Roadmap: face detector yn face recognizer sf (#1232)

objdetect: FaceDetectorYN + FaceRecognizerSF

.github/workflows/linux.yml

@@ -44,6 +44,8 @@ jobs:
         run: |
           mkdir -p ${GITHUB_WORKSPACE}/testdata
           curl -sL https://github.com/onnx/models/raw/main/validated/vision/classification/inception_and_googlenet/googlenet/model/googlenet-9.onnx > ${GITHUB_WORKSPACE}/testdata/googlenet-9.onnx
+          curl -sL https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_recognition_sface/face_recognition_sface_2021dec.onnx > ${GITHUB_WORKSPACE}/testdata/face_recognition_sface_2021dec.onnx
+          curl -sL https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx > ${GITHUB_WORKSPACE}/testdata/face_detection_yunet_2023mar.onnx
       - name: Run main tests
         run: xvfb-run -a --error-file /var/log/xvfb_error.log --server-args="-screen 0 1024x768x24 +extension RANDR" go test -v -coverprofile=/tmp/coverage.out -count=1 -tags matprofile .
         env:

.github/workflows/macos.yml

@@ -53,6 +53,8 @@ jobs:
         run: |
           mkdir -p ${GITHUB_WORKSPACE}/testdata
           curl -sL https://github.com/onnx/models/raw/main/validated/vision/classification/inception_and_googlenet/googlenet/model/googlenet-9.onnx > ${GITHUB_WORKSPACE}/testdata/googlenet-9.onnx
+          curl -sL https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_recognition_sface/face_recognition_sface_2021dec.onnx > ${GITHUB_WORKSPACE}/testdata/face_recognition_sface_2021dec.onnx
+          curl -sL https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx > ${GITHUB_WORKSPACE}/testdata/face_detection_yunet_2023mar.onnx
       - name: Run main tests
         run: go test -v -tags matprofile .
         env:

.github/workflows/windows.yml

@@ -90,6 +90,8 @@ jobs:
       - name: Install ONNX test model
         run: |
           curl -sL https://github.com/onnx/models/raw/main/validated/vision/classification/inception_and_googlenet/googlenet/model/googlenet-9.onnx > ./testdata/googlenet-9.onnx
+          curl -sL https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_recognition_sface/face_recognition_sface_2021dec.onnx > ./testdata/face_recognition_sface_2021dec.onnx
+          curl -sL https://github.com/opencv/opencv_zoo/raw/refs/heads/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx > ./testdata/face_detection_yunet_2023mar.onnx
       - name: Install GOTURN test model
         shell: bash
         run: |

ROADMAP.md

@@ -164,9 +164,9 @@ Your pull requests will be greatly appreciated!
         - [ ] [detectBoard](https://docs.opencv.org/4.x/d9/df5/classcv_1_1aruco_1_1CharucoDetector.html#aacbea601612a3a0feaa45ebb7fb255fd)
         - [ ] [detectDiamonds](https://docs.opencv.org/4.x/d9/df5/classcv_1_1aruco_1_1CharucoDetector.html#a50342803f68deb1e6b0b79f61d4b1a73)
 
-    - [ ] Face Detection
+    - [X] Face Detection
-        - [ ] [FaceDetectorYN](https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html)
+        - [X] [FaceDetectorYN](https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html)
-        - [ ] [FaceRecognizerSF](https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html)
+        - [X] [FaceRecognizerSF](https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html)
         
 - [X] **dnn. Deep Neural Network module**
 - [ ] ml. Machine Learning

objdetect.cpp

@@ -176,3 +176,139 @@ bool QRCodeDetector_DetectAndDecodeMulti(QRCodeDetector qr, Mat input, CStrings*
   decoded->strs = strs;
   return res;
 }
+
+FaceDetectorYN FaceDetectorYN_Create(const char* model, const char* config, Size size) {
+    cv::String smodel = cv::String(model);
+    cv::String sconfig = cv::String(config);
+    cv::Size   ssize = cv::Size(size.width, size.height);
+
+    return new cv::Ptr<cv::FaceDetectorYN>(cv::FaceDetectorYN::create(smodel, sconfig, ssize));
+}
+
+FaceDetectorYN FaceDetectorYN_Create_WithParams(const char* model, const char* config, Size size, float score_threshold, float nms_threshold, int top_k, int backend_id, int target_id) {
+    cv::String smodel = cv::String(model);
+    cv::String sconfig = cv::String(config);
+    cv::Size   ssize = cv::Size(size.width, size.height);
+
+    return new cv::Ptr<cv::FaceDetectorYN>(cv::FaceDetectorYN::create(smodel, sconfig, ssize, score_threshold, nms_threshold, top_k, backend_id, target_id));
+}
+
+FaceDetectorYN FaceDetectorYN_Create_FromBytes(const char* framework, void* bufferModel, int model_size, void* bufferConfig, int config_size, Size size) {
+    cv::String sframework = cv::String(framework);
+    cv::Size   ssize = cv::Size(size.width, size.height);
+    
+    std::vector<uchar> bufferModelV;
+    std::vector<uchar> bufferConfigV;
+
+    uchar* bmv = (uchar*)bufferModel;
+    uchar* bcv = (uchar*)bufferConfig;
+
+
+    for(int i = 0; i < model_size; i ++) {
+        bufferModelV.push_back(bmv[i]);
+    }
+   for(int i = 0; i < config_size; i ++) {
+        bufferConfigV.push_back(bcv[i]);
+    }
+
+    return new cv::Ptr<cv::FaceDetectorYN>(cv::FaceDetectorYN::create(sframework, bufferModelV, bufferConfigV, ssize));
+}
+
+FaceDetectorYN FaceDetectorYN_Create_FromBytes_WithParams(const char* framework, void* bufferModel, int model_size, void* bufferConfig, int config_size, Size size, float score_threshold, float nms_threshold, int top_k, int backend_id, int target_id) {
+    cv::String sframework = cv::String(framework);
+    cv::Size   ssize = cv::Size(size.width, size.height);
+    
+    std::vector<uchar> bufferModelV;
+    std::vector<uchar> bufferConfigV;
+
+    uchar* bmv = (uchar*)bufferModel;
+    uchar* bcv = (uchar*)bufferConfig;
+
+
+    for(int i = 0; i < model_size; i ++) {
+        bufferModelV.push_back(bmv[i]);
+    }
+    for(int i = 0; i < config_size; i ++) {
+        bufferConfigV.push_back(bcv[i]);
+    }
+
+    return new cv::Ptr<cv::FaceDetectorYN>(cv::FaceDetectorYN::create(sframework, bufferModelV, bufferConfigV, ssize, score_threshold, nms_threshold, top_k, backend_id, target_id));
+}
+
+void FaceDetectorYN_Close(FaceDetectorYN fd) {
+    delete fd;
+}
+
+int FaceDetectorYN_Detect(FaceDetectorYN fd, Mat image, Mat faces) {
+    return (*fd)->detect(*image, *faces);
+}
+
+Size FaceDetectorYN_GetInputSize(FaceDetectorYN fd) {
+    Size sz;
+
+    cv::Size cvsz = (*fd)->getInputSize();
+
+    sz.width = cvsz.width;
+    sz.height = cvsz.height;
+
+    return sz;
+}
+
+float FaceDetectorYN_GetNMSThreshold(FaceDetectorYN fd) {
+    return (*fd)->getNMSThreshold();
+}
+
+float FaceDetectorYN_GetScoreThreshold(FaceDetectorYN fd) {
+    return (*fd)->getScoreThreshold();
+}
+
+int FaceDetectorYN_GetTopK(FaceDetectorYN fd) {
+    return (*fd)->getTopK();
+}
+
+void FaceDetectorYN_SetInputSize(FaceDetectorYN fd, Size input_size){
+    cv::Size isz(input_size.width, input_size.height);
+    (*fd)->setInputSize(isz);
+}
+
+void FaceDetectorYN_SetNMSThreshold(FaceDetectorYN fd, float nms_threshold){
+    (*fd)->setNMSThreshold(nms_threshold);
+}
+
+void FaceDetectorYN_SetScoreThreshold(FaceDetectorYN fd, float score_threshold){
+    (*fd)->setScoreThreshold(score_threshold);
+}
+
+void FaceDetectorYN_SetTopK(FaceDetectorYN fd, int top_k){
+    (*fd)->setTopK(top_k);
+}
+
+FaceRecognizerSF FaceRecognizerSF_Create(const char* model, const char* config) {
+    return FaceRecognizerSF_Create_WithParams(model, config, 0, 0);
+}
+
+FaceRecognizerSF FaceRecognizerSF_Create_WithParams(const char* model, const char* config, int backend_id, int target_id) {
+    cv::Ptr<cv::FaceRecognizerSF>* p = new cv::Ptr<cv::FaceRecognizerSF>(cv::FaceRecognizerSF::create(model, config, backend_id, target_id));
+    return p;
+}
+
+void FaceRecognizerSF_Close(FaceRecognizerSF fr) {
+    delete fr;
+}
+
+void FaceRecognizerSF_AlignCrop(FaceRecognizerSF fr, Mat src_img, Mat face_box, Mat aligned_img) {
+    (*fr)->alignCrop(*src_img, *face_box, *aligned_img);
+}
+
+void FaceRecognizerSF_Feature(FaceRecognizerSF fr, Mat aligned_img, Mat face_feature) {
+    (*fr)->feature(*aligned_img, *face_feature);
+}
+
+float FaceRecognizerSF_Match(FaceRecognizerSF fr, Mat face_feature1, Mat face_feature2) {
+    return FaceRecognizerSF_Match_WithParams(fr, face_feature1, face_feature2, 0);
+}
+
+float FaceRecognizerSF_Match_WithParams(FaceRecognizerSF fr, Mat face_feature1, Mat face_feature2, int dis_type) {
+    double rv = (*fr)->match(*face_feature1, *face_feature2, dis_type);
+    return (float)rv;
+}

objdetect.go

@@ -269,3 +269,294 @@ func (a *QRCodeDetector) DetectAndDecodeMulti(input Mat, decoded []string, point
 	}
 	return bool(success)
 }
+
+type FaceDetectorYN struct {
+	p C.FaceDetectorYN
+}
+
+// NewFaceDetectorYN Creates an instance of face detector with given parameters.
+//
+// modelPath: the path to the requested model
+//
+// configPath: the path to the config file for compability, which is not requested for ONNX models
+//
+// size: the size of the input image
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#a5f7fb43c60c95ca5ebab78483de02516
+func NewFaceDetectorYN(modelPath string, configPath string, size image.Point) FaceDetectorYN {
+
+	c_model_path := C.CString(modelPath)
+	defer C.free(unsafe.Pointer(c_model_path))
+
+	c_config_path := C.CString(configPath)
+	defer C.free(unsafe.Pointer(c_config_path))
+
+	c_size := C.Size{
+		width:  C.int(size.X),
+		height: C.int(size.Y),
+	}
+
+	return FaceDetectorYN{p: C.FaceDetectorYN_Create(c_model_path, c_config_path, c_size)}
+}
+
+// NewFaceDetectorYNWithParams Creates an instance of face detector with given parameters.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#a5f7fb43c60c95ca5ebab78483de02516
+func NewFaceDetectorYNWithParams(modelPath string, configPath string, size image.Point, scoreThreshold float32, nmsThreshold float32, topK int, backendId int, targetId int) FaceDetectorYN {
+
+	c_model_path := C.CString(modelPath)
+	defer C.free(unsafe.Pointer(c_model_path))
+
+	c_config_path := C.CString(configPath)
+	defer C.free(unsafe.Pointer(c_config_path))
+
+	c_size := C.Size{
+		width:  C.int(size.X),
+		height: C.int(size.Y),
+	}
+
+	return FaceDetectorYN{p: C.FaceDetectorYN_Create_WithParams(c_model_path, c_config_path, c_size, C.float(scoreThreshold), C.float(nmsThreshold), C.int(topK), C.int(backendId), C.int(targetId))}
+}
+
+// NewFaceDetectorYNFromBytes Creates an instance of face detector with given parameters.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#aa0796a4bfe2d4709bef81abbae9a927a
+func NewFaceDetectorYNFromBytes(framework string, bufferModel []byte, bufferConfig []byte, size image.Point) FaceDetectorYN {
+
+	c_framework := C.CString(framework)
+	defer C.free(unsafe.Pointer(c_framework))
+
+	c_size := C.Size{
+		width:  C.int(size.X),
+		height: C.int(size.Y),
+	}
+
+	return FaceDetectorYN{p: C.FaceDetectorYN_Create_FromBytes(c_framework,
+		unsafe.Pointer(unsafe.SliceData(bufferModel)), C.int(len(bufferModel)),
+		unsafe.Pointer(unsafe.SliceData(bufferConfig)), C.int(len(bufferConfig)), c_size)}
+}
+
+// NewFaceDetectorYNFromBuffers Creates an instance of face detector with given parameters.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#aa0796a4bfe2d4709bef81abbae9a927a
+func NewFaceDetectorYNFromBytesWithParams(framework string, bufferModel []byte, bufferConfig []byte, size image.Point, scoreThreshold float32, nmsThreshold float32, topK int, backendId int, targetId int) FaceDetectorYN {
+
+	c_framework := C.CString(framework)
+	defer C.free(unsafe.Pointer(c_framework))
+
+	c_size := C.Size{
+		width:  C.int(size.X),
+		height: C.int(size.Y),
+	}
+
+	return FaceDetectorYN{p: C.FaceDetectorYN_Create_FromBytes_WithParams(c_framework,
+		unsafe.Pointer(unsafe.SliceData(bufferModel)), C.int(len(bufferModel)),
+		unsafe.Pointer(unsafe.SliceData(bufferConfig)), C.int(len(bufferConfig)), c_size,
+		C.float(scoreThreshold), C.float(nmsThreshold), C.int(topK), C.int(backendId), C.int(targetId))}
+}
+
+func (fd *FaceDetectorYN) Close() {
+	C.FaceDetectorYN_Close(fd.p)
+}
+
+// Detect Detects faces in the input image.
+//
+// image: an image to detect
+//
+// faces: detection results stored in a 2D cv::Mat of shape [num_faces, 15]
+//
+// 0-1: x, y of bbox top left corner
+//
+// 2-3: width, height of bbox
+//
+// 4-5: x, y of right eye (blue point in the example image)
+//
+// 6-7: x, y of left eye (red point in the example image)
+//
+// 8-9: x, y of nose tip (green point in the example image)
+//
+// 10-11: x, y of right corner of mouth (pink point in the example image)
+//
+// 12-13: x, y of left corner of mouth (yellow point in the example image)
+//
+// 14: face score
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#ac05bd075ca3e6edc0e328927aae6f45b
+func (fd *FaceDetectorYN) Detect(image Mat, faces *Mat) int {
+	c_rv := C.FaceDetectorYN_Detect(fd.p, image.p, faces.p)
+	return int(c_rv)
+}
+
+func (fd *FaceDetectorYN) GetInputSize() image.Point {
+	sz := C.FaceDetectorYN_GetInputSize(fd.p)
+
+	return image.Pt(int(sz.width), int(sz.height))
+}
+
+func (fd *FaceDetectorYN) GetMNSThreshold() float32 {
+	t := C.FaceDetectorYN_GetNMSThreshold(fd.p)
+	return float32(t)
+}
+
+func (fd *FaceDetectorYN) GetScoreThreshold() float32 {
+	t := C.FaceDetectorYN_GetScoreThreshold(fd.p)
+	return float32(t)
+}
+
+func (fd *FaceDetectorYN) GetTopK() int {
+	i := C.FaceDetectorYN_GetTopK(fd.p)
+	return int(i)
+}
+
+// SetInputSize Set the size for the network input, which overwrites the input size of creating model.
+// Call this method when the size of input image does not match the input size when creating model.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#a072418e5ce7beeb69c41edda75c41d2e
+func (fd *FaceDetectorYN) SetInputSize(sz image.Point) {
+	c_sz := C.Size{
+		width:  C.int(sz.X),
+		height: C.int(sz.Y),
+	}
+	C.FaceDetectorYN_SetInputSize(fd.p, c_sz)
+}
+
+// SetNMSThreshold Set the Non-maximum-suppression threshold to suppress
+// bounding boxes that have IoU greater than the given value.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#ab6011efee7e12dca3857d82de5269ac5
+func (fd *FaceDetectorYN) SetNMSThreshold(nmsThreshold float32) {
+	C.FaceDetectorYN_SetNMSThreshold(fd.p, C.float(nmsThreshold))
+}
+
+// SetScoreThreshold Set the score threshold to filter out bounding boxes of score less than the given value.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#a37f3c23b82158fac7fdad967d315f85a
+func (fd *FaceDetectorYN) SetScoreThreshold(scoreThreshold float32) {
+	C.FaceDetectorYN_SetScoreThreshold(fd.p, C.float(scoreThreshold))
+}
+
+// SetTopK Set the number of bounding boxes preserved before NMS.
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/df/d20/classcv_1_1FaceDetectorYN.html#aa88d20e1e2df75ea36b851534089856a
+func (fd *FaceDetectorYN) SetTopK(topK int) {
+	C.FaceDetectorYN_SetTopK(fd.p, C.int(topK))
+}
+
+type FaceRecognizerSFDisType int
+
+const (
+	FaceRecognizerSFDisTypeCosine FaceRecognizerSFDisType = 0
+	FaceRecognizerSFDisTypeNormL2 FaceRecognizerSFDisType = 1
+)
+
+type FaceRecognizerSF struct {
+	p C.FaceRecognizerSF
+}
+
+// NewFaceRecognizerSF Creates an instance with given 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
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html#a04df90b0cd7d26d350acd92621a35743
+func NewFaceRecognizerSF(modelPath string, configPath string) FaceRecognizerSF {
+	c_model := C.CString(modelPath)
+	defer C.free(unsafe.Pointer(c_model))
+
+	c_config := C.CString(configPath)
+	defer C.free(unsafe.Pointer(c_config))
+
+	return FaceRecognizerSF{p: C.FaceRecognizerSF_Create(c_model, c_config)}
+}
+
+// NewFaceRecognizerSFWithParams Creates an instance with given 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
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html#a04df90b0cd7d26d350acd92621a35743
+func NewFaceRecognizerSFWithParams(modelPath string, configPath string, backendId int, targetId int) FaceRecognizerSF {
+	c_model := C.CString(modelPath)
+	defer C.free(unsafe.Pointer(c_model))
+
+	c_config := C.CString(configPath)
+	defer C.free(unsafe.Pointer(c_config))
+
+	return FaceRecognizerSF{p: C.FaceRecognizerSF_Create_WithParams(c_model, c_config, C.int(backendId), C.int(targetId))}
+}
+
+// Close Releases FaceRecognizerSF resources.
+func (fr *FaceRecognizerSF) Close() {
+	C.FaceRecognizerSF_Close(fr.p)
+}
+
+// AlignCrop Aligns detected face with the source input image and crops it.
+//
+// srcImg: input image
+//
+// faceBox: the detected face result from the input image
+//
+// alignedImg: output aligned image
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html#a84492908abecbc9362b4ddc8d46b8345
+func (fr *FaceRecognizerSF) AlignCrop(srcImg Mat, faceBox Mat, alignedImg *Mat) {
+	C.FaceRecognizerSF_AlignCrop(fr.p, srcImg.p, faceBox.p, alignedImg.p)
+}
+
+// Feature Extracts face feature from aligned image.
+//
+// alignedImg: input aligned image
+//
+// faceFeature: output face feature
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html#ab1b4a3c12213e89091a490c573dc5aba
+func (fr *FaceRecognizerSF) Feature(alignedImg Mat, faceFeature *Mat) {
+	C.FaceRecognizerSF_Feature(fr.p, alignedImg.p, faceFeature.p)
+}
+
+// Match Calculates the distance between two face features.
+//
+// faceFeature1: the first input feature
+//
+// faceFeature2: the second input feature of the same size and the same type as face_feature1
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html#a2f0362ca1e64320a1f3ba7e1386d0219
+func (fr *FaceRecognizerSF) Match(faceFeature1 Mat, faceFeature2 Mat) float32 {
+	rv := C.FaceRecognizerSF_Match(fr.p, faceFeature1.p, faceFeature2.p)
+	return float32(rv)
+}
+
+// MatchWithParams Calculates the distance between two face features.
+//
+// faceFeature1: the first input feature
+//
+// faceFeature2: the second input feature of the same size and the same type as face_feature1
+//
+// disType: defines how to calculate the distance between two face features
+//
+// For further details, please see:
+// https://docs.opencv.org/4.x/da/d09/classcv_1_1FaceRecognizerSF.html#a2f0362ca1e64320a1f3ba7e1386d0219
+func (fr *FaceRecognizerSF) MatchWithParams(faceFeature1 Mat, faceFeature2 Mat, disType FaceRecognizerSFDisType) float32 {
+	rv := C.FaceRecognizerSF_Match_WithParams(fr.p, faceFeature1.p, faceFeature2.p, C.int(disType))
+	return float32(rv)
+}

objdetect.h

@@ -14,10 +14,14 @@ extern "C" {
 typedef cv::CascadeClassifier* CascadeClassifier;
 typedef cv::HOGDescriptor* HOGDescriptor;
 typedef cv::QRCodeDetector* QRCodeDetector;
+typedef cv::Ptr<cv::FaceDetectorYN>* FaceDetectorYN;
+typedef cv::Ptr<cv::FaceRecognizerSF>* FaceRecognizerSF;
 #else
 typedef void* CascadeClassifier;
 typedef void* HOGDescriptor;
 typedef void* QRCodeDetector;
+typedef void* FaceDetectorYN;
+typedef void* FaceRecognizerSF;
 #endif
 
 // CascadeClassifier
@@ -48,6 +52,31 @@ void QRCodeDetector_Close(QRCodeDetector qr);
 bool QRCodeDetector_DetectMulti(QRCodeDetector qr, Mat input, Mat points);
 bool QRCodeDetector_DetectAndDecodeMulti(QRCodeDetector qr, Mat input, CStrings* decoded ,Mat points, struct Mats* mats);
 
+// FaceDetectorYN
+FaceDetectorYN FaceDetectorYN_Create(const char* model, const char* config, Size size);
+FaceDetectorYN FaceDetectorYN_Create_WithParams(const char* model, const char* config, Size size, float score_threshold, float mms_threshold, int top_k, int backend_id, int target_id);
+FaceDetectorYN FaceDetectorYN_Create_FromBytes(const char* framework, void* bufferModel, int model_size, void* bufferConfig, int config_size, Size size);
+FaceDetectorYN FaceDetectorYN_Create_FromBytes_WithParams(const char* framework, void* bufferModel, int model_size, void* bufferConfig, int config_size, Size size, float score_threshold, float mms_threshold, int top_k, int backend_id, int target_id);
+void FaceDetectorYN_Close(FaceDetectorYN fd); 
+int FaceDetectorYN_Detect(FaceDetectorYN fd, Mat image, Mat faces);
+Size FaceDetectorYN_GetInputSize(FaceDetectorYN fd);
+float FaceDetectorYN_GetNMSThreshold(FaceDetectorYN fd);
+float FaceDetectorYN_GetScoreThreshold(FaceDetectorYN fd);
+int FaceDetectorYN_GetTopK(FaceDetectorYN fd);
+void FaceDetectorYN_SetInputSize(FaceDetectorYN fd, Size input_size);
+void FaceDetectorYN_SetNMSThreshold(FaceDetectorYN fd, float nms_threshold);
+void FaceDetectorYN_SetScoreThreshold(FaceDetectorYN fd, float score_threshold);
+void FaceDetectorYN_SetTopK(FaceDetectorYN fd, int top_k);
+
+// FaceRecognizerSF
+FaceRecognizerSF FaceRecognizerSF_Create(const char* model, const char* config);
+FaceRecognizerSF FaceRecognizerSF_Create_WithParams(const char* model, const char* config, int backend_id, int target_id);
+void FaceRecognizerSF_Close(FaceRecognizerSF fr);
+void FaceRecognizerSF_AlignCrop(FaceRecognizerSF fr, Mat src_img, Mat face_box, Mat aligned_img);
+void FaceRecognizerSF_Feature(FaceRecognizerSF fr, Mat aligned_img, Mat face_feature);
+float FaceRecognizerSF_Match(FaceRecognizerSF fr, Mat face_feature1, Mat face_feature2);
+float FaceRecognizerSF_Match_WithParams(FaceRecognizerSF fr, Mat face_feature1, Mat face_feature2, int dis_type);
+
 #ifdef __cplusplus
 }
 #endif

objdetect_test.go

@@ -3,6 +3,7 @@ package gocv
 import (
 	"image"
 	"image/color"
+	"os"
 	"testing"
 )
 
@@ -214,3 +215,268 @@ func padQr(qr *Mat) Mat {
 	CopyMakeBorder(qrCodes0, &out, d, d, d, d, BorderConstant, color.RGBA{255, 255, 255, 255})
 	return out
 }
+
+func TestFaceDetectorYN(t *testing.T) {
+
+	img := IMRead("images/face.jpg", IMReadAnyColor)
+	defer img.Close()
+
+	s := image.Pt(img.Size()[1], img.Size()[0])
+
+	faces := NewMat()
+	defer faces.Close()
+
+	fd := NewFaceDetectorYN("testdata/face_detection_yunet_2023mar.onnx", "", s)
+	defer fd.Close()
+
+	sz := fd.GetInputSize()
+	if sz.X != 640 && sz.Y != 480 {
+		t.Error("error on FaceDetectorYN.GetInputSize()")
+	}
+	fd.SetInputSize(sz)
+
+	t1 := fd.GetMNSThreshold()
+	fd.SetNMSThreshold(t1)
+
+	t2 := fd.GetScoreThreshold()
+	fd.SetScoreThreshold(t2)
+
+	topK := fd.GetTopK()
+	fd.SetTopK(topK)
+
+	fd.Detect(img, &faces)
+
+	facesCount := faces.Rows()
+
+	if facesCount < 1 {
+		t.Error("no face detected")
+	}
+}
+
+func TestFaceDetectorYNWithParams(t *testing.T) {
+
+	img := IMRead("images/face.jpg", IMReadAnyColor)
+	defer img.Close()
+
+	s := image.Pt(img.Size()[1], img.Size()[0])
+
+	faces := NewMat()
+	defer faces.Close()
+
+	fd := NewFaceDetectorYNWithParams("testdata/face_detection_yunet_2023mar.onnx", "", s, 0.9, 0.3, 5000, 0, 0)
+	defer fd.Close()
+
+	sz := fd.GetInputSize()
+	if sz.X != 640 && sz.Y != 480 {
+		t.Error("error on FaceDetectorYN.GetInputSize()")
+	}
+	fd.SetInputSize(sz)
+
+	t1 := fd.GetMNSThreshold()
+	fd.SetNMSThreshold(t1)
+
+	t2 := fd.GetScoreThreshold()
+	fd.SetScoreThreshold(t2)
+
+	topK := fd.GetTopK()
+	fd.SetTopK(topK)
+
+	fd.Detect(img, &faces)
+
+	facesCount := faces.Rows()
+
+	if facesCount < 1 {
+		t.Error("no face detected")
+	}
+
+}
+
+func TestFaceDetectorYNFromBytes(t *testing.T) {
+
+	modelBuffer, err := os.ReadFile("testdata/face_detection_yunet_2023mar.onnx")
+	if err != nil {
+		t.Errorf("%s reading testdata/face_detection_yunet_2023mar.onnx", err.Error())
+	}
+
+	img := IMRead("images/face.jpg", IMReadAnyColor)
+	defer img.Close()
+
+	s := image.Pt(img.Size()[1], img.Size()[0])
+
+	faces := NewMat()
+	defer faces.Close()
+
+	fd := NewFaceDetectorYNFromBytes("onnx", modelBuffer, []byte(""), s)
+	defer fd.Close()
+
+	sz := fd.GetInputSize()
+	if sz.X != 640 && sz.Y != 480 {
+		t.Error("error on FaceDetectorYN.GetInputSize()")
+	}
+	fd.SetInputSize(sz)
+
+	t1 := fd.GetMNSThreshold()
+	fd.SetNMSThreshold(t1)
+
+	t2 := fd.GetScoreThreshold()
+	fd.SetScoreThreshold(t2)
+
+	topK := fd.GetTopK()
+	fd.SetTopK(topK)
+
+	fd.Detect(img, &faces)
+
+	facesCount := faces.Rows()
+
+	if facesCount < 1 {
+		t.Error("no face detected")
+	}
+}
+
+func TestFaceDetectorYNFromBytesWithParams(t *testing.T) {
+
+	modelBuffer, err := os.ReadFile("testdata/face_detection_yunet_2023mar.onnx")
+	if err != nil {
+		t.Errorf("%s reading testdata/face_detection_yunet_2023mar.onnx", err.Error())
+	}
+
+	img := IMRead("images/face.jpg", IMReadAnyColor)
+	defer img.Close()
+
+	s := image.Pt(img.Size()[1], img.Size()[0])
+
+	faces := NewMat()
+	defer faces.Close()
+
+	fd := NewFaceDetectorYNFromBytesWithParams("onnx", modelBuffer, []byte(""), s, 0.9, 0.3, 5000, 0, 0)
+	defer fd.Close()
+
+	sz := fd.GetInputSize()
+	if sz.X != 640 && sz.Y != 480 {
+		t.Error("error on FaceDetectorYN.GetInputSize()")
+	}
+	fd.SetInputSize(sz)
+
+	t1 := fd.GetMNSThreshold()
+	fd.SetNMSThreshold(t1)
+
+	t2 := fd.GetScoreThreshold()
+	fd.SetScoreThreshold(t2)
+
+	topK := fd.GetTopK()
+	fd.SetTopK(topK)
+
+	fd.Detect(img, &faces)
+
+	facesCount := faces.Rows()
+
+	if facesCount < 1 {
+		t.Error("no face detected")
+	}
+}
+
+func TestFaceRecognizerSF(t *testing.T) {
+
+	rons := IMRead("images/face.jpg", IMReadUnchanged)
+	defer rons.Close()
+
+	ronsImgSz := rons.Size()
+
+	s := image.Pt(ronsImgSz[1], ronsImgSz[0])
+
+	fd := NewFaceDetectorYN("testdata/face_detection_yunet_2023mar.onnx", "", s)
+	defer fd.Close()
+
+	ronsFaces := NewMat()
+	defer ronsFaces.Close()
+
+	detectRv := fd.Detect(rons, &ronsFaces)
+	t.Log("detect rv is", detectRv)
+
+	facesCount := ronsFaces.Rows()
+	if facesCount < 1 {
+		t.Error("no face detected")
+	}
+
+	ronsFaceX0 := ronsFaces.GetFloatAt(0, 0)
+	ronsFaceY0 := ronsFaces.GetFloatAt(0, 1)
+	ronsFaceX1 := ronsFaces.GetFloatAt(0, 0) + ronsFaces.GetFloatAt(0, 2)
+	ronsFaceY1 := ronsFaces.GetFloatAt(0, 1) + ronsFaces.GetFloatAt(0, 3)
+
+	ronsFace := rons.Region(image.Rect(int(ronsFaceX0), int(ronsFaceY0), int(ronsFaceX1), int(ronsFaceY1)))
+	defer ronsFace.Close()
+
+	fr := NewFaceRecognizerSF("testdata/face_recognition_sface_2021dec.onnx", "")
+	defer fr.Close()
+
+	ronsAligned := NewMat()
+	defer ronsAligned.Close()
+
+	fr.AlignCrop(rons, ronsFace, &ronsAligned)
+
+	if ronsAligned.Empty() {
+		t.Error("aligned is empty")
+	}
+
+	ronsFaceFeature := NewMat()
+	defer ronsFaceFeature.Close()
+
+	fr.Feature(ronsAligned, &ronsFaceFeature)
+
+	match := fr.Match(ronsFaceFeature, ronsFaceFeature)
+	t.Log("face feature match: ", match)
+
+}
+
+func TestFaceRecognizerSFWithParams(t *testing.T) {
+
+	rons := IMRead("images/face.jpg", IMReadUnchanged)
+	defer rons.Close()
+
+	ronsImgSz := rons.Size()
+
+	s := image.Pt(ronsImgSz[1], ronsImgSz[0])
+
+	fd := NewFaceDetectorYN("testdata/face_detection_yunet_2023mar.onnx", "", s)
+	defer fd.Close()
+
+	ronsFaces := NewMat()
+	defer ronsFaces.Close()
+
+	detectRv := fd.Detect(rons, &ronsFaces)
+	t.Log("detect rv is", detectRv)
+
+	facesCount := ronsFaces.Rows()
+	if facesCount < 1 {
+		t.Error("no face detected")
+	}
+
+	ronsFaceX0 := ronsFaces.GetFloatAt(0, 0)
+	ronsFaceY0 := ronsFaces.GetFloatAt(0, 1)
+	ronsFaceX1 := ronsFaces.GetFloatAt(0, 0) + ronsFaces.GetFloatAt(0, 2)
+	ronsFaceY1 := ronsFaces.GetFloatAt(0, 1) + ronsFaces.GetFloatAt(0, 3)
+
+	ronsFace := rons.Region(image.Rect(int(ronsFaceX0), int(ronsFaceY0), int(ronsFaceX1), int(ronsFaceY1)))
+	defer ronsFace.Close()
+
+	fr := NewFaceRecognizerSFWithParams("testdata/face_recognition_sface_2021dec.onnx", "", 0, 0)
+	defer fr.Close()
+
+	ronsAligned := NewMat()
+	defer ronsAligned.Close()
+
+	fr.AlignCrop(rons, ronsFace, &ronsAligned)
+
+	if ronsAligned.Empty() {
+		t.Error("aligned is empty")
+	}
+
+	ronsFaceFeature := NewMat()
+	defer ronsFaceFeature.Close()
+
+	fr.Feature(ronsAligned, &ronsFaceFeature)
+
+	match := fr.MatchWithParams(ronsFaceFeature, ronsFaceFeature, FaceRecognizerSFDisTypeCosine)
+	t.Log("face feature match: ", match)
+
+}