Class EigenFaceRecognizer

Namespace

OpenCvSharp.Face

Assembly

OpenCvSharp.dll

base for two FaceRecognizer classes

public class EigenFaceRecognizer : BasicFaceRecognizer, IDisposable, ICvPtrHolder

Inheritance

object

DisposableObject

DisposableCvObject

Algorithm

FaceRecognizer

BasicFaceRecognizer

EigenFaceRecognizer

Implements

IDisposable

ICvPtrHolder

Inherited Members

BasicFaceRecognizer.GetNumComponents()

BasicFaceRecognizer.SetNumComponents(int)

BasicFaceRecognizer.GetThreshold()

BasicFaceRecognizer.SetThreshold(double)

BasicFaceRecognizer.GetProjections()

BasicFaceRecognizer.GetLabels()

BasicFaceRecognizer.GetEigenValues()

BasicFaceRecognizer.GetEigenVectors()

BasicFaceRecognizer.GetMean()

FaceRecognizer.Train(IEnumerable<Mat>, IEnumerable<int>)

FaceRecognizer.Update(IEnumerable<Mat>, IEnumerable<int>)

FaceRecognizer.Predict(InputArray)

FaceRecognizer.Predict(InputArray, out int, out double)

FaceRecognizer.Write(string)

FaceRecognizer.Read(string)

FaceRecognizer.Write(FileStorage)

FaceRecognizer.Read(FileNode)

FaceRecognizer.SetLabelInfo(int, string)

FaceRecognizer.GetLabelInfo(int)

FaceRecognizer.GetLabelsByString(string)

Algorithm.Empty

Algorithm.Save(string)

Algorithm.GetDefaultName()

DisposableCvObject.ptr

DisposableCvObject.DisposeUnmanaged()

DisposableCvObject.CvPtr

DisposableObject.DataHandle

DisposableObject.IsDisposed

DisposableObject.IsEnabledDispose

DisposableObject.AllocatedMemory

DisposableObject.AllocatedMemorySize

DisposableObject.Dispose()

DisposableObject.Dispose(bool)

DisposableObject.AllocGCHandle(object)

DisposableObject.AllocMemory(int)

DisposableObject.NotifyMemoryPressure(long)

DisposableObject.ThrowIfDisposed()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

EigenFaceRecognizer()

protected EigenFaceRecognizer()

Methods

Create(int, 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.

public static EigenFaceRecognizer Create(int numComponents = 0, double threshold = 1.7976931348623157E+308)

Parameters

numComponents int

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.

threshold double

The threshold applied in the prediction.

Returns

EigenFaceRecognizer

DisposeManaged()

Releases managed resources

protected override void DisposeManaged()