = AnalysisMsr.Read( @"Data/objects/analysis.vip" ); Processing.LabelFilteringAnalysisOutput result = Processing.LabelFilteringAnalysis( polystyrene_sep_label, polystyrene, "Area>=3000", analysis ); Console.WriteLine( "Area2d: " + result.outputAnalysis.Get( NativeMeasurements.Area2d ).Value( 0 ) ); Console.WriteLine( "outputLabelImage:" + result.outputLabelImage.ToString() );