Struct FaceRecognizerSF

pub struct FaceRecognizerSF { /* private fields */ }

DNN-based face recognizer

model download link: https://github.com/opencv/opencv_zoo/tree/master/models/face_recognition_sface

Implementations

impl FaceRecognizerSF

pub fn create( model: &str, config: &str, backend_id: i32, target_id: i32, ) -> Result<Ptr<FaceRecognizerSF>>

Creates an instance of this class with given parameters

Parameters

• model: the path of the onnx model used for face recognition
• config: the path to the config file for compability, which is not requested for ONNX models
• backend_id: the id of backend
• target_id: the id of target device

C++ default parameters

• backend_id: 0
• target_id: 0

pub fn create_def(model: &str, config: &str) -> Result<Ptr<FaceRecognizerSF>>

Creates an instance of this class with given parameters

Parameters

• model: the path of the onnx model used for face recognition
• config: the path to the config file for compability, which is not requested for ONNX models
• backend_id: the id of backend
• target_id: the id of target device

Note

This alternative version of FaceRecognizerSF::create function uses the following default values for its arguments:

• backend_id: 0
• target_id: 0

pub fn create_1( framework: &str, buffer_model: &Vector<u8>, buffer_config: &Vector<u8>, backend_id: i32, target_id: i32, ) -> Result<Ptr<FaceRecognizerSF>>

Creates an instance of this class from a buffer containing the model weights and configuration.

Parameters

• framework: Name of the framework (ONNX, etc.)
• bufferModel: A buffer containing the binary model weights.
• bufferConfig: A buffer containing the network configuration.
• backend_id: The id of the backend.
• target_id: The id of the target device.

Returns

A pointer to the created instance of FaceRecognizerSF.

C++ default parameters

• backend_id: 0
• target_id: 0

pub fn create_def_1( framework: &str, buffer_model: &Vector<u8>, buffer_config: &Vector<u8>, ) -> Result<Ptr<FaceRecognizerSF>>

Creates an instance of this class from a buffer containing the model weights and configuration.

Parameters

• framework: Name of the framework (ONNX, etc.)
• bufferModel: A buffer containing the binary model weights.
• bufferConfig: A buffer containing the network configuration.
• backend_id: The id of the backend.
• target_id: The id of the target device.

Returns

A pointer to the created instance of FaceRecognizerSF.

Note

This alternative version of FaceRecognizerSF::create function uses the following default values for its arguments:

• backend_id: 0
• target_id: 0

Trait Implementations

impl Boxed for FaceRecognizerSF

unsafe fn from_raw( ptr: <FaceRecognizerSF as OpenCVFromExtern>::ExternReceive, ) -> Self

Wrap the specified raw pointer

fn into_raw( self, ) -> <FaceRecognizerSF as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw(&self) -> <FaceRecognizerSF as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self, ) -> <FaceRecognizerSF as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for FaceRecognizerSF

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Drop for FaceRecognizerSF

fn drop(&mut self)

Executes the destructor for this type.

impl FaceRecognizerSFTrait for FaceRecognizerSF

fn as_raw_mut_FaceRecognizerSF(&mut self) -> *mut c_void

fn feature( &mut self, aligned_img: &impl ToInputArray, face_feature: &mut impl ToOutputArray, ) -> Result<()>

Extracts face feature from aligned image

impl FaceRecognizerSFTraitConst for FaceRecognizerSF

fn as_raw_FaceRecognizerSF(&self) -> *const c_void

fn align_crop( &self, src_img: &impl ToInputArray, face_box: &impl ToInputArray, aligned_img: &mut impl ToOutputArray, ) -> Result<()>

Aligns detected face with the source input image and crops it

fn match_( &self, face_feature1: &impl ToInputArray, face_feature2: &impl ToInputArray, dis_type: i32, ) -> Result<f64>

Calculates the distance between two face features

fn match__def( &self, face_feature1: &impl ToInputArray, face_feature2: &impl ToInputArray, ) -> Result<f64>

Calculates the distance between two face features

impl Send for FaceRecognizerSF