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Class EigenFaceRecognizer

Training and prediction must be done on grayscale images, use cvtColor to convert between the color spaces.

  • **THE EIGENFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL SIZE. ** (caps-lock, because I got so many mails asking for this). You have to make sure your input data has the correct shape, else a meaningful exception is thrown.Use resize to resize the images.
  • This model does not support updating.
Inheritance
System.Object
DisposableObject
DisposableCvObject
Algorithm
FaceRecognizer
BasicFaceRecognizer
EigenFaceRecognizer
Implements
ICvPtrHolder
Inherited Members
BasicFaceRecognizer.GetNumComponents()
BasicFaceRecognizer.SetNumComponents(Int32)
BasicFaceRecognizer.GetThreshold()
BasicFaceRecognizer.SetThreshold(Double)
BasicFaceRecognizer.GetProjections()
BasicFaceRecognizer.GetLabels()
BasicFaceRecognizer.GetEigenValues()
BasicFaceRecognizer.GetEigenVectors()
BasicFaceRecognizer.GetMean()
FaceRecognizer.Train(IEnumerable<Mat>, IEnumerable<Int32>)
FaceRecognizer.Update(IEnumerable<Mat>, IEnumerable<Int32>)
FaceRecognizer.Predict(InputArray)
FaceRecognizer.Predict(InputArray, Int32, Double)
FaceRecognizer.Write(String)
FaceRecognizer.Read(String)
FaceRecognizer.Write(FileStorage)
FaceRecognizer.Read(FileNode)
FaceRecognizer.SetLabelInfo(Int32, String)
FaceRecognizer.GetLabelInfo(Int32)
FaceRecognizer.GetLabelsByString(String)
Algorithm.Empty
Algorithm.Save(String)
Algorithm.GetDefaultName()
DisposableCvObject.ptr
DisposableCvObject.CvPtr
DisposableObject.DataHandle
DisposableObject.IsDisposed
DisposableObject.IsEnabledDispose
DisposableObject.AllocatedMemory
DisposableObject.AllocatedMemorySize
DisposableObject.Dispose()
DisposableObject.Dispose(Boolean)
DisposableObject.AllocGCHandle(Object)
DisposableObject.AllocMemory(Int32)
DisposableObject.NotifyMemoryPressure(Int64)
DisposableObject.ThrowIfDisposed()
Namespace: OpenCvSharp.Face
Assembly: OpenCvSharp.dll
Syntax
public class EigenFaceRecognizer : BasicFaceRecognizer, ICvPtrHolder

Constructors

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EigenFaceRecognizer()

Declaration
protected EigenFaceRecognizer()

Methods

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Create(Int32, Double)

Training and prediction must be done on grayscale images, use cvtColor to convert between the color spaces.

  • **THE EIGENFACES METHOD MAKES THE ASSUMPTION, THAT THE TRAINING AND TEST IMAGES ARE OF EQUAL SIZE. ** (caps-lock, because I got so many mails asking for this). You have to make sure your input data has the correct shape, else a meaningful exception is thrown.Use resize to resize the images.
  • This model does not support updating.
Declaration
public static EigenFaceRecognizer Create(int numComponents = 0, double threshold = 1.7976931348623157E+308)
Parameters
Type Name Description
System.Int32 numComponents

The number of components (read: Eigenfaces) kept for this Principal Component Analysis. As a hint: There's no rule how many components (read: Eigenfaces) should be kept for good reconstruction capabilities. It is based on your input data, so experiment with the number. Keeping 80 components should almost always be sufficient.

System.Double threshold

The threshold applied in the prediction.

Returns
Type Description
EigenFaceRecognizer
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DisposeManaged()

Releases managed resources

Declaration
protected override void DisposeManaged()
Overrides
DisposableObject.DisposeManaged()
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DisposeUnmanaged()

Declaration
protected override void DisposeUnmanaged()
Overrides
DisposableCvObject.DisposeUnmanaged()
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Get()

Declaration
public override IntPtr Get()
Returns
Type Description
IntPtr

Implements

ICvPtrHolder
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