OpenCV  4.9.0-dev
Open Source Computer Vision
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cv::FaceRecognizerSF Class Referenceabstract

DNN-based face recognizer. More...

#include <opencv2/objdetect/face.hpp>

Collaboration diagram for cv::FaceRecognizerSF:

Public Types

enum  DisType {
  FR_COSINE =0 ,
  FR_NORM_L2 =1
 Definition of distance used for calculating the distance between two face features. More...

Public Member Functions

virtual ~FaceRecognizerSF ()
virtual void alignCrop (InputArray src_img, InputArray face_box, OutputArray aligned_img) const =0
 Aligning image to put face on the standard position.
virtual void feature (InputArray aligned_img, OutputArray face_feature)=0
 Extracting face feature from aligned image.
virtual double match (InputArray face_feature1, InputArray face_feature2, int dis_type=FaceRecognizerSF::FR_COSINE) const =0
 Calculating the distance between two face features.

Static Public Member Functions

static Ptr< FaceRecognizerSFcreate (CV_WRAP_FILE_PATH const String &model, CV_WRAP_FILE_PATH const String &config, int backend_id=0, int target_id=0)
 Creates an instance of this class with given parameters.

Detailed Description

DNN-based face recognizer.

model download link:

Member Enumeration Documentation

◆ DisType

Definition of distance used for calculating the distance between two face features.


Constructor & Destructor Documentation

◆ ~FaceRecognizerSF()

virtual cv::FaceRecognizerSF::~FaceRecognizerSF ( )

Member Function Documentation

◆ alignCrop()

virtual void cv::FaceRecognizerSF::alignCrop ( InputArray  src_img,
InputArray  face_box,
OutputArray  aligned_img 
) const
pure virtual
cv.FaceRecognizerSF.alignCrop(src_img, face_box[, aligned_img]) -> aligned_img

Aligning image to put face on the standard position.

src_imginput image
face_boxthe detection result used for indicate face in input image
aligned_imgoutput aligned image

◆ create()

static Ptr< FaceRecognizerSF > cv::FaceRecognizerSF::create ( CV_WRAP_FILE_PATH const String model,
CV_WRAP_FILE_PATH const String config,
int  backend_id = 0,
int  target_id = 0 
cv.FaceRecognizerSF.create(model, config[, backend_id[, target_id]]) -> retval
cv.FaceRecognizerSF_create(model, config[, backend_id[, target_id]]) -> retval

Creates an instance of this class with given parameters.

modelthe path of the onnx model used for face recognition
configthe path to the config file for compability, which is not requested for ONNX models
backend_idthe id of backend
target_idthe id of target device

◆ feature()

virtual void cv::FaceRecognizerSF::feature ( InputArray  aligned_img,
OutputArray  face_feature 
pure virtual
cv.FaceRecognizerSF.feature(aligned_img[, face_feature]) -> face_feature

Extracting face feature from aligned image.

aligned_imginput aligned image
face_featureoutput face feature

◆ match()

virtual double cv::FaceRecognizerSF::match ( InputArray  face_feature1,
InputArray  face_feature2,
int  dis_type = FaceRecognizerSF::FR_COSINE 
) const
pure virtual
cv.FaceRecognizerSF.match(face_feature1, face_feature2[, dis_type]) -> retval

Calculating the distance between two face features.

face_feature1the first input feature
face_feature2the second input feature of the same size and the same type as face_feature1
dis_typedefining the similarity with optional values "FR_OSINE" or "FR_NORM_L2"

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