OpenCV for Unity 2.6.5
Enox Software / Please refer to OpenCV official document ( http://docs.opencv.org/4.10.0/index.html ) for the details of the argument of the method.
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Static Public Member Functions | Protected Member Functions | List of all members
OpenCVForUnity.FaceModule.FisherFaceRecognizer Class Reference

Static Public Member Functions

static new FisherFaceRecognizer __fromPtr__ (IntPtr addr)
 
static FisherFaceRecognizer create ()
 
static FisherFaceRecognizer create (int num_components)
 
static FisherFaceRecognizer create (int num_components, double threshold)
 
- Static Public Member Functions inherited from OpenCVForUnity.FaceModule.BasicFaceRecognizer
static new BasicFaceRecognizer __fromPtr__ (IntPtr addr)
 
- Static Public Member Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
static new FaceRecognizer __fromPtr__ (IntPtr addr)
 
- Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
static Algorithm __fromPtr__ (IntPtr addr)
 
- Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr ThrowIfNullIntPtr (IntPtr ptr)
 

Protected Member Functions

override void Dispose (bool disposing)
 
- Protected Member Functions inherited from OpenCVForUnity.FaceModule.BasicFaceRecognizer
- Protected Member Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
- Protected Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
- Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
 DisposableOpenCVObject ()
 
 DisposableOpenCVObject (bool isEnabledDispose)
 
 DisposableOpenCVObject (IntPtr ptr)
 
 DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)
 
- Protected Member Functions inherited from OpenCVForUnity.DisposableObject
 DisposableObject ()
 
 DisposableObject (bool isEnabledDispose)
 

Additional Inherited Members

- Public Member Functions inherited from OpenCVForUnity.FaceModule.BasicFaceRecognizer
Mat getEigenValues ()
 
Mat getEigenVectors ()
 
Mat getLabels ()
 
Mat getMean ()
 
int getNumComponents ()
 
List< Mat > getProjections ()
 
double getThreshold ()
 
void setNumComponents (int val)
 
void setThreshold (double val)
 
- Public Member Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
string getLabelInfo (int label)
 Gets string information by label.
 
MatOfInt getLabelsByString (string str)
 Gets vector of labels by string.
 
void predict (Mat src, int[] label, double[] confidence)
 Predicts a label and associated confidence (e.g. distance) for a given input image.
 
void predict_collect (Mat src, PredictCollector collector)
 
int predict_label (Mat src)
 
void read (string filename)
 Loads a FaceRecognizer and its model state.
 
void setLabelInfo (int label, string strInfo)
 Sets string info for the specified model's label.
 
void train (List< Mat > src, Mat labels)
 Trains a FaceRecognizer with given data and associated labels.
 
void update (List< Mat > src, Mat labels)
 Updates a FaceRecognizer with given data and associated labels.
 
void write (string filename)
 Saves a FaceRecognizer and its model state.
 
- Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
virtual void clear ()
 Clears the algorithm state.
 
virtual bool empty ()
 Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
 
virtual string getDefaultName ()
 
IntPtr getNativeObjAddr ()
 
void save (string filename)
 
- Public Member Functions inherited from OpenCVForUnity.DisposableObject
void Dispose ()
 
void ThrowIfDisposed ()
 
- Package Functions inherited from OpenCVForUnity.FaceModule.BasicFaceRecognizer
- Package Functions inherited from OpenCVForUnity.FaceModule.FaceRecognizer
- Package Functions inherited from OpenCVForUnity.CoreModule.Algorithm
- Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject
- Properties inherited from OpenCVForUnity.DisposableObject
bool IsDisposed [get, protected set]
 
bool IsEnabledDispose [get, set]
 

Member Function Documentation

◆ __fromPtr__()

static new FisherFaceRecognizer OpenCVForUnity.FaceModule.FisherFaceRecognizer.__fromPtr__ ( IntPtr addr)
static

◆ create() [1/3]

static FisherFaceRecognizer OpenCVForUnity.FaceModule.FisherFaceRecognizer.create ( )
static
Parameters
num_componentsThe number of components (read: Fisherfaces) kept for this Linear Discriminant Analysis with the Fisherfaces criterion. It's useful to keep all components, that means the number of your classes c (read: subjects, persons you want to recognize). If you leave this at the default (0) or set it to a value less-equal 0 or greater (c-1), it will be set to the correct number (c-1) automatically.
thresholdThe threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

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

Model internal data:

  • num_components see FisherFaceRecognizer.create.
  • threshold see FisherFaceRecognizer.create.
  • eigenvalues The eigenvalues for this Linear Discriminant Analysis (ordered descending).
  • eigenvectors The eigenvectors for this Linear Discriminant Analysis (ordered by their eigenvalue).
  • mean The sample mean calculated from the training data.
  • projections The projections of the training data.
  • labels The labels corresponding to the projections.

◆ create() [2/3]

static FisherFaceRecognizer OpenCVForUnity.FaceModule.FisherFaceRecognizer.create ( int num_components)
static
Parameters
num_componentsThe number of components (read: Fisherfaces) kept for this Linear Discriminant Analysis with the Fisherfaces criterion. It's useful to keep all components, that means the number of your classes c (read: subjects, persons you want to recognize). If you leave this at the default (0) or set it to a value less-equal 0 or greater (c-1), it will be set to the correct number (c-1) automatically.
thresholdThe threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

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

Model internal data:

  • num_components see FisherFaceRecognizer.create.
  • threshold see FisherFaceRecognizer.create.
  • eigenvalues The eigenvalues for this Linear Discriminant Analysis (ordered descending).
  • eigenvectors The eigenvectors for this Linear Discriminant Analysis (ordered by their eigenvalue).
  • mean The sample mean calculated from the training data.
  • projections The projections of the training data.
  • labels The labels corresponding to the projections.

◆ create() [3/3]

static FisherFaceRecognizer OpenCVForUnity.FaceModule.FisherFaceRecognizer.create ( int num_components,
double threshold )
static
Parameters
num_componentsThe number of components (read: Fisherfaces) kept for this Linear Discriminant Analysis with the Fisherfaces criterion. It's useful to keep all components, that means the number of your classes c (read: subjects, persons you want to recognize). If you leave this at the default (0) or set it to a value less-equal 0 or greater (c-1), it will be set to the correct number (c-1) automatically.
thresholdThe threshold applied in the prediction. If the distance to the nearest neighbor is larger than the threshold, this method returns -1.

Notes:

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

Model internal data:

  • num_components see FisherFaceRecognizer.create.
  • threshold see FisherFaceRecognizer.create.
  • eigenvalues The eigenvalues for this Linear Discriminant Analysis (ordered descending).
  • eigenvectors The eigenvectors for this Linear Discriminant Analysis (ordered by their eigenvalue).
  • mean The sample mean calculated from the training data.
  • projections The projections of the training data.
  • labels The labels corresponding to the projections.

◆ Dispose()

override void OpenCVForUnity.FaceModule.FisherFaceRecognizer.Dispose ( bool disposing)
protectedvirtual

Reimplemented from OpenCVForUnity.FaceModule.BasicFaceRecognizer.

The documentation for this class was generated from the following file:
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