| FisherFaceRecognizerCreate Method |
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.
Namespace:
OpenCvSharp.Face
Assembly:
OpenCvSharp (in OpenCvSharp.dll) Version: 1.0.0
Syntax public static FisherFaceRecognizer Create(
int numComponents = 0,
double threshold = 1.79769313486232E+308
)
Public Shared Function Create (
Optional numComponents As Integer = 0,
Optional threshold As Double = 1.79769313486232E+308
) As FisherFaceRecognizer
public:
static FisherFaceRecognizer^ Create(
int numComponents = 0,
double threshold = 1.79769313486232E+308
)
static member Create :
?numComponents : int *
?threshold : float
(* Defaults:
let _numComponents = defaultArg numComponents 0
let _threshold = defaultArg threshold 1.79769313486232E+308
*)
-> FisherFaceRecognizer
Parameters
- numComponents (Optional)
- Type: SystemInt32
The 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. - threshold (Optional)
- Type: SystemDouble
The threshold applied in the prediction. If the distance to the nearest neighbor
is larger than the threshold, this method returns -1.
Return Value
Type:
FisherFaceRecognizer[Missing <returns> documentation for "M:OpenCvSharp.Face.FisherFaceRecognizer.Create(System.Int32,System.Double)"]
See Also