HistogramMostPopulatedGL

Compute the intensity of the most populated class. More...

Classes
class	ipsdk::imaproc::shape::analysis::HistogramMostPopulatedGLMsr
	Measurement object for measure HistogramMostPopulatedGL. More...
class	ipsdk::imaproc::shape::analysis::HistogramMostPopulatedGLMsrInfo
	Information object for measure HistogramMostPopulatedGL. More...
class	ipsdk::imaproc::shape::analysis::HistogramMostPopulatedGLMsrParams
	Parameter object for measure HistogramMostPopulatedGL. More...

Detailed Description

Compute the intensity of the most populated class.

HistogramMostPopulatedGL computes, for given histogram parameters (bin width or number of classes, and the way to determine histogram minimal and maximal intensities), the mean grey level associated to the most populated class in the histogram computed on the shape.

Here is an example of histogram most populated grey level measurement in 2d case :

Author

H. Delestre

Date

2015/07/27

Copyright

2015 Reactiv'IP, all right reserved.

Compute the intensity of the most populated class

Measure synthesis :

Measure Type	Measure Unit Type	Parameter Type	Result Type	Shape Requirements
Generic	None	HistogramMostPopulatedGLMsrParams	Value (ipsdk::ipReal64)	Row Intersections

See Shape measurement for additional information on these pictograms

Measure Type :

This is a generic measure

• it does not directly use shape or image data
• it can use dependencies to other measures to compute a result (see Measure Dependencies section)

This measure can be used in 2d and 3d case

Measure Unit Type:

Measure HistogramMostPopulatedGL is not associated to any unit [ipsdk::shape::analysis::eMsrUnitFormat::eMUF_NoUnit]

Measure Parameter Type :

Measure HistogramMostPopulatedGL is associated to HistogramMostPopulatedGLMsrParams parameters

Measure Result Type :

Measure HistogramMostPopulatedGL is associated to ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64> results

Measure Shape Requirements :

Measure HistogramMostPopulatedGL requires row intersections from shape data

Measure Dependencies :

Measure HistogramMostPopulatedGL depends on following measures :

Measure Mode	Measure Name	Measure Type	Measure Parameters
eMVP_2d3d	HistogramMostPopulated	HistogramMostPopulated	createHistogramMostPopulatedMsrParams(_pMsrParams->getNode<HistogramMostPopulatedGLMsrParams::HistoParams>())

Note

See Shape Analysis 2d for more information on general shape 2d analysis and measurement usage.

See Shape Analysis 3d for more information on general shape 3d analysis and measurement usage.

Example of Python code :

Generic example in 2d case :

import PyIPSDK
import PyIPSDK.IPSDKIPLShapeAnalysis as shapeanalysis

    # Create the infoset
    inMeasureInfoSet2d = PyIPSDK.createMeasureInfoSet2d()
    PyIPSDK.createMeasureInfo(inMeasureInfoSet2d, "HistogramMostPopulatedGLMsr")
    
    #Perform the analysis
    outMeasureSet = shapeanalysis.labelAnalysis2d(inGreyImg, inLabelImg2d, inMeasureInfoSet2d)
    
    # save results to csv format
    PyIPSDK.saveCsvMeasureFile(os.path.join(tmpPath,  "shape_analysis_results.csv"), outMeasureSet)
    
    # retrieve measure results
    outMsr = outMeasureSet.getMeasure("HistogramMostPopulatedGLMsr")
    
    # retrieve measure values
    outMsrValues = outMsr.getMeasureResult().getColl(0)
    print("First label measurement equal " + str(outMsrValues[1]))

Generic example in 3d case :

import PyIPSDK
import PyIPSDK.IPSDKIPLShapeAnalysis as shapeanalysis

    # Create the infoset
    inMeasureInfoSet3d = PyIPSDK.createMeasureInfoSet3d()
    PyIPSDK.createMeasureInfo(inMeasureInfoSet3d, "HistogramMostPopulatedGLMsr")
    
    #Perform the analysis
    outMeasureSet = shapeanalysis.labelAnalysis3d(inGreyImg, inLabelImg, inMeasureInfoSet3d)
    
    # save results to csv format
    PyIPSDK.saveCsvMeasureFile(os.path.join(tmpPath,  "shape_analysis_results.csv"), outMeasureSet)
    
    # retrieve measure results
    outMsr = outMeasureSet.getMeasure("HistogramMostPopulatedGLMsr")
    
    # retrieve measure values
    outMsrValues = outMsr.getMeasureResult().getColl(0)
    print("First label measurement equal " + str(outMsrValues[1]))

Example of C++ code :

Example informations

Associated library

IPSDKIPLShapeAnalysis

Code Example

    // opening grey level input image
    ImagePtr pInGreyImg2d = loadTiffImageFile(inputGreyImgPath);

    // read entity shape 2d collection used for processing
    Shape2dCollPtr pShape2dColl = boost::make_shared<Shape2dColl>();
    readFromXmlFile(inputShape2dCollPath, *pShape2dColl);

    // define a measure info set
    MeasureInfoSetPtr pMeasureInfoSet = MeasureInfoSet::create2dInstance();

    HistogramMostPopulatedGLMsrParamsPtr pParams;
    switch(minMaxDef.value()) {
    case eMinMaxDefinition::eMMD_ImgMinMax:
        case eMinMaxDefinition::eMMD_ShapeMinMax:
        pParams = createHistogramMostPopulatedGLMsrParamsBinWidth(1.0);
        break;
    case eMinMaxDefinition::eMMD_UserDefinedMinMax:
        pParams = createHistogramMostPopulatedGLMsrParamsBinWidth(1.0, fMin.get(), fMax.get());
        break;
    }
    createMeasureInfo(pMeasureInfoSet, "HistogramMostPopulatedGLMsr", pParams);
    
    // compute measure on shape 2d collection
    MeasureSetPtr pOutMeasureSet = shapeAnalysis2d(pInGreyImg2d, pShape2dColl, pMeasureInfoSet);

    // retrieve associated results
    const MeasureConstPtr& pHistogramMostPopulatedGLOutMsr = pOutMeasureSet->getMeasure("HistogramMostPopulatedGLMsr");
    const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64>& outResults = static_cast<const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipReal64>&>(pHistogramMostPopulatedGLOutMsr->getMeasureResult());