Number of neighbors

measure allowing to compute number of neighbors of shapes given a distance threshold More...

Classes
class	ipsdk::imaproc::shape::analysis::NbNeighborsMsr
	Measurement object for measure NbNeighbors. More...
class	ipsdk::imaproc::shape::analysis::NbNeighborsMsrInfo
	Information object for measure NbNeighbors. More...

Typedefs
typedef ipsdk::imaproc::shape::analysis::NeighborsDistanceMsrParams	ipsdk::imaproc::shape::analysis::NbNeighborsMsrParams
	parameters type associated to measure

Detailed Description

measure allowing to compute number of neighbors of shapes given a distance threshold

This measure allows to compute number of neighbors of a shape given a user parameter distance threshold MaxDist (we count shapes for which distance is lower or equal to this value). It is based on a geometric analysis of shape neighborhood.

Parameter flag ProcessHoles allows to specify whether shape holes should be taken into account during computation. Please see Distance to nearest neighbor 2d for an explanation of effects of this flag.

Please refer to documentation of following measures for more information :

• Nearest neighbors 2d
• Nearest neighbors 3d

Author

E.Noirfalise

Date

2017/07/27

Copyright

2017 Reactiv'IP, all right reserved.

measure allowing to compute number of neighbors of shapes given a distance threshold

Measure synthesis :

Measure Type	Measure Unit Type	Parameter Type	Result Type	Shape Requirements
Generic	None	NbNeighborsMsrParams	Value (ipsdk::ipUInt32)	Boundary Approximation

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

Measure Parameter Type :

Measure NbNeighbors is associated to NbNeighborsMsrParams parameters

Measure Result Type :

Measure NbNeighbors is associated to ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipUInt32> results

Measure Shape Requirements :

Measure NbNeighbors requires boundary approximation from shape data

Measure Dependencies :

Measure NbNeighbors depends on following measures :

Measure Mode	Measure Name	Measure Type	Measure Parameters
eMVP_2d	NearestNeighbors	NearestNeighbors2d	boost::make_shared<NeighborsDistanceMsrParams>(*_pMsrParams)
eMVP_3d	NearestNeighbors	NearestNeighbors3d	boost::make_shared<NeighborsDistanceMsrParams>(*_pMsrParams)

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, "NbNeighborsMsr")
    
    #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("NbNeighborsMsr")
    
    # 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, "NbNeighborsMsr")
    
    #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("NbNeighborsMsr")
    
    # 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>();
    IPSDK_REQUIRE(readFromXmlFile(inputShape2dCollPath, *pShape2dColl) == true);

    // define a measure info set
    MeasureInfoSetPtr pMeasureInfoSet = MeasureInfoSet::create2dInstance();
    createMeasureInfo(pMeasureInfoSet, "NbNeighborsMsr", createNeighborsDistanceMsrParams(maxDist, bProcessHoles));
    
    // compute measure on shape 2d collection
    MeasureSetPtr pOutMeasureSet = shapeAnalysis2d(pInGreyImg2d, pShape2dColl, pMeasureInfoSet);

    // retrieve associated results
    const MeasureConstPtr& pNbNeighborsOutMsr = pOutMeasureSet->getMeasure("NbNeighborsMsr");
    const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipUInt32>& outResults = static_cast<const ipsdk::shape::analysis::ValueMeasureResult<ipsdk::ipUInt32>&>(pNbNeighborsOutMsr->getMeasureResult());