LabelFilteringAnalysis

Computes measurements on objects and filters them from a label image.

Access to parameter description

For an introduction:

section Image Analysis
section Label Filtering

This algorithm is similar to the LabelAnalysis algorithm except that it applies a filter formula with its criteria to the analyzed image. Then it outputs the filtered label image and the corresponding analysis result object.

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 = nullptr,
                        std::shared_ptr< iolink::ImageView > outputLabelImage = nullptr );

This function returns a tuple containing output_analysis and output_label_image.

// Function prototype.
label_filtering_analysis(input_label_image: idt.ImageType,
                         input_intensity_image: idt.ImageType,
                         input_filter: str = "",
                         output_analysis: Union[Any, None] = None,
                         output_label_image: idt.ImageType = None) -> Tuple[AnalysisMsr, idt.ImageType]

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

// Command constructor.
LabelFilteringAnalysis();

/// Gets the inputLabelImage parameter.
/// The label input image
std::shared_ptr< iolink::ImageView > inputLabelImage() const;
/// Sets the inputLabelImage parameter.
/// The label input image
void setInputLabelImage( std::shared_ptr< iolink::ImageView > inputLabelImage );

/// Gets the inputIntensityImage parameter.
/// The intensity input image. If it equals null, the label input image will be used as the intensity input image.
std::shared_ptr< iolink::ImageView > inputIntensityImage() const;
/// Sets the inputIntensityImage parameter.
/// The intensity input image. If it equals null, the label input image will be used as the intensity input image.
void setInputIntensityImage( std::shared_ptr< iolink::ImageView > inputIntensityImage );

/// Gets the inputFilter parameter.
/// The input filter formula.
std::string inputFilter() const;
/// Sets the inputFilter parameter.
/// The input filter formula.
void setInputFilter( const std::string& inputFilter );

/// Gets the outputAnalysis parameter.
/// The output analysis.
AnalysisMsr::Ptr outputAnalysis() const;
/// Sets the outputAnalysis parameter.
/// The output analysis.
void setOutputAnalysis( AnalysisMsr::Ptr outputAnalysis );

/// Gets the outputLabelImage parameter.
/// The output label image. Its dimensions and type are forced to the same values as the input.
std::shared_ptr< iolink::ImageView > outputLabelImage() const;
/// Sets the outputLabelImage parameter.
/// The output label image. Its dimensions and type are forced to the same values as the input.
void setOutputLabelImage( std::shared_ptr< iolink::ImageView > outputLabelImage );


// Method to launch the command.
void execute();

# Property of the inputLabelImage parameter.
LabelFilteringAnalysis.input_label_image
# Property of the inputIntensityImage parameter.
LabelFilteringAnalysis.input_intensity_image
# Property of the inputFilter parameter.
LabelFilteringAnalysis.input_filter
# Property of the outputAnalysis parameter.
LabelFilteringAnalysis.output_analysis
# Property of the outputLabelImage parameter.
LabelFilteringAnalysis.output_label_image

// Method to launch the command.
execute()

// Command constructor.
LabelFilteringAnalysis()

// Property of the inputLabelImage parameter.
LabelFilteringAnalysis.inputLabelImage
// Property of the inputIntensityImage parameter.
LabelFilteringAnalysis.inputIntensityImage
// Property of the inputFilter parameter.
LabelFilteringAnalysis.inputFilter
// Property of the outputAnalysis parameter.
LabelFilteringAnalysis.outputAnalysis
// Property of the outputLabelImage parameter.
LabelFilteringAnalysis.outputLabelImage

// Method to launch the command.
Execute()

Parameters

	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

	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

	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" );
auto 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" );
auto 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() );