feat(face): add scrfd face detecter/landmarker

README.md

@@ -22,12 +22,14 @@ cmake .. # optional -DNCNN_VULKAN=OFF -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COM
     - centerface [Google Drive](https://drive.google.com/drive/folders/1xMhO6aCnkkjt90Fh8BxVD_JHB3QJ2q-q?usp=sharing)
     - retainface [Google Drive](https://drive.google.com/drive/folders/1nxR3WFqqEWLwGVsp5c4tI0_iVVEaVOe8?usp=sharing)
     - yoloface [Google Drive](https://drive.google.com/drive/folders/1EM9H6-aYXKsWTRxx_wbKDyYHVIYpU6f7?usp=sharing)
+    - scrfd [Google Drive](https://drive.google.com/drive/folders/1XPjfsuXGj9rXqAmo1K70BsqWmHvoYQv_?usp=sharing)
     - anticonv (for mask detection) [Google Drive](https://drive.google.com/drive/folders/1Fje0fmVPy5g0_oaxUbH_cAedkgjBf7QW?usp=sharing)
   - recognizer (face feature extration for classification)
     - mobilenet [Google Drive](https://drive.google.com/drive/folders/1fRLs10atm_vwDWQXZ-GJbKQpypNcXLAx?usp=sharing)
   - landmarker (for face landmarkers extraction)
     - insightface [Google Drive](https://drive.google.com/drive/folders/1e_nRwneMEDf_sXEMZCmOk0S4VT0_XpOS?usp=sharing)
     - zq [Google Drive](https://drive.google.com/drive/folders/1ax0J1TVhf2S-B3V6lnqwJaaHUK433sPm?usp=sharing)
+    - scrfd [Google Drive](https://drive.google.com/drive/folders/1XPjfsuXGj9rXqAmo1K70BsqWmHvoYQv_?usp=sharing)
   - tracker (for face IOU calculation bettween frames)
   - hopenet (for head pose detection) [Google Drive](https://drive.google.com/drive/folders/1zLam-8s9ZMPDUxUEtNU2F9yFTDRM5fk-?usp=sharing)
 - pose
@@ -40,3 +42,14 @@ cmake .. # optional -DNCNN_VULKAN=OFF -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COM
   - pose (for hand pose estimation)
     - handnet [Google Drive](https://drive.google.com/drive/folders/1DsCGmiVaZobbMWRp5Oec8GbIpeg7CsNR?usp=sharing)
 - golang binding (github.com/bububa/openvision/go)
+
+## Reference
+
+- [MirrorYuChen/ncnn_example](https://github.com/MirrorYuChen/ncnn_example)
+- [nihui/ncnn-android-nanodet](https://github.com/nihui/ncnn-android-nanodet)
+- [FeiGeChuanShu/ncnn_Android_face](https://github.com/FeiGeChuanShu/ncnn_Android_face)
+- [FeiGeChuanShu/ncnn_nanodet_hand](https://github.com/FeiGeChuanShu/ncnn_nanodet_hand)
+- [docongminh/deep-head-pose-ncnn](https://github.com/docongminh/deep-head-pose-ncnn)
+- [nilseuropa/hopenet_ncnn](https://github.com/nilseuropa/hopenet_ncnn)
+- [dog-qiuqiu/Ultralight-SimplePose](https://github.com/dog-qiuqiu/Ultralight-SimplePose)
+- [GHLab/deep-head-pose-lite-ncnn](https://github.com/GHLab/deep-head-pose-lite-ncnn)

go/common/estimator.go

@@ -0,0 +1,41 @@
+package common
+
+/*
+#include <stdlib.h>
+#include <stdbool.h>
+#include "openvision/common/common.h"
+*/
+import "C"
+import (
+	"unsafe"
+
+	openvision "github.com/bububa/openvision/go"
+)
+
+// Estimator represents Estimator interface
+type Estimator interface {
+	LoadModel(modelPath string) error
+	Destroy()
+	Pointer() unsafe.Pointer
+}
+
+// SetEstimatorThreads set ncnn net opt.num_threads
+func SetEstimatorThreads(e Estimator, n int) {
+	C.set_num_threads((C.IEstimator)(e.Pointer()), C.int(n))
+}
+
+// DestroyEstimator destory an Estimator
+func DestroyEstimator(e Estimator) {
+	C.destroy_estimator((C.IEstimator)(e.Pointer()))
+}
+
+// EstimatorLoadModel load detecter model
+func EstimatorLoadModel(e Estimator, modelPath string) error {
+	cpath := C.CString(modelPath)
+	defer C.free(unsafe.Pointer(cpath))
+	retCode := C.load_model((C.IEstimator)(e.Pointer()), cpath)
+	if retCode != 0 {
+		return openvision.LoadModelError(int(retCode))
+	}
+	return nil
+}

go/common/gpu.go

@@ -7,16 +7,29 @@ package common
 */
 import "C"
 
+// GetGPUCount get gpu number
 func GetGPUCount() int {
 	count := C.get_gpu_count()
 	return int(count)
 }
 
+// CreateGPUInstance create gpu instance
 func CreateGPUInstance() int {
 	i := C.create_gpu_instance()
 	return int(i)
 }
 
+// DestroyGPUInstance destory gpu instance
 func DestroyGPUInstance() {
 	C.destroy_gpu_instance()
 }
+
+// GetBigCPUCount get cpu number
+func GetBigCPUCount() int {
+	return int(C.get_big_cpu_count())
+}
+
+// SetOMPThreads set omp thread number
+func SetOMPThreads(n int) {
+	C.set_omp_num_threads(C.int(n))
+}

go/common/keypoint.go

@@ -22,14 +22,14 @@ type Keypoint struct {
 func GoKeypoint(c *C.Keypoint, w float64, h float64) Keypoint {
 	return Keypoint{
 		Point: Pt(float64(c.p.x)/w, float64(c.p.y)/h),
-		Score: float32(c.prob),
+		Score: float32(c.score),
 	}
 }
 
 // Convert Keypoint to C.Keypoint pointer
 func (k Keypoint) CKeypoint(w float64, h float64) *C.Keypoint {
 	ret := (*C.Keypoint)(C.malloc(C.sizeof_Keypoint))
-	ret.prob = C.float(k.Score)
+	ret.score = C.float(k.Score)
 	ret.p = C.Point2f{
 		C.float(k.Point.X * w),
 		C.float(k.Point.Y * h),

go/common/objectinfo.go

@@ -26,7 +26,7 @@ type ObjectInfo struct {
 func GoObjectInfo(c *C.ObjectInfo, w float64, h float64) ObjectInfo {
 	ret := ObjectInfo{
 		Label: int(c.label),
-		Score: float32(c.prob),
+		Score: float32(c.score),
 		Rect: Rect(
 			float64(c.rect.x)/w,
 			float64(c.rect.y)/h,
@@ -44,7 +44,7 @@ func GoObjectInfo(c *C.ObjectInfo, w float64, h float64) ObjectInfo {
 func (o ObjectInfo) ToCObjectInfo(w float64, h float64) *C.ObjectInfo {
 	ret := (*C.ObjectInfo)(C.malloc(C.sizeof_ObjectInfo))
 	ret.label = C.int(o.Label)
-	ret.prob = C.float(o.Score)
+	ret.score = C.float(o.Score)
 	ret.rect.x = C.int(o.Rect.X * w)
 	ret.rect.y = C.int(o.Rect.Y * h)
 	ret.rect.width = C.int(o.Rect.Width * w)

go/examples/detecter/main.go

@@ -23,24 +23,30 @@ func main() {
 	modelPath := filepath.Join(dataPath, "./models")
 	common.CreateGPUInstance()
 	defer common.DestroyGPUInstance()
-	test_detect(imgPath, modelPath)
-	test_mask(imgPath, modelPath)
+	cpuCores := common.GetBigCPUCount()
+	common.SetOMPThreads(cpuCores)
+	log.Printf("CPU big cores:%d\n", cpuCores)
+	test_detect(imgPath, modelPath, cpuCores)
+	test_mask(imgPath, modelPath, cpuCores)
 }
 
-func test_detect(imgPath string, modelPath string) {
+func test_detect(imgPath string, modelPath string, threads int) {
 	for idx, d := range []detecter.Detecter{
 		retinaface(modelPath),
 		centerface(modelPath),
 		mtcnn(modelPath),
 		yoloface(modelPath),
+		scrfd(modelPath),
 	} {
+		common.SetEstimatorThreads(d, threads)
 		detect(d, imgPath, idx, "4.jpg", false)
 		d.Destroy()
 	}
 }
 
-func test_mask(imgPath string, modelPath string) {
+func test_mask(imgPath string, modelPath string, threads int) {
 	d := anticonv(modelPath)
+	common.SetEstimatorThreads(d, threads)
 	defer d.Destroy()
 	detect(d, imgPath, 0, "mask3.jpg", true)
 }
@@ -72,6 +78,15 @@ func yoloface(modelPath string) detecter.Detecter {
 	return d
 }
 
+func scrfd(modelPath string) detecter.Detecter {
+	modelPath = filepath.Join(modelPath, "scrfd/scrfd1g")
+	d := detecter.NewScrfd()
+	if err := d.LoadModel(modelPath); err != nil {
+		log.Fatalln(err)
+	}
+	return d
+}
+
 func centerface(modelPath string) detecter.Detecter {
 	modelPath = filepath.Join(modelPath, "centerface")
 	d := detecter.NewCenterface()
@@ -96,7 +111,7 @@ func detect(d detecter.Detecter, imgPath string, idx int, filename string, mask
 	if err != nil {
 		log.Fatalln("load image failed,", err)
 	}
-	faces, err := d.DetectFace(common.NewImage(img))
+	faces, err := d.Detect(common.NewImage(img))
 	if err != nil {
 		log.Fatalln(err)
 	}

go/examples/hand/main.go

@@ -24,13 +24,19 @@ func main() {
 	modelPath := filepath.Join(dataPath, "./models")
 	common.CreateGPUInstance()
 	defer common.DestroyGPUInstance()
+	cpuCores := common.GetBigCPUCount()
+	common.SetOMPThreads(cpuCores)
+	log.Printf("CPU big cores:%d\n", cpuCores)
 	estimator := handpose(modelPath)
 	defer estimator.Destroy()
+	common.SetEstimatorThreads(estimator, cpuCores)
 	for idx, d := range []detecter.Detecter{
-		yolox(modelPath), nanodet(modelPath),
+		yolox(modelPath),
+		nanodet(modelPath),
 	} {
 		defer d.Destroy()
-		detect(d, estimator, imgPath, "hand2.jpg", idx)
+		common.SetEstimatorThreads(d, cpuCores)
+		detect(d, estimator, imgPath, "hand1.jpg", idx)
 	}
 }
 

go/examples/hopenet/main.go

@@ -24,10 +24,15 @@ func main() {
 	modelPath := filepath.Join(dataPath, "./models")
 	common.CreateGPUInstance()
 	defer common.DestroyGPUInstance()
+	cpuCores := common.GetBigCPUCount()
+	common.SetOMPThreads(cpuCores)
+	log.Printf("CPU big cores:%d\n", cpuCores)
 	d := retinaface(modelPath)
 	defer d.Destroy()
+	common.SetEstimatorThreads(d, cpuCores)
 	h := processer(modelPath)
 	defer h.Destroy()
+	common.SetEstimatorThreads(h, cpuCores)
 	for _, fn := range []string{"robocop.jpg", "terminator.jpg"} {
 		process(d, h, imgPath, fn)
 	}
@@ -60,7 +65,7 @@ func process(d detecter.Detecter, h *hopenet.Hopenet, imgPath string, filename s
 		log.Fatalln("load image failed,", err)
 	}
 	img := common.NewImage(imgLoaded)
-	faces, err := d.DetectFace(img)
+	faces, err := d.Detect(img)
 	if err != nil {
 		log.Fatalln(err)
 	}

go/examples/landmarker/main.go

@@ -2,6 +2,7 @@ package main
 
 import (
 	"bytes"
+	"fmt"
 	"image"
 	"image/jpeg"
 	"log"
@@ -23,11 +24,21 @@ func main() {
 	modelPath := filepath.Join(dataPath, "./models")
 	common.CreateGPUInstance()
 	defer common.DestroyGPUInstance()
+	cpuCores := common.GetBigCPUCount()
+	common.SetOMPThreads(cpuCores)
+	log.Printf("CPU big cores:%d\n", cpuCores)
 	d := retinaface(modelPath)
 	defer d.Destroy()
-	m := insightface(modelPath)
-	defer m.Destroy()
-	extract_keypoints(d, m, imgPath, "4.jpg")
+	common.SetEstimatorThreads(d, cpuCores)
+	for idx, m := range []landmarker.Landmarker{
+		insightface(modelPath),
+		zq(modelPath),
+		scrfd(modelPath),
+	} {
+		defer m.Destroy()
+		common.SetEstimatorThreads(m, cpuCores)
+		extract_keypoints(d, m, imgPath, "4.jpg", idx)
+	}
 }
 
 func retinaface(modelPath string) detecter.Detecter {
@@ -57,14 +68,23 @@ func zq(modelPath string) landmarker.Landmarker {
 	return d
 }
 
-func extract_keypoints(d detecter.Detecter, m landmarker.Landmarker, imgPath string, filename string) {
+func scrfd(modelPath string) landmarker.Landmarker {
+	modelPath = filepath.Join(modelPath, "scrfd/landmarker")
+	d := landmarker.NewScrfd()
+	if err := d.LoadModel(modelPath); err != nil {
+		log.Fatalln(err)
+	}
+	return d
+}
+
+func extract_keypoints(d detecter.Detecter, m landmarker.Landmarker, imgPath string, filename string, idx int) {
 	inPath := filepath.Join(imgPath, filename)
 	imgLoaded, err := loadImage(inPath)
 	if err != nil {
 		log.Fatalln("load image failed,", err)
 	}
 	img := common.NewImage(imgLoaded)
-	faces, err := d.DetectFace(img)
+	faces, err := d.Detect(img)
 	if err != nil {
 		log.Fatalln(err)
 	}
@@ -83,8 +103,7 @@ func extract_keypoints(d detecter.Detecter, m landmarker.Landmarker, imgPath str
 		keypoints = append(keypoints, points...)
 	}
 	out := drawer.DrawLandmark(imgLoaded, keypoints)
-	outPath := filepath.Join(imgPath, "./results", filename)
-
+	outPath := filepath.Join(imgPath, "./results", fmt.Sprintf("landmarker-%d-%s", idx, filename))
 	if err := saveImage(out, outPath); err != nil {
 		log.Fatalln(err)
 	}

go/examples/pose/main.go

@@ -23,8 +23,12 @@ func main() {
 	modelPath := filepath.Join(dataPath, "./models")
 	common.CreateGPUInstance()
 	defer common.DestroyGPUInstance()
+	cpuCores := common.GetBigCPUCount()
+	common.SetOMPThreads(cpuCores)
+	log.Printf("CPU big cores:%d\n", cpuCores)
 	d := ultralightDetector(modelPath)
 	defer d.Destroy()
+	common.SetEstimatorThreads(d, cpuCores)
 	detect(d, imgPath, "ultralight-pose3.jpg")
 }
 

go/examples/recognizer/main.go

@@ -22,10 +22,15 @@ func main() {
 	modelPath := filepath.Join(dataPath, "./models")
 	common.CreateGPUInstance()
 	defer common.DestroyGPUInstance()
+	cpuCores := common.GetBigCPUCount()
+	common.SetOMPThreads(cpuCores)
+	log.Printf("CPU big cores:%d\n", cpuCores)
 	d := retinaface(modelPath)
 	defer d.Destroy()
+	common.SetEstimatorThreads(d, cpuCores)
 	m := mobilefacenet(modelPath)
 	defer m.Destroy()
+	common.SetEstimatorThreads(m, cpuCores)
 	extract_features(d, m, imgPath, "4.jpg")
 }
 
@@ -54,7 +59,7 @@ func extract_features(d detecter.Detecter, r recognizer.Recognizer, imgPath stri
 		log.Fatalln("load image failed,", err)
 	}
 	img := common.NewImage(imgLoaded)
-	faces, err := d.DetectFace(img)
+	faces, err := d.Detect(img)
 	if err != nil {
 		log.Fatalln(err)
 	}

go/examples/tracker/main.go

@@ -48,7 +48,7 @@ func track(d detecter.Detecter, t *tracker.Tracker, imgPath string, filename str
 		log.Fatalln("load image failed,", err)
 	}
 	img := common.NewImage(imgLoaded)
-	faces, err := d.DetectFace(img)
+	faces, err := d.Detect(img)
 	if err != nil {
 		log.Fatalln(err)
 	}

go/face/detecter/anticonv.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 	"github.com/bububa/openvision/go/face"
 )
@@ -25,20 +27,20 @@ func NewAnticonv() *Anticonv {
 
 // Destroy free detecter
 func (d *Anticonv) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IDetecter
-func (d *Anticonv) Handler() C.IFaceDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Anticonv) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel load model for detecter
 func (d *Anticonv) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
-// DetectFace implement Detecter interface
-func (d *Anticonv) DetectFace(img *common.Image) ([]face.FaceInfo, error) {
-	return DetectFace(d, img)
+// Detect implement Detecter interface
+func (d *Anticonv) Detect(img *common.Image) ([]face.FaceInfo, error) {
+	return Detect(d, img)
 }

go/face/detecter/centerface.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 	"github.com/bububa/openvision/go/face"
 )
@@ -25,20 +27,20 @@ func NewCenterface() *Centerface {
 
 // Destroy free detecter
 func (d *Centerface) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IDetecter
-func (d *Centerface) Handler() C.IFaceDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Centerface) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel load model for detecter
 func (d *Centerface) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
-// DetectFace implement Detecter interface
-func (d *Centerface) DetectFace(img *common.Image) ([]face.FaceInfo, error) {
-	return DetectFace(d, img)
+// Detect implement Detecter interface
+func (d *Centerface) Detect(img *common.Image) ([]face.FaceInfo, error) {
+	return Detect(d, img)
 }

go/face/detecter/detecter.go

@@ -17,36 +17,18 @@ import (
 
 // Detecter represents deteter interface
 type Detecter interface {
-	Handler() C.IFaceDetecter
-	LoadModel(modelPath string) error
-	DetectFace(img *common.Image) ([]face.FaceInfo, error)
-	Destroy()
+	common.Estimator
+	Detect(img *common.Image) ([]face.FaceInfo, error)
 }
 
-// LoadModel load detecter model
-func LoadModel(d Detecter, modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(d.Handler())), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
-	return nil
-}
-
-// Destroy a detecter
-func Destroy(d Detecter) {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(d.Handler())))
-}
-
-// DetectFace detect face useing detecter
-func DetectFace(d Detecter, img *common.Image) ([]face.FaceInfo, error) {
+// Detect detect face useing detecter
+func Detect(d Detecter, img *common.Image) ([]face.FaceInfo, error) {
 	imgWidth := img.WidthF64()
 	imgHeight := img.HeightF64()
 	data := img.Bytes()
 	CFaces := face.NewCFaceInfoVector()
 	defer face.FreeCFaceInfoVector(CFaces)
-	errCode := C.detect_face(d.Handler(), (*C.uchar)(unsafe.Pointer(&data[0])), C.int(imgWidth), C.int(imgHeight), (*C.FaceInfoVector)(unsafe.Pointer(CFaces)))
+	errCode := C.detect_face((C.IFaceDetecter)(d.Pointer()), (*C.uchar)(unsafe.Pointer(&data[0])), C.int(imgWidth), C.int(imgHeight), (*C.FaceInfoVector)(unsafe.Pointer(CFaces)))
 	if errCode != 0 {
 		return nil, openvision.DetectFaceError(int(errCode))
 	}

go/face/detecter/mtcnn.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 	"github.com/bububa/openvision/go/face"
 )
@@ -25,20 +27,20 @@ func NewMtcnn() *Mtcnn {
 
 // Destroy free detecter
 func (d *Mtcnn) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IFaceDetecter
-func (d *Mtcnn) Handler() C.IFaceDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Mtcnn) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel implement Detecter interface
 func (d *Mtcnn) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
-// DetectFace implement Detecter interface
-func (d *Mtcnn) DetectFace(img *common.Image) ([]face.FaceInfo, error) {
-	return DetectFace(d, img)
+// Detect implement Detecter interface
+func (d *Mtcnn) Detect(img *common.Image) ([]face.FaceInfo, error) {
+	return Detect(d, img)
 }

go/face/detecter/retinaface.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 	"github.com/bububa/openvision/go/face"
 )
@@ -25,19 +27,20 @@ func NewRetinaFace() *RetinaFace {
 
 // Destroy free detecter
 func (d *RetinaFace) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IFaceDetecter
-func (d *RetinaFace) Handler() C.IFaceDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *RetinaFace) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel implement Detecter interface
 func (d *RetinaFace) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
-func (d *RetinaFace) DetectFace(img *common.Image) ([]face.FaceInfo, error) {
-	return DetectFace(d, img)
+// Detect implement Detecter interface
+func (d *RetinaFace) Detect(img *common.Image) ([]face.FaceInfo, error) {
+	return Detect(d, img)
 }

go/face/detecter/scrfd.go

@@ -0,0 +1,46 @@
+package detecter
+
+/*
+#include <stdlib.h>
+#include <stdbool.h>
+#include "openvision/face/detecter.h"
+*/
+import "C"
+import (
+	"unsafe"
+
+	"github.com/bububa/openvision/go/common"
+	"github.com/bububa/openvision/go/face"
+)
+
+// Scrfd represents scrfd detecter
+type Scrfd struct {
+	d C.IFaceDetecter
+}
+
+// NewScrfd returns a new Scrfd
+func NewScrfd() *Scrfd {
+	return &Scrfd{
+		d: C.new_scrfd(),
+	}
+}
+
+// Destroy free detecter
+func (d *Scrfd) Destroy() {
+	common.DestroyEstimator(d)
+}
+
+// LoadModel implement Detecter interface
+func (d *Scrfd) LoadModel(modelPath string) error {
+	return common.EstimatorLoadModel(d, modelPath)
+}
+
+// Pointer implement Estimator interface
+func (d *Scrfd) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
+}
+
+// Detect implement Detecter interface
+func (d *Scrfd) Detect(img *common.Image) ([]face.FaceInfo, error) {
+	return Detect(d, img)
+}

go/face/detecter/yoloface.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 	"github.com/bububa/openvision/go/face"
 )
@@ -25,20 +27,20 @@ func NewYoloFace() *YoloFace {
 
 // Destroy free detecter
 func (d *YoloFace) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IFaceDetecter
-func (d *YoloFace) Handler() C.IFaceDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *YoloFace) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel implement Detecter interface
 func (d *YoloFace) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
-// DetectFace implement Detecter interface
-func (d *YoloFace) DetectFace(img *common.Image) ([]face.FaceInfo, error) {
-	return DetectFace(d, img)
+// Detect implement Detecter interface
+func (d *YoloFace) Detect(img *common.Image) ([]face.FaceInfo, error) {
+	return Detect(d, img)
 }

go/face/face_info.go

@@ -27,13 +27,13 @@ type FaceInfo struct {
 // GoFaceInfo convert c FaceInfo to go type
 func GoFaceInfo(cInfo *C.FaceInfo, w float64, h float64) FaceInfo {
 	info := FaceInfo{
-		Score: float32(cInfo.score_),
+		Score: float32(cInfo.score),
 		Mask:  bool(cInfo.mask_),
 		Rect: common.Rect(
-			float64(cInfo.location_.x)/w,
-			float64(cInfo.location_.y)/h,
-			float64(cInfo.location_.width)/w,
-			float64(cInfo.location_.height)/h,
+			float64(cInfo.rect.x)/w,
+			float64(cInfo.rect.y)/h,
+			float64(cInfo.rect.width)/w,
+			float64(cInfo.rect.height)/h,
 		),
 	}
 	for i := 0; i < 5; i++ {
@@ -48,9 +48,9 @@ func GoFaceInfo(cInfo *C.FaceInfo, w float64, h float64) FaceInfo {
 // CFaceInfo convert FaceInfo to C.FaceInfo
 func (f FaceInfo) CFaceInfo(w float64, h float64) *C.FaceInfo {
 	ret := (*C.FaceInfo)(C.malloc(C.sizeof_FaceInfo))
-	ret.score_ = C.float(f.Score)
+	ret.score = C.float(f.Score)
 	ret.mask_ = C.bool(f.Mask)
-	ret.location_ = C.Rect{
+	ret.rect = C.Rect{
 		C.int(f.Rect.X * w),
 		C.int(f.Rect.Y * h),
 		C.int(f.Rect.Width * w),

go/face/hopenet/hopenet.go

@@ -26,20 +26,20 @@ func NewHopenet() *Hopenet {
 	}
 }
 
+// Pointer implement Estimator interface
+func (h *Hopenet) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(h.d)
+}
+
 // LoadModel load detecter model
 func (h *Hopenet) LoadModel(modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(h.d)), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
+	return common.EstimatorLoadModel(h, modelPath)
 	return nil
 }
 
 // Destroy destroy C.IHopeNet
 func (h *Hopenet) Destroy() {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(h.d)))
+	common.DestroyEstimator(h)
 }
 
 // Detect head pose
@@ -51,7 +51,7 @@ func (h *Hopenet) Detect(img *common.Image, faceRect common.Rectangle) (face.Hea
 	CHeadPose := face.NewCHeadPose()
 	defer C.free(unsafe.Pointer(CHeadPose))
 	errCode := C.hopenet_detect(
-		h.d,
+		(C.IHopenet)(h.Pointer()),
 		(*C.uchar)(unsafe.Pointer(&data[0])),
 		C.int(imgWidth), C.int(imgHeight),
 		(*C.Rect)(unsafe.Pointer(CRect)),

go/face/landmarker/insightface.go

@@ -6,7 +6,11 @@ package landmarker
 #include "openvision/face/landmarker.h"
 */
 import "C"
-import "github.com/bububa/openvision/go/common"
+import (
+	"unsafe"
+
+	"github.com/bububa/openvision/go/common"
+)
 
 // Insightface represents Insightface landmarker
 type Insightface struct {
@@ -20,19 +24,19 @@ func NewInsightface() *Insightface {
 	}
 }
 
-// Handler returns C.ILandmarker
-func (d *Insightface) Handler() C.IFaceLandmarker {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Insightface) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel implement Landmarker interface
 func (d *Insightface) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // Destroy implement Landmarker interface
 func (d *Insightface) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
 // ExtractKeypoints implement Landmarker interface

go/face/landmarker/landmarker.go

@@ -16,26 +16,8 @@ import (
 
 // Landmarker represents landmarker interface
 type Landmarker interface {
-	Handler() C.IFaceLandmarker
-	LoadModel(modelPath string) error
+	common.Estimator
 	ExtractKeypoints(img *common.Image, face common.Rectangle) ([]common.Point, error)
-	Destroy()
-}
-
-// LoadModel load landmarker model
-func LoadModel(d Landmarker, modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(d.Handler())), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
-	return nil
-}
-
-// Destroy a landmarker
-func Destroy(d Landmarker) {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(d.Handler())))
 }
 
 // ExtractKeypoints extract keypoints using landmarker
@@ -47,7 +29,7 @@ func ExtractKeypoints(d Landmarker, img *common.Image, faceRect common.Rectangle
 	defer common.FreeCPoint2fVector(CPoints)
 	CRect := faceRect.CRect(imgWidth, imgHeight)
 	errCode := C.extract_face_keypoints(
-		d.Handler(),
+		(C.IFaceLandmarker)(d.Pointer()),
 		(*C.uchar)(unsafe.Pointer(&data[0])),
 		C.int(imgWidth), C.int(imgHeight),
 		(*C.Rect)(unsafe.Pointer(CRect)),

go/face/landmarker/scrfd.go

@@ -0,0 +1,45 @@
+package landmarker
+
+/*
+#include <stdlib.h>
+#include <stdbool.h>
+#include "openvision/face/landmarker.h"
+*/
+import "C"
+import (
+	"unsafe"
+
+	"github.com/bububa/openvision/go/common"
+)
+
+// Scrfd represents Scrfd landmarker
+type Scrfd struct {
+	d C.IFaceLandmarker
+}
+
+// NewScrfd returns a new Scrfd landmarker
+func NewScrfd() *Scrfd {
+	return &Scrfd{
+		d: C.new_scrfd_landmarker(),
+	}
+}
+
+// Pointer implement Estimator interface
+func (d *Scrfd) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
+}
+
+// LoadModel implement Landmarker interface
+func (d *Scrfd) LoadModel(modelPath string) error {
+	return common.EstimatorLoadModel(d, modelPath)
+}
+
+// Destroy implement Landmarker interface
+func (d *Scrfd) Destroy() {
+	common.DestroyEstimator(d)
+}
+
+// ExtractKeypoints implement Landmarker interface
+func (d *Scrfd) ExtractKeypoints(img *common.Image, faceRect common.Rectangle) ([]common.Point, error) {
+	return ExtractKeypoints(d, img, faceRect)
+}

go/face/landmarker/zq.go

@@ -6,7 +6,11 @@ package landmarker
 #include "openvision/face/landmarker.h"
 */
 import "C"
-import "github.com/bububa/openvision/go/common"
+import (
+	"unsafe"
+
+	"github.com/bububa/openvision/go/common"
+)
 
 // Zq represents Zq landmarker
 type Zq struct {
@@ -20,19 +24,19 @@ func NewZq() *Zq {
 	}
 }
 
-// Handler returns C.ILandmarker
-func (d *Zq) Handler() C.IFaceLandmarker {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Zq) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel implement Landmarker interface
 func (d *Zq) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // Destroy implement Landmarker interface
 func (d *Zq) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
 // ExtractKeypoints implement Landmarker interface

go/face/recognizer/mobilefacenet.go

@@ -6,7 +6,11 @@ package recognizer
 #include "openvision/face/recognizer.h"
 */
 import "C"
-import "github.com/bububa/openvision/go/common"
+import (
+	"unsafe"
+
+	"github.com/bububa/openvision/go/common"
+)
 
 // Mobilefacenet represents Mobilefacenet recognizer
 type Mobilefacenet struct {
@@ -20,19 +24,19 @@ func NewMobilefacenet() *Mobilefacenet {
 	}
 }
 
-// Handler returns C.IFaceRecognizer
-func (d *Mobilefacenet) Handler() C.IFaceRecognizer {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Mobilefacenet) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel implement Recognizer interface
 func (d *Mobilefacenet) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // Destroy implement Recognizer interface
 func (d *Mobilefacenet) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
 // ExtractFeatures implement Recognizer interface

go/face/recognizer/recognizer.go

@@ -16,26 +16,8 @@ import (
 
 // Recognizer represents Recognizer interface
 type Recognizer interface {
-	Handler() C.IFaceRecognizer
-	LoadModel(modelPath string) error
+	common.Estimator
 	ExtractFeatures(img *common.Image, face common.Rectangle) ([]float64, error)
-	Destroy()
-}
-
-// LoadModel load recognizer model
-func LoadModel(r Recognizer, modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(r.Handler())), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
-	return nil
-}
-
-// Destroy a recognizer
-func Destroy(r Recognizer) {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(r.Handler())))
 }
 
 // ExtractFeatures extract features using recognizer
@@ -47,7 +29,7 @@ func ExtractFeatures(r Recognizer, img *common.Image, faceRect common.Rectangle)
 	defer common.FreeCFloatVector(CFeatures)
 	CRect := faceRect.CRect(imgWidth, imgHeight)
 	errCode := C.extract_feature(
-		r.Handler(),
+		(C.IFaceRecognizer)(r.Pointer()),
 		(*C.uchar)(unsafe.Pointer(&data[0])),
 		C.int(imgWidth), C.int(imgHeight),
 		(*C.Rect)(unsafe.Pointer(CRect)),

go/hand/detecter/detecter.go

@@ -16,26 +16,8 @@ import (
 
 // Detecter represents deteter interface
 type Detecter interface {
-	Handler() C.IHandDetecter
-	LoadModel(modelPath string) error
+	common.Estimator
 	Detect(img *common.Image) ([]common.ObjectInfo, error)
-	Destroy()
-}
-
-// LoadModel load detecter model
-func LoadModel(d Detecter, modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(d.Handler())), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
-	return nil
-}
-
-// Destroy a detecter
-func Destroy(d Detecter) {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(d.Handler())))
 }
 
 // Detect detect hand ROI
@@ -46,7 +28,7 @@ func Detect(d Detecter, img *common.Image) ([]common.ObjectInfo, error) {
 	cObjs := common.NewCObjectInfoVector()
 	defer common.FreeCObjectInfoVector(cObjs)
 	errCode := C.extract_hand_rois(
-		d.Handler(),
+		(C.IHandDetecter)(d.Pointer()),
 		(*C.uchar)(unsafe.Pointer(&data[0])),
 		C.int(imgWidth),
 		C.int(imgHeight),

go/hand/detecter/nanodet.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 )
 
@@ -24,17 +26,17 @@ func NewNanodet() *Nanodet {
 
 // Destroy free detecter
 func (d *Nanodet) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IHandDetecter
-func (d *Nanodet) Handler() C.IHandDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Nanodet) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel load model for detecter
 func (d *Nanodet) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // Detect implement Detecter interface

go/hand/detecter/yolox.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 )
 
@@ -24,17 +26,17 @@ func NewYolox() *Yolox {
 
 // Destroy free detecter
 func (d *Yolox) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IHandDetecter
-func (d *Yolox) Handler() C.IHandDetecter {
-	return d.d
+// Pointer implenment Estimator interface
+func (d *Yolox) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel load model for detecter
 func (d *Yolox) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // Detect implement Detecter interface

go/hand/pose/estimator.go

@@ -16,26 +16,8 @@ import (
 
 // Estimator represents estimator interface
 type Estimator interface {
-	Handler() C.IHandPoseEstimator
-	LoadModel(modelPath string) error
+	common.Estimator
 	Detect(img *common.Image, rect common.Rectangle) ([]common.Point, error)
-	Destroy()
-}
-
-// LoadModel load detecter model
-func LoadModel(d Estimator, modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(d.Handler())), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
-	return nil
-}
-
-// Destroy a estimator
-func Destroy(d Estimator) {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(d.Handler())))
 }
 
 // Detect detect hand pose
@@ -47,7 +29,7 @@ func Detect(d Estimator, img *common.Image, rect common.Rectangle) ([]common.Poi
 	defer common.FreeCPoint2fVector(CPoints)
 	CRect := rect.CRect(imgWidth, imgHeight)
 	errCode := C.hand_pose(
-		d.Handler(),
+		(C.IHandPoseEstimator)(d.Pointer()),
 		(*C.uchar)(unsafe.Pointer(&data[0])),
 		C.int(imgWidth), C.int(imgHeight),
 		(*C.Rect)(unsafe.Pointer(CRect)),

go/hand/pose/handpose.go

@@ -7,6 +7,8 @@ package pose
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 )
 
@@ -24,17 +26,17 @@ func NewHandPoseEstimator() *HandPoseEstimator {
 
 // Destroy free Estimator
 func (d *HandPoseEstimator) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IHandPoseEstimator
-func (d *HandPoseEstimator) Handler() C.IHandPoseEstimator {
-	return d.d
+// Pointer implement Estimator interface
+func (d *HandPoseEstimator) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel load model for  estimator
 func (d *HandPoseEstimator) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // Detect implement Estimator interface

go/pose/detecter/detecter.go

@@ -16,26 +16,8 @@ import (
 
 // Detecter represents deteter interface
 type Detecter interface {
-	Handler() C.IPoseDetecter
-	LoadModel(modelPath string) error
+	common.Estimator
 	ExtractKeypoints(img *common.Image) ([]common.ObjectInfo, error)
-	Destroy()
-}
-
-// LoadModel load detecter model
-func LoadModel(d Detecter, modelPath string) error {
-	cpath := C.CString(modelPath)
-	defer C.free(unsafe.Pointer(cpath))
-	retCode := C.load_model((C.IEstimator)(unsafe.Pointer(d.Handler())), cpath)
-	if retCode != 0 {
-		return openvision.LoadModelError(int(retCode))
-	}
-	return nil
-}
-
-// Destroy a detecter
-func Destroy(d Detecter) {
-	C.destroy_estimator((C.IEstimator)(unsafe.Pointer(d.Handler())))
 }
 
 // ExtractKeypoints detect pose keypoints using detecter
@@ -46,7 +28,7 @@ func ExtractKeypoints(d Detecter, img *common.Image) ([]common.ObjectInfo, error
 	cObjs := common.NewCObjectInfoVector()
 	defer common.FreeCObjectInfoVector(cObjs)
 	errCode := C.extract_pose_rois(
-		d.Handler(),
+		(C.IPoseDetecter)(d.Pointer()),
 		(*C.uchar)(unsafe.Pointer(&data[0])),
 		C.int(imgWidth),
 		C.int(imgHeight),
@@ -62,7 +44,7 @@ func ExtractKeypoints(d Detecter, img *common.Image) ([]common.ObjectInfo, error
 		defer common.FreeCKeypointVector(cKeypoints)
 		cROI := (*C.ObjectInfo)(unsafe.Pointer(uintptr(ptr) + uintptr(C.sizeof_ObjectInfo*C.int(i))))
 		errCode := C.extract_pose_keypoints(
-			d.Handler(),
+			(C.IPoseDetecter)(d.Pointer()),
 			(*C.uchar)(unsafe.Pointer(&data[0])),
 			C.int(imgWidth),
 			C.int(imgHeight),
@@ -80,7 +62,7 @@ func ExtractKeypoints(d Detecter, img *common.Image) ([]common.ObjectInfo, error
 				float64(cROI.rect.width)/imgWidth,
 				float64(cROI.rect.height)/imgHeight,
 			),
-			Score: float32(cROI.prob),
+			Score: float32(cROI.score),
 		})
 
 	}

go/pose/detecter/ultralight.go

@@ -7,6 +7,8 @@ package detecter
 */
 import "C"
 import (
+	"unsafe"
+
 	"github.com/bububa/openvision/go/common"
 )
 
@@ -24,17 +26,17 @@ func NewUltralight() *Ultralight {
 
 // Destroy free detecter
 func (d *Ultralight) Destroy() {
-	Destroy(d)
+	common.DestroyEstimator(d)
 }
 
-// Handler returns C.IPoseDetecter
-func (d *Ultralight) Handler() C.IPoseDetecter {
-	return d.d
+// Pointer implement Estimator interface
+func (d *Ultralight) Pointer() unsafe.Pointer {
+	return unsafe.Pointer(d.d)
 }
 
 // LoadModel load model for detecter
 func (d *Ultralight) LoadModel(modelPath string) error {
-	return LoadModel(d, modelPath)
+	return common.EstimatorLoadModel(d, modelPath)
 }
 
 // ExtractKeypoints implement Detecter interface

src/common/common.cpp

@@ -1,8 +1,8 @@
 #include "common.h"
 #include <algorithm>
-#include <iostream>
 #include <math.h>
 #include <float.h>
+#include "cpu.h"
 
 #ifdef OV_VULKAN
 #include "gpu.h"
@@ -28,6 +28,16 @@ void destroy_gpu_instance() {
 #endif // OV_VULKAN
 }
 
+int get_big_cpu_count() {
+    return ncnn::get_big_cpu_count();
+}
+
+void set_omp_num_threads(int n) {
+#ifdef OV_OPENMP
+    ncnn::set_omp_num_threads(n);
+#endif
+}
+
 int load_model(IEstimator d, const char *root_path) {
     return static_cast<ov::Estimator*>(d)->LoadModel(root_path);
 }
@@ -36,6 +46,10 @@ void destroy_estimator(IEstimator d) {
     delete static_cast<ov::Estimator*>(d);
 }
 
+void set_num_threads(IEstimator d, int n) {
+    static_cast<ov::Estimator*>(d)->set_num_threads(n);
+}
+
 void FreePoint2fVector(Point2fVector* p) {
     if (p->points != NULL) {
         free(p->points);
@@ -97,9 +111,44 @@ void FreeObjectInfoVector(ObjectInfoVector *p) {
 }
 namespace ov {
 
+Estimator::Estimator() {
+    net_ = new ncnn::Net();
+	initialized_ = false;
+#ifdef OV_VULKAN
+    net_->opt.use_vulkan_compute = true;
+#endif // OV_VULKAN
+}
+
+Estimator::~Estimator() {
+    if (net_) {
+        net_->clear();
+    }
+}
+
+int Estimator::LoadModel(const char * root_path) {
+	std::string param_file = std::string(root_path) + "/param";
+	std::string bin_file = std::string(root_path) + "/bin";
+	if (net_->load_param(param_file.c_str()) == -1 ||
+		net_->load_model(bin_file.c_str()) == -1) {
+		return 10000;
+	}
+
+	initialized_ = true;
+
+	return 0;
+}
+
+void Estimator::set_num_threads(int n) {
+    num_threads = n;
+    if (net_) {
+        net_->opt.num_threads = n;
+    }
+}
+
+
 int RatioAnchors(const Rect & anchor,
 	const std::vector<float>& ratios, 
-	std::vector<Rect>* anchors) {
+	std::vector<Rect>* anchors, int threads_num) {
 	anchors->clear();
 	Point center = Point(anchor.x + (anchor.width - 1) * 0.5f,
 		anchor.y + (anchor.height - 1) * 0.5f);
@@ -123,7 +172,7 @@ int RatioAnchors(const Rect & anchor,
 }
 
 int ScaleAnchors(const std::vector<Rect>& ratio_anchors,
-	const std::vector<float>& scales, std::vector<Rect>* anchors) {
+	const std::vector<float>& scales, std::vector<Rect>* anchors, int threads_num) {
 	anchors->clear();
 #if defined(_OPENMP)
 #pragma omp parallel for num_threads(threads_num)
@@ -150,12 +199,13 @@ int ScaleAnchors(const std::vector<Rect>& ratio_anchors,
 int GenerateAnchors(const int & base_size,
 	const std::vector<float>& ratios, 
 	const std::vector<float> scales,
-	std::vector<Rect>* anchors) {
+	std::vector<Rect>* anchors,
+    int threads_num) {
 	anchors->clear();
 	Rect anchor = Rect(0, 0, base_size, base_size);
 	std::vector<Rect> ratio_anchors;
-	RatioAnchors(anchor, ratios, &ratio_anchors);
-	ScaleAnchors(ratio_anchors, scales, anchors);
+	RatioAnchors(anchor, ratios, &ratio_anchors, threads_num);
+	ScaleAnchors(ratio_anchors, scales, anchors, threads_num);
 	
 	return 0;
 }
@@ -207,14 +257,14 @@ void qsort_descent_inplace(std::vector<ObjectInfo>& objects, int left, int right
 {
     int i = left;
     int j = right;
-    float p = objects[(left + right) / 2].prob;
+    float p = objects[(left + right) / 2].score;
 
     while (i <= j)
     {
-        while (objects[i].prob > p)
+        while (objects[i].score > p)
             i++;
 
-        while (objects[j].prob < p)
+        while (objects[j].score < p)
             j--;
 
         if (i <= j)
@@ -281,6 +331,44 @@ void nms_sorted_bboxes(const std::vector<ObjectInfo>& objects, std::vector<int>&
             picked.push_back(i);
     }
 }
+//
+// insightface/detection/scrfd/mmdet/core/anchor/anchor_generator.py gen_single_level_base_anchors()
+ncnn::Mat generate_anchors(int base_size, const ncnn::Mat& ratios, const ncnn::Mat& scales)
+{
+    int num_ratio = ratios.w;
+    int num_scale = scales.w;
+
+    ncnn::Mat anchors;
+    anchors.create(4, num_ratio * num_scale);
+
+    const float cx = 0;
+    const float cy = 0;
+
+    for (int i = 0; i < num_ratio; i++)
+    {
+        float ar = ratios[i];
+
+        int r_w = round(base_size / sqrt(ar));
+        int r_h = round(r_w * ar); //round(base_size * sqrt(ar));
+
+        for (int j = 0; j < num_scale; j++)
+        {
+            float scale = scales[j];
+
+            float rs_w = r_w * scale;
+            float rs_h = r_h * scale;
+
+            float* anchor = anchors.row(i * num_scale + j);
+
+            anchor[0] = cx - rs_w * 0.5f;
+            anchor[1] = cy - rs_h * 0.5f;
+            anchor[2] = cx + rs_w * 0.5f;
+            anchor[3] = cy + rs_h * 0.5f;
+        }
+    }
+
+    return anchors;
+}
 
 int generate_grids_and_stride(const int target_size, std::vector<int>& strides, std::vector<GridAndStride>& grid_strides)
 {

src/common/common.h

@@ -43,7 +43,7 @@ typedef struct Rect {
 
 typedef struct Keypoint {
     Point2f p;
-    float prob;
+    float score;
 } Keypoint;
 
 
@@ -54,8 +54,11 @@ typedef void* IEstimator;
 int get_gpu_count();
 int create_gpu_instance();
 void destroy_gpu_instance();
+int get_big_cpu_count(); 
+void set_omp_num_threads(int n);
 int load_model(IEstimator e, const char* root_path);
 void destroy_estimator(IEstimator e);
+void set_num_threads(IEstimator e, int n);
 
 typedef struct Point2fVector {
     Point2f* points;
@@ -96,7 +99,7 @@ void KeypointVectorSetValue(KeypointVector *p, int i, const Keypoint* val);
 
 typedef struct ObjectInfoC {
     Rect rect;
-    float prob;
+    float score;
     int label;
     KeypointVector* pts;
 } ObjectInfo;

src/common/common.hpp

@@ -10,12 +10,17 @@
 #endif
 
 namespace ov {
-const int threads_num = 2;
 
 class Estimator {
 public:
-    virtual ~Estimator(){};
-    virtual int LoadModel(const char* root_path) = 0;
+    Estimator();
+    virtual ~Estimator();
+    virtual int LoadModel(const char* root_path);
+    virtual void set_num_threads(int n);
+protected:
+    int num_threads = 2;
+    ncnn::Net* net_;
+    bool initialized_ = false;
 };
 
 // Wrapper for an individual cv::cvSize
@@ -78,17 +83,17 @@ typedef struct Rect {
 
 struct ImageInfo {
     std::string label_;
-    float score_;
+    float score;
 };
 
 struct Keypoint {
-    ov::Point2f p;
-    float prob;
+    Point2f p;
+    float score;
 };
 
 struct ObjectInfo {
 	Rect rect;
-	float prob;
+	float score;
     int label;
     std::vector<Point2f> pts;
 };
@@ -101,14 +106,15 @@ struct GridAndStride
 };
 
 int RatioAnchors(const Rect & anchor,
-	const std::vector<float>& ratios, std::vector<Rect>* anchors);
+	const std::vector<float>& ratios, std::vector<Rect>* anchors, int threads_num);
 
 int ScaleAnchors(const std::vector<Rect>& ratio_anchors,
-	const std::vector<float>& scales, std::vector<Rect>* anchors);
+	const std::vector<float>& scales, std::vector<Rect>* anchors, int threads_num);
 
 int GenerateAnchors(const int & base_size,
 	const std::vector<float>& ratios, const std::vector<float> scales,
-	std::vector<Rect>* anchors);
+	std::vector<Rect>* anchors,
+    int threads_num);
 
 float InterRectArea(const Rect & a,
 	const Rect & b);
@@ -128,7 +134,7 @@ int const NMS(const std::vector<T>& inputs, std::vector<T>* result,
     inputs_tmp.assign(inputs.begin(), inputs.end());
     std::sort(inputs_tmp.begin(), inputs_tmp.end(),
     [](const T& a, const T& b) {
-        return a.score_ > b.score_;
+        return a.score > b.score;
     });
 
     std::vector<int> indexes(inputs_tmp.size());
@@ -145,7 +151,7 @@ int const NMS(const std::vector<T>& inputs, std::vector<T>* result,
         for (int i = 1; i < tmp_indexes.size(); i++) {
             int tmp_i = tmp_indexes[i];
             float iou = 0.0f;
-            ComputeIOU(inputs_tmp[good_idx].location_, inputs_tmp[tmp_i].location_, &iou, type);
+            ComputeIOU(inputs_tmp[good_idx].rect, inputs_tmp[tmp_i].rect, &iou, type);
             if (iou <= threshold) {
                 indexes.push_back(tmp_i);
             }
@@ -160,6 +166,9 @@ void qsort_descent_inplace(std::vector<ObjectInfo>& objects);
 
 void nms_sorted_bboxes(const std::vector<ObjectInfo>& objects, std::vector<int>& picked, float nms_threshold);
 
+// insightface/detection/scrfd/mmdet/core/anchor/anchor_generator.py gen_single_level_base_anchors()
+ncnn::Mat generate_anchors(int base_size, const ncnn::Mat& ratios, const ncnn::Mat& scales);
+
 int generate_grids_and_stride(const int target_size, std::vector<int>& strides, std::vector<GridAndStride>& grid_strides);
 
 float sigmoid(float x);

src/face/common.h

@@ -13,8 +13,8 @@ typedef ovface::TrackedFaceInfo TrackedFaceInfo;
 typedef ovface::HeadPose HeadPose;
 #else
 typedef struct FaceInfo {
-    Rect location_;
-    float score_;
+    Rect rect;
+    float score;
     float keypoints_[10];
     bool mask_;
 } FaceInfo;

src/face/common/common.cpp

@@ -33,7 +33,86 @@ void FreeTrackedFaceInfoVector(TrackedFaceInfoVector *p) {
 
 namespace ovface {
 
-float CalculateSimilarity(const std::vector<float>&feature1, const std::vector<float>& feature2) {
+void qsort_descent_inplace(std::vector<FaceInfo>& objects, int left, int right)
+{
+    int i = left;
+    int j = right;
+    float p = objects[(left + right) / 2].score;
+
+    while (i <= j)
+    {
+        while (objects[i].score > p)
+            i++;
+
+        while (objects[j].score < p)
+            j--;
+
+        if (i <= j)
+        {
+            // swap
+            std::swap(objects[i], objects[j]);
+
+            i++;
+            j--;
+        }
+    }
+
+    #pragma omp parallel sections
+    {
+        #pragma omp section
+        {
+            if (left < j) qsort_descent_inplace(objects, left, j);
+        }
+        #pragma omp section
+        {
+            if (i < right) qsort_descent_inplace(objects, i, right);
+        }
+    }
+}
+
+void qsort_descent_inplace(std::vector<FaceInfo>& objects) 
+{
+    if (objects.empty())
+        return;
+
+    qsort_descent_inplace(objects, 0, objects.size() - 1);
+}
+
+void nms_sorted_bboxes(const std::vector<FaceInfo>& objects, std::vector<int>& picked, float nms_threshold)
+{
+    picked.clear();
+
+    const int n = objects.size();
+
+    std::vector<float> areas(n);
+    for (int i = 0; i < n; i++)
+    {
+        areas[i] = objects[i].rect.area();
+    }
+
+    for (int i = 0; i < n; i++)
+    {
+        const FaceInfo& a = objects[i];
+
+        int keep = 1;
+        for (int j = 0; j < (int)picked.size(); j++)
+        {
+            const FaceInfo& b = objects[picked[j]];
+
+            // intersection over union
+            float inter_area = InterRectArea(a.rect, b.rect);
+            float union_area = areas[i] + areas[picked[j]] - inter_area;
+            // float IoU = inter_area / union_area
+            if (inter_area / union_area > nms_threshold)
+                keep = 0;
+        }
+
+        if (keep)
+            picked.push_back(i);
+    }
+}
+
+float CalculateSimilarity(const std::vector<float>&feature1, const std::vector<float>& feature2, int threads_num) {
 	if (feature1.size() != feature2.size()) {
 		return 10003;
 	}
@@ -41,7 +120,7 @@ float CalculateSimilarity(const std::vector<float>&feature1, const std::vector<f
 	float feature_norm1 = 0.0f;
 	float feature_norm2 = 0.0f;
 #ifdef OV_OPENMP
-#pragma omp parallel for num_threads(ov::threads_num)
+#pragma omp parallel for num_threads(threads_num)
 #endif
 	for(int i = 0; i < kFaceFeatureDim; ++i) {
 		inner_product += feature1[i] * feature2[i];

src/face/common/common.hpp

@@ -8,8 +8,8 @@ namespace ovface {
 #define kFaceFeatureDim 128
 #define kFaceNameDim 256
 struct FaceInfo {
-    ov::Rect location_;
-	float score_;
+    ov::Rect rect;
+	float score;
 	float keypoints_[10];
     bool mask_;
 };
@@ -25,7 +25,15 @@ struct HeadPose
     float pitch;
     float yaw;
 };
-}
+
+void qsort_descent_inplace(std::vector<FaceInfo>& objects, int left, int right);
+
+void qsort_descent_inplace(std::vector<FaceInfo>& objects); 
+
+void nms_sorted_bboxes(const std::vector<FaceInfo>& objects, std::vector<int>& picked, float nms_threshold);
 
 float CalculateSimilarity(const std::vector<float>&feature1, const std::vector<float>& feature2);
+
+}
+
 #endif // !_FACE_COMMON_H_

src/face/detecter.h

@@ -12,6 +12,7 @@ extern "C" {
     IFaceDetecter new_centerface();
     IFaceDetecter new_mtcnn();
     IFaceDetecter new_yoloface();
+    IFaceDetecter new_scrfd();
     IFaceDetecter new_anticonv();
     int detect_face(IFaceDetecter d, const unsigned char* rgbdata, int img_width, int img_height, FaceInfoVector* faces); 
 #ifdef __cplusplus

src/face/detecter/anticonv/anticonv.cpp

@@ -5,44 +5,26 @@
 #endif // OV_VULKAN
 
 namespace ovface {
-AntiConv::AntiConv() :
-	anticonv_net_(new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    anticonv_net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-
-}
-
-AntiConv::~AntiConv() {
-	if (anticonv_net_) {
-		anticonv_net_->clear();
-	}
-}
 
 int AntiConv::LoadModel(const char * root_path) {
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (anticonv_net_->load_param(param_file.c_str()) == -1 ||
-		anticonv_net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
-
+    int ret = Estimator::LoadModel(root_path);
+    if (ret != 0) {
+        return ret;
+    }
 	// generate anchors
 	for (int i = 0; i < 3; ++i) {
 		ANCHORS anchors;
 		if (0 == i) {
-			GenerateAnchors(16, { 1.0f }, { 32, 16 }, &anchors);
+			GenerateAnchors(16, { 1.0f }, { 32, 16 }, &anchors, num_threads);
 		}
 		else if (1 == i) {
-			GenerateAnchors(16, { 1.0f }, { 8, 4 }, &anchors);
+			GenerateAnchors(16, { 1.0f }, { 8, 4 }, &anchors, num_threads);
 		}
 		else {
-			GenerateAnchors(16, { 1.0f }, { 2, 1 }, &anchors);
+			GenerateAnchors(16, { 1.0f }, { 2, 1 }, &anchors, num_threads);
 		}
 		anchors_generated_.push_back(anchors);
 	}
-	initialized_ = true;
 
 	return 0;
 }
@@ -60,7 +42,7 @@ int AntiConv::DetectFace(const unsigned char* rgbdata,
 
 	float factor_x = static_cast<float>(img_width) / inputSize_.width;
 	float factor_y = static_cast<float>(img_height) / inputSize_.height;
-	ncnn::Extractor ex = anticonv_net_->create_extractor();
+	ncnn::Extractor ex = net_->create_extractor();
 	ncnn::Mat in = ncnn::Mat::from_pixels_resize(rgbdata,
 		ncnn::Mat::PIXEL_RGB, img_width, img_height, inputSize_.width, inputSize_.height);
 	ex.input("data", in);
@@ -115,9 +97,9 @@ int AntiConv::DetectFace(const unsigned char* rgbdata,
 
 					FaceInfo face_info;
 					memset(&face_info, 0, sizeof(face_info));
-					face_info.score_ = score;
+					face_info.score = score;
 					face_info.mask_ = (prob > maskThreshold_);
-					face_info.location_ = curr_box;
+					face_info.rect = curr_box;
 					faces_tmp.push_back(face_info);
 				}
 			}

src/face/detecter/anticonv/anticonv.hpp

@@ -8,17 +8,13 @@ namespace ovface {
 using ANCHORS = std::vector<ov::Rect>;
 class AntiConv : public Detecter {
 public:
-	AntiConv();
-	~AntiConv();
 	int LoadModel(const char* root_path);
 	int DetectFace(const unsigned char* rgbdata, 
         int img_width, int img_height,
         std::vector<FaceInfo>* faces);
 
 private:
-	ncnn::Net* anticonv_net_;
 	std::vector<ANCHORS> anchors_generated_;
-	bool initialized_;
 	const int RPNs_[3] = { 32, 16, 8 };
 	const Size inputSize_ = { 640, 640 };
 	const float iouThreshold_ = 0.4f;

src/face/detecter/centerface/centerface.cpp

@@ -5,31 +5,6 @@
 #endif // OV_VULKAN
 
 namespace ovface {
-CenterFace::CenterFace() {
-    centernet_ = new ncnn::Net();
-    initialized_ = false;
-#ifdef OV_VULKAN
-    centernet_->opt.use_vulkan_compute = true;
-#endif // MIRROR_VULKAN
-}
-
-CenterFace::~CenterFace(){
-    if (centernet_) {
-        centernet_->clear();
-    }
-}
-
-int CenterFace::LoadModel(const char* root_path) {
-    std::string param_file = std::string(root_path) + "/param";
-	std::string model_file = std::string(root_path) + "/bin";
-    if (centernet_->load_param(param_file.c_str()) == -1 ||
-        centernet_->load_model(model_file.c_str()) == -1) {
-        return 10000;
-	}
-
-    initialized_ = true;
-    return 0;
-}
 
 int CenterFace::DetectFace(const unsigned char* rgbdata, 
     int img_width, int img_height,
@@ -49,7 +24,7 @@ int CenterFace::DetectFace(const unsigned char* rgbdata,
 
     ncnn::Mat in = ncnn::Mat::from_pixels_resize(rgbdata, ncnn::Mat::PIXEL_RGB,
 		img_width, img_height, img_width_new, img_height_new);
-	ncnn::Extractor ex = centernet_->create_extractor();
+	ncnn::Extractor ex = net_->create_extractor();
 	ex.input("input.1", in);
 	ncnn::Mat mat_heatmap, mat_scale, mat_offset, mat_landmark;
 	ex.extract("537", mat_heatmap);
@@ -78,11 +53,11 @@ int CenterFace::DetectFace(const unsigned char* rgbdata,
 			float xmax = fminf(xmin + s1, img_width_new);
 
             FaceInfo face_info;
-            face_info.score_ = score;
-            face_info.location_.x = scale_x * xmin;
-            face_info.location_.y = scale_y * ymin;
-            face_info.location_.width = scale_x * (xmax - xmin);
-            face_info.location_.height = scale_y * (ymax - ymin);
+            face_info.score = score;
+            face_info.rect.x = scale_x * xmin;
+            face_info.rect.y = scale_y * ymin;
+            face_info.rect.width = scale_x * (xmax - xmin);
+            face_info.rect.height = scale_y * (ymax - ymin);
 
             for (int num = 0; num < 5; ++num) {
                 face_info.keypoints_[num    ] = scale_x * (s1 * mat_landmark.channel(2 * num + 1)[index] + xmin);

src/face/detecter/centerface/centerface.hpp

@@ -8,18 +8,13 @@
 namespace ovface {
 class CenterFace : public Detecter {
 public:
-    CenterFace();
-    ~CenterFace();
-	int LoadModel(const char* root_path);
 	int DetectFace(const unsigned char* rgbdata,
         int img_width, int img_height,
         std::vector<FaceInfo>* faces);
 
 private:
-    ncnn::Net* centernet_ = nullptr;
     const float scoreThreshold_ = 0.5f;
     const float nmsThreshold_ = 0.5f;
-    bool initialized_;
 };
 
 }

src/face/detecter/detecter.cpp

@@ -4,6 +4,7 @@
 #include "retinaface/retinaface.hpp"
 #include "anticonv/anticonv.hpp"
 #include "yoloface/yoloface.hpp"
+#include "scrfd/scrfd.hpp"
 
 IFaceDetecter new_retinaface() {
     return new ovface::RetinaFace();
@@ -21,6 +22,10 @@ IFaceDetecter new_yoloface() {
     return new ovface::YoloFace();
 }
 
+IFaceDetecter new_scrfd() {
+    return new ovface::Scrfd();
+}
+
 IFaceDetecter new_anticonv() {
     return new ovface::AntiConv();
 }
@@ -58,6 +63,10 @@ Detecter* YoloFaceFactory::CreateDetecter() {
 	return new YoloFace();
 }
 
+Detecter* ScrfdFactory::CreateDetecter() {
+	return new Scrfd();
+}
+
 Detecter* AnticonvFactory::CreateDetecter() {
 	return new AntiConv();
 }

src/face/detecter/detecter.hpp

@@ -7,7 +7,6 @@ namespace ovface {
 // 抽象类
 class Detecter: public ov::Estimator {
 public:
-	virtual ~Detecter() {};
 	virtual int DetectFace(const unsigned char* rgbdata, 
         int img_width, int img_height,
         std::vector<FaceInfo>* faces) = 0;
@@ -51,6 +50,13 @@ public:
 	Detecter* CreateDetecter();
 };
 
+class ScrfdFactory : public DetecterFactory {
+public:
+	ScrfdFactory() {}
+	~ScrfdFactory() {}
+	Detecter* CreateDetecter();
+};
+
 class AnticonvFactory : public DetecterFactory {
 public:
 	AnticonvFactory() {}

src/face/detecter/mtcnn/mtcnn.cpp

@@ -32,6 +32,19 @@ Mtcnn::~Mtcnn() {
 	}
 }
 
+void Mtcnn::set_num_threads(int n) {
+    num_threads = n;
+    if (pnet_) {
+        pnet_->opt.num_threads = n;
+    }
+    if (rnet_) {
+        rnet_->opt.num_threads = n;
+    }
+    if (onet_) {
+        onet_->opt.num_threads = n;
+    }
+}
+
 int Mtcnn::LoadModel(const char * root_path) {
 	std::string pnet_param = std::string(root_path) + "/pnet.param";
 	std::string pnet_bin = std::string(root_path) + "/pnet.bin";
@@ -141,12 +154,12 @@ int Mtcnn::PDetect(const ncnn::Mat & img_in,
 				int bbox_height = y2 - y1 + 1;
 
 				FaceInfo face_info;
-				face_info.score_ = score;
-				face_info.location_.x = x1 + x1_reg * bbox_width;
-				face_info.location_.y = y1 + y1_reg * bbox_height;
-				face_info.location_.width = x2 + x2_reg * bbox_width - face_info.location_.x;
-				face_info.location_.height = y2 + y2_reg * bbox_height - face_info.location_.y;
-				face_info.location_ = face_info.location_ & Rect(0, 0, width, height);
+				face_info.score = score;
+				face_info.rect.x = x1 + x1_reg * bbox_width;
+				face_info.rect.y = y1 + y1_reg * bbox_height;
+				face_info.rect.width = x2 + x2_reg * bbox_width - face_info.rect.x;
+				face_info.rect.height = y2 + y2_reg * bbox_height - face_info.rect.y;
+				face_info.rect = face_info.rect & Rect(0, 0, width, height);
 				first_bboxes->push_back(face_info);
 			}
 		}
@@ -159,13 +172,13 @@ int Mtcnn::RDetect(const ncnn::Mat & img_in,
 	std::vector<FaceInfo>* second_bboxes) {
 	second_bboxes->clear();
 	for (int i = 0; i < static_cast<int>(first_bboxes.size()); ++i) {
-		Rect face = first_bboxes.at(i).location_ & Rect(0, 0, img_in.w, img_in.h);
+		Rect face = first_bboxes.at(i).rect & Rect(0, 0, img_in.w, img_in.h);
 		ncnn::Mat img_face, img_resized;
 		ncnn::copy_cut_border(img_in, img_face, face.y, img_in.h - face.br().y, face.x, img_in.w - face.br().x);
 		ncnn::resize_bilinear(img_face, img_resized, 24, 24);
 		ncnn::Extractor ex = rnet_->create_extractor();
 		ex.set_light_mode(true);
-		ex.set_num_threads(2);
+		// ex.set_num_threads(2);
 		ex.input("data", img_resized);
 		ncnn::Mat score_mat, location_mat;
 		ex.extract("prob1", score_mat);
@@ -178,13 +191,13 @@ int Mtcnn::RDetect(const ncnn::Mat & img_in,
 		float h_reg = location_mat[3];
 
 		FaceInfo face_info;
-		face_info.score_ = score;
-		face_info.location_.x = face.x + x_reg * face.width;
-		face_info.location_.y = face.y + y_reg * face.height;
-		face_info.location_.width = face.x + face.width +
-			w_reg * face.width - face_info.location_.x;
-		face_info.location_.height = face.y + face.height +
-			h_reg * face.height - face_info.location_.y;
+		face_info.score = score;
+		face_info.rect.x = face.x + x_reg * face.width;
+		face_info.rect.y = face.y + y_reg * face.height;
+		face_info.rect.width = face.x + face.width +
+			w_reg * face.width - face_info.rect.x;
+		face_info.rect.height = face.y + face.height +
+			h_reg * face.height - face_info.rect.y;
 		second_bboxes->push_back(face_info);
 	}
 	return 0;
@@ -195,14 +208,14 @@ int Mtcnn::ODetect(const ncnn::Mat & img_in,
 	std::vector<FaceInfo>* third_bboxes) {
 	third_bboxes->clear();
 	for (int i = 0; i < static_cast<int>(second_bboxes.size()); ++i) {
-		Rect face = second_bboxes.at(i).location_ & Rect(0, 0, img_in.w, img_in.h);
+		Rect face = second_bboxes.at(i).rect & Rect(0, 0, img_in.w, img_in.h);
 		ncnn::Mat img_face, img_resized;
 		ncnn::copy_cut_border(img_in, img_face, face.y, img_in.h - face.br().y, face.x, img_in.w - face.br().x);
 		ncnn::resize_bilinear(img_face, img_resized, 48, 48);
 
 		ncnn::Extractor ex = onet_->create_extractor();
 		ex.set_light_mode(true);
-		ex.set_num_threads(2);
+		// ex.set_num_threads(2);
 		ex.input("data", img_resized);
 		ncnn::Mat score_mat, location_mat, keypoints_mat;
 		ex.extract("prob1", score_mat);
@@ -216,13 +229,13 @@ int Mtcnn::ODetect(const ncnn::Mat & img_in,
 		float h_reg = location_mat[3];
 
 		FaceInfo face_info;
-		face_info.score_ = score;
-		face_info.location_.x = face.x + x_reg * face.width;
-		face_info.location_.y = face.y + y_reg * face.height;
-		face_info.location_.width = face.x + face.width +
-			w_reg * face.width - face_info.location_.x;
-		face_info.location_.height = face.y + face.height +
-			h_reg * face.height - face_info.location_.y;
+		face_info.score = score;
+		face_info.rect.x = face.x + x_reg * face.width;
+		face_info.rect.y = face.y + y_reg * face.height;
+		face_info.rect.width = face.x + face.width +
+			w_reg * face.width - face_info.rect.x;
+		face_info.rect.height = face.y + face.height +
+			h_reg * face.height - face_info.rect.y;
 
 		for (int num = 0; num < 5; num++) {
 			face_info.keypoints_[num] = face.x + face.width * keypoints_mat[num];
@@ -238,15 +251,15 @@ int Mtcnn::Refine(std::vector<FaceInfo>* bboxes, const Size max_size) {
 	int num_boxes = static_cast<int>(bboxes->size());
 	for (int i = 0; i < num_boxes; ++i) {
 		FaceInfo face_info = bboxes->at(i);
-		int width = face_info.location_.width;
-		int height = face_info.location_.height;
+		int width = face_info.rect.width;
+		int height = face_info.rect.height;
 		float max_side = fmaxf(width, height);
 
-		face_info.location_.x = face_info.location_.x + 0.5 * width - 0.5 * max_side;
-		face_info.location_.y = face_info.location_.y + 0.5 * height - 0.5 * max_side;
-		face_info.location_.width = max_side;
-		face_info.location_.height = max_side;
-		face_info.location_ = face_info.location_ & Rect(0, 0, max_size.width, max_size.height);
+		face_info.rect.x = face_info.rect.x + 0.5 * width - 0.5 * max_side;
+		face_info.rect.y = face_info.rect.y + 0.5 * height - 0.5 * max_side;
+		face_info.rect.width = max_side;
+		face_info.rect.height = max_side;
+		face_info.rect = face_info.rect & Rect(0, 0, max_size.width, max_size.height);
 		bboxes->at(i) = face_info;
 	}
 	

src/face/detecter/mtcnn/mtcnn.hpp

@@ -11,6 +11,7 @@ public:
 	Mtcnn();
 	~Mtcnn();
 	int LoadModel(const char* root_path);
+    void set_num_threads(int n);
 	int DetectFace(const unsigned char* rgbdata, 
         int img_width, int img_height,
         std::vector<FaceInfo>* faces);

src/face/detecter/retinaface/retinaface.cpp

@@ -5,44 +5,26 @@
 #endif // OV_VULKAN
 
 namespace ovface {
-RetinaFace::RetinaFace() :
-	retina_net_(new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    retina_net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-
-}
-
-RetinaFace::~RetinaFace() {
-	if (retina_net_) {
-		retina_net_->clear();
-	}
-}
 
 int RetinaFace::LoadModel(const char * root_path) {
-	std::string fd_param = std::string(root_path) + "/param";
-	std::string fd_bin = std::string(root_path) + "/bin";
-	if (retina_net_->load_param(fd_param.c_str()) == -1 ||
-		retina_net_->load_model(fd_bin.c_str()) == -1) {
-		return 10000;
-	}
-
+    int ret = Estimator::LoadModel(root_path);
+    if (ret != 0) {
+        return ret;
+    }
 	// generate anchors
 	for (int i = 0; i < 3; ++i) {
 		ANCHORS anchors;
 		if (0 == i) {
-			GenerateAnchors(16, { 1.0f }, { 32, 16 }, &anchors);
+			GenerateAnchors(16, { 1.0f }, { 32, 16 }, &anchors, num_threads);
 		}
 		else if (1 == i) {
-			GenerateAnchors(16, { 1.0f }, { 8, 4 }, &anchors);
+			GenerateAnchors(16, { 1.0f }, { 8, 4 }, &anchors, num_threads);
 		}
 		else {
-			GenerateAnchors(16, { 1.0f }, { 2, 1 }, &anchors);
+			GenerateAnchors(16, { 1.0f }, { 2, 1 }, &anchors, num_threads);
 		}
 		anchors_generated_.push_back(anchors);
 	}
-	initialized_ = true;
 
 	return 0;
 }
@@ -60,7 +42,7 @@ int RetinaFace::DetectFace(const unsigned char* rgbdata,
 
 	float factor_x = static_cast<float>(img_width) / inputSize_.width;
 	float factor_y = static_cast<float>(img_height) / inputSize_.height;
-	ncnn::Extractor ex = retina_net_->create_extractor();
+	ncnn::Extractor ex = net_->create_extractor();
 	ncnn::Mat in = ncnn::Mat::from_pixels_resize(rgbdata,
 		ncnn::Mat::PIXEL_RGB, img_width, img_height, inputSize_.width, inputSize_.height);
 	ex.input("data", in);
@@ -131,8 +113,8 @@ int RetinaFace::DetectFace(const unsigned char* rgbdata,
 						face_info.keypoints_[k + 5] = fminf(fmaxf(y * factor_y, 0.0f), img_height - 1);
 					}
 
-					face_info.score_ = score;
-					face_info.location_ = curr_box;
+					face_info.score = score;
+					face_info.rect = curr_box;
 					faces_tmp.push_back(face_info);
 				}
 			}

src/face/detecter/retinaface/retinaface.hpp

@@ -5,20 +5,16 @@
 #include "net.h"
 
 namespace ovface {
-using ANCHORS = std::vector<Rect>;
+using ANCHORS = std::vector<ov::Rect>;
 class RetinaFace : public Detecter {
 public:
-	RetinaFace();
-	~RetinaFace();
 	int LoadModel(const char* root_path);
 	int DetectFace(const unsigned char* rgbdata,
         int img_width, int img_height,
         std::vector<FaceInfo>* faces);
 
 private:
-	ncnn::Net* retina_net_;
 	std::vector<ANCHORS> anchors_generated_;
-	bool initialized_;
 	const int RPNs_[3] = { 32, 16, 8 };
 	const Size inputSize_ = { 300, 300 };
 	const float iouThreshold_ = 0.4f;

src/face/detecter/scrfd/scrfd.cpp

@@ -0,0 +1,262 @@
+#include "scrfd.hpp"
+
+#ifdef OV_VULKAN
+#include "gpu.h"
+#endif // OV_VULKAN
+
+namespace ovface {
+static void generate_scrfd_proposals(const ncnn::Mat& anchors, int feat_stride, const ncnn::Mat& score_blob, const ncnn::Mat& bbox_blob, const ncnn::Mat& kps_blob, float prob_threshold, std::vector<FaceInfo>& faceobjects)
+{
+    int w = score_blob.w;
+    int h = score_blob.h;
+
+    // generate face proposal from bbox deltas and shifted anchors
+    const int num_anchors = anchors.h;
+
+    for (int q = 0; q < num_anchors; q++)
+    {
+        const float* anchor = anchors.row(q);
+
+        const ncnn::Mat score = score_blob.channel(q);
+        const ncnn::Mat bbox = bbox_blob.channel_range(q * 4, 4);
+
+        // shifted anchor
+        float anchor_y = anchor[1];
+
+        float anchor_w = anchor[2] - anchor[0];
+        float anchor_h = anchor[3] - anchor[1];
+
+        for (int i = 0; i < h; i++)
+        {
+            float anchor_x = anchor[0];
+
+            for (int j = 0; j < w; j++)
+            {
+                int index = i * w + j;
+
+                float prob = score[index];
+
+                if (prob >= prob_threshold)
+                {
+                    // insightface/detection/scrfd/mmdet/models/dense_heads/scrfd_head.py _get_bboxes_single()
+                    float dx = bbox.channel(0)[index] * feat_stride;
+                    float dy = bbox.channel(1)[index] * feat_stride;
+                    float dw = bbox.channel(2)[index] * feat_stride;
+                    float dh = bbox.channel(3)[index] * feat_stride;
+
+                    // insightface/detection/scrfd/mmdet/core/bbox/transforms.py distance2bbox()
+                    float cx = anchor_x + anchor_w * 0.5f;
+                    float cy = anchor_y + anchor_h * 0.5f;
+
+                    float x0 = cx - dx;
+                    float y0 = cy - dy;
+                    float x1 = cx + dw;
+                    float y1 = cy + dh;
+
+                    FaceInfo obj;
+                    obj.rect.x = x0;
+                    obj.rect.y = y0;
+                    obj.rect.width = x1 - x0 + 1;
+                    obj.rect.height = y1 - y0 + 1;
+                    obj.score = prob;
+
+                    if (!kps_blob.empty())
+                    {
+                        const ncnn::Mat kps = kps_blob.channel_range(q * 10, 10);
+
+                        obj.keypoints_[0] = cx + kps.channel(0)[index] * feat_stride;
+                        obj.keypoints_[5] = cy + kps.channel(1)[index] * feat_stride;
+                        obj.keypoints_[1] = cx + kps.channel(2)[index] * feat_stride;
+                        obj.keypoints_[6] = cy + kps.channel(3)[index] * feat_stride;
+                        obj.keypoints_[2] = cx + kps.channel(4)[index] * feat_stride;
+                        obj.keypoints_[7] = cy + kps.channel(5)[index] * feat_stride;
+                        obj.keypoints_[3] = cx + kps.channel(6)[index] * feat_stride;
+                        obj.keypoints_[8] = cy + kps.channel(7)[index] * feat_stride;
+                        obj.keypoints_[4] = cx + kps.channel(8)[index] * feat_stride;
+                        obj.keypoints_[9] = cy + kps.channel(9)[index] * feat_stride;
+                    }
+
+                    faceobjects.push_back(obj);
+                }
+
+                anchor_x += feat_stride;
+            }
+
+            anchor_y += feat_stride;
+        }
+    }
+}
+
+int Scrfd::DetectFace(const unsigned char* rgbdata,
+    int img_width, int img_height, 
+    std::vector<FaceInfo>* faces) {
+    faces->clear();
+	if (!initialized_) {
+		return 10000;
+	}
+	if (rgbdata == 0){
+		return 10001;
+    }
+
+    // pad to multiple of 32
+    int w = img_width;
+    int h = img_height;
+    float scale = 1.f;
+    if (w > h)
+    {
+        scale = (float)target_size / w;
+        w = target_size;
+        h = h * scale;
+    }
+    else
+    {
+        scale = (float)target_size / h;
+        h = target_size;
+        w = w * scale;
+    }
+
+    ncnn::Mat in = ncnn::Mat::from_pixels_resize(rgbdata, ncnn::Mat::PIXEL_RGB, img_width, img_height, w, h);
+
+    // pad to target_size rectangle
+    float wpad = (float)(w + 31) / 32 * 32 - w;
+    float hpad = (float)(h + 31) / 32 * 32 - h;
+    ncnn::Mat in_pad;
+    ncnn::copy_make_border(in, in_pad, hpad / 2, hpad - hpad / 2, wpad / 2, wpad - wpad / 2, ncnn::BORDER_CONSTANT, 0.f);
+
+    const float mean_vals[3] = {127.5f, 127.5f, 127.5f};
+    const float norm_vals[3] = {1/128.f, 1/128.f, 1/128.f};
+    in_pad.substract_mean_normalize(mean_vals, norm_vals);
+
+    ncnn::Extractor ex = net_->create_extractor();
+
+    ex.input("input.1", in_pad);
+
+    std::vector<FaceInfo> faceproposals;
+
+    // stride 8
+    {
+        ncnn::Mat score_blob, bbox_blob, kps_blob;
+        ex.extract("score_8", score_blob);
+        ex.extract("bbox_8", bbox_blob);
+        if (has_kps)
+            ex.extract("kps_8", kps_blob);
+
+        const int base_size = 16;
+        const int feat_stride = 8;
+        ncnn::Mat ratios(1);
+        ratios[0] = 1.f;
+        ncnn::Mat scales(2);
+        scales[0] = 1.f;
+        scales[1] = 2.f;
+        ncnn::Mat anchors = ov::generate_anchors(base_size, ratios, scales);
+
+        std::vector<FaceInfo> faceobjects32;
+        generate_scrfd_proposals(anchors, feat_stride, score_blob, bbox_blob, kps_blob, prob_threshold, faceobjects32);
+
+        faceproposals.insert(faceproposals.end(), faceobjects32.begin(), faceobjects32.end());
+    }
+
+    // stride 16
+    {
+        ncnn::Mat score_blob, bbox_blob, kps_blob;
+        ex.extract("score_16", score_blob);
+        ex.extract("bbox_16", bbox_blob);
+        if (has_kps)
+            ex.extract("kps_16", kps_blob);
+
+        const int base_size = 64;
+        const int feat_stride = 16;
+        ncnn::Mat ratios(1);
+        ratios[0] = 1.f;
+        ncnn::Mat scales(2);
+        scales[0] = 1.f;
+        scales[1] = 2.f;
+        ncnn::Mat anchors = ov::generate_anchors(base_size, ratios, scales);
+
+        std::vector<FaceInfo> faceobjects16;
+        generate_scrfd_proposals(anchors, feat_stride, score_blob, bbox_blob, kps_blob, prob_threshold, faceobjects16);
+
+        faceproposals.insert(faceproposals.end(), faceobjects16.begin(), faceobjects16.end());
+    }
+
+    // stride 32
+    {
+        ncnn::Mat score_blob, bbox_blob, kps_blob;
+        ex.extract("score_32", score_blob);
+        ex.extract("bbox_32", bbox_blob);
+        if (has_kps)
+            ex.extract("kps_32", kps_blob);
+
+        const int base_size = 256;
+        const int feat_stride = 32;
+        ncnn::Mat ratios(1);
+        ratios[0] = 1.f;
+        ncnn::Mat scales(2);
+        scales[0] = 1.f;
+        scales[1] = 2.f;
+        ncnn::Mat anchors = ov::generate_anchors(base_size, ratios, scales);
+
+        std::vector<FaceInfo> faceobjects8;
+        generate_scrfd_proposals(anchors, feat_stride, score_blob, bbox_blob, kps_blob, prob_threshold, faceobjects8);
+
+        faceproposals.insert(faceproposals.end(), faceobjects8.begin(), faceobjects8.end());
+    }
+
+    // sort all proposals by score from highest to lowest
+    qsort_descent_inplace(faceproposals);
+
+    // apply nms with nms_threshold
+    std::vector<int> picked;
+    nms_sorted_bboxes(faceproposals, picked, nms_threshold);
+
+    int face_count = picked.size();
+
+    for (int i = 0; i < face_count; i++)
+    {
+        FaceInfo obj = faceproposals[picked[i]];
+
+        // adjust offset to original unpadded
+        float x0 = (obj.rect.x - (wpad / 2)) / scale;
+        float y0 = (obj.rect.y - (hpad / 2)) / scale;
+        float x1 = (obj.rect.x + obj.rect.width - (wpad / 2)) / scale;
+        float y1 = (obj.rect.y + obj.rect.height - (hpad / 2)) / scale;
+
+        x0 = std::max(std::min(x0, (float)img_width - 1), 0.f);
+        y0 = std::max(std::min(y0, (float)img_height - 1), 0.f);
+        x1 = std::max(std::min(x1, (float)img_width - 1), 0.f);
+        y1 = std::max(std::min(y1, (float)img_height - 1), 0.f);
+
+        obj.rect.x = x0;
+        obj.rect.y = y0;
+        obj.rect.width = x1 - x0;
+        obj.rect.height = y1 - y0;
+
+        if (has_kps)
+        {
+            float x0 = (obj.keypoints_[0] - (wpad / 2)) / scale;
+            float y0 = (obj.keypoints_[5] - (hpad / 2)) / scale;
+            float x1 = (obj.keypoints_[1] - (wpad / 2)) / scale;
+            float y1 = (obj.keypoints_[6] - (hpad / 2)) / scale;
+            float x2 = (obj.keypoints_[2] - (wpad / 2)) / scale;
+            float y2 = (obj.keypoints_[7] - (hpad / 2)) / scale;
+            float x3 = (obj.keypoints_[3] - (wpad / 2)) / scale;
+            float y3 = (obj.keypoints_[8] - (hpad / 2)) / scale;
+            float x4 = (obj.keypoints_[4] - (wpad / 2)) / scale;
+            float y4 = (obj.keypoints_[9] - (hpad / 2)) / scale;
+
+            obj.keypoints_[0] = std::max(std::min(x0, (float)img_width - 1), 0.f);
+            obj.keypoints_[5] = std::max(std::min(y0, (float)img_height - 1), 0.f);
+            obj.keypoints_[1] = std::max(std::min(x1, (float)img_width - 1), 0.f);
+            obj.keypoints_[6] = std::max(std::min(y1, (float)img_height - 1), 0.f);
+            obj.keypoints_[2] = std::max(std::min(x2, (float)img_width - 1), 0.f);
+            obj.keypoints_[7] = std::max(std::min(y2, (float)img_height - 1), 0.f);
+            obj.keypoints_[3] = std::max(std::min(x3, (float)img_width - 1), 0.f);
+            obj.keypoints_[8] = std::max(std::min(y3, (float)img_height - 1), 0.f);
+            obj.keypoints_[4] = std::max(std::min(x4, (float)img_width - 1), 0.f);
+            obj.keypoints_[9] = std::max(std::min(y4, (float)img_height - 1), 0.f);
+        }
+        faces->push_back(obj);
+    }
+    return 0;
+}
+}

src/face/detecter/scrfd/scrfd.hpp

@@ -0,0 +1,26 @@
+#ifndef _SCRFD_DETECT_H_
+#define _SCRFD_DETECT_H_
+
+#include "../detecter.hpp"
+#include "net.h"
+
+namespace ovface {
+class Scrfd : public Detecter {
+public:
+	int DetectFace(const unsigned char* rgbdata,
+        int img_width, int img_height,
+        std::vector<FaceInfo>* faces);
+
+private:
+    const int target_size = 640;
+    const float meanVals[3] = { 123.675f, 116.28f,  103.53f };
+    const float normVals[3] = { 0.01712475f, 0.0175f, 0.01742919f };
+    const float prob_threshold = 0.5f;
+    const float nms_threshold = 0.45f;
+    const bool has_kps = false;
+};
+
+}
+
+#endif // !_RETINAFACE_H_
+

src/face/detecter/yoloface/yoloface.cpp

@@ -92,7 +92,7 @@ static void generate_proposals(const ncnn::Mat& anchors, int stride, const ncnn:
                     obj.rect.width = x1 - x0;
                     obj.rect.height = y1 - y0;
                     obj.label = class_index;
-                    obj.prob = confidence;
+                    obj.score = confidence;
 
 					for (int l = 0; l < 5; l++)
 					{
@@ -107,28 +107,10 @@ static void generate_proposals(const ncnn::Mat& anchors, int stride, const ncnn:
     }
 }
 
-YoloFace::YoloFace() : 
-    net_ (new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-YoloFace::~YoloFace() {
-    net_->clear();
-}
 
 int YoloFace::LoadModel(const char * root_path) {
     register_yolov5focus(net_);
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (net_->load_param(param_file.c_str()) == -1 ||
-		net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
-	initialized_ = true;
-	return 0;
+    return Estimator::LoadModel(root_path);
 }
 
 int YoloFace::DetectFace(const unsigned char* rgbdata,
@@ -274,7 +256,7 @@ int YoloFace::DetectFace(const unsigned char* rgbdata,
         obj.rect.height = y1 - y0;
 
         FaceInfo info;
-        info.location_ = obj.rect;
+        info.rect = obj.rect;
         for (int k = 0; k < 5; ++k) {
             info.keypoints_[k] = obj.pts[k].x;
             info.keypoints_[k + 5] = obj.pts[k].y;

src/face/detecter/yoloface/yoloface.hpp

@@ -7,16 +7,12 @@
 namespace ovface {
 class YoloFace : public Detecter {
 public:
-	YoloFace();
-	~YoloFace();
-	int LoadModel(const char* root_path);
+    int LoadModel(const char * root_path);
 	int DetectFace(const unsigned char* rgbdata,
         int img_width, int img_height,
         std::vector<FaceInfo>* faces);
 
 private:
-	ncnn::Net* net_;
-	bool initialized_;
     const int target_size = 640;
     const float mean_vals[3] = {127.f, 127.f, 127.f};
     const float norm_vals[3] = {1 / 255.f, 1 / 255.f, 1 / 255.f};

src/face/hopenet/hopenet.cpp

@@ -21,34 +21,15 @@ namespace ovface {
 #define NEAR_0 1e-10
 #define ODIM   66
 
-Hopenet::Hopenet():
-    net_(new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-Hopenet::~Hopenet() {
-	if (net_) {
-		net_->clear();
-	}
-}
-
-int Hopenet::LoadModel(const char * root_path) {
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (net_->load_param(param_file.c_str()) == -1 ||
-		net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
+int Hopenet::LoadModel(const char* root_path) {
+    int ret = Estimator::LoadModel(root_path);
+    if (ret != 0) {
+        return ret;
+    }
     for (uint i=1; i<67; i++) idx_tensor[i-1] = i;
-	initialized_ = true;
-
-	return 0;
+    return 0;
 }
 
-
 int Hopenet::Detect(const unsigned char* rgbdata, 
     int img_width, int img_height,
     Rect roi, HeadPose* head_angles) {
@@ -80,15 +61,15 @@ int Hopenet::Detect(const unsigned char* rgbdata,
     float* pred_roll  = output.range(ODIM, ODIM*2);
     float* pred_yaw   = output.range(ODIM*2, ODIM*3);
 
-    softmax(pred_pitch, ODIM);
-    softmax(pred_roll,  ODIM);
-    softmax(pred_yaw,   ODIM);
+    this->softmax(pred_pitch, ODIM);
+    this->softmax(pred_roll,  ODIM);
+    this->softmax(pred_yaw,   ODIM);
 
     // printArray(pred_pitch, ODIM);
 
-    head_angles->pitch = getAngle(pred_pitch, ODIM);
-    head_angles->roll  = getAngle(pred_roll,  ODIM);
-    head_angles->yaw   = getAngle(pred_yaw,   ODIM);
+    head_angles->pitch = this->getAngle(pred_pitch, ODIM);
+    head_angles->roll  = this->getAngle(pred_roll,  ODIM);
+    head_angles->yaw   = this->getAngle(pred_yaw,   ODIM);
 
     free(img_face);
 

src/face/hopenet/hopenet.hpp

@@ -7,16 +7,12 @@
 namespace ovface {
 class Hopenet : public ov::Estimator {
 public:
-    Hopenet();
-    ~Hopenet();
-	int LoadModel(const char* root_path);
+    int LoadModel(const char* root_path);
     int Detect(const unsigned char* rgbdata, 
         int img_width, int img_height,
         Rect roi, HeadPose* euler_angles);
 
 private:
-    ncnn::Net* net_;
-    bool initialized_;
     float idx_tensor[66];
     void softmax(float* z, size_t el);
     double getAngle(float* prediction, size_t len);

src/face/landmarker.h

@@ -10,6 +10,7 @@ extern "C" {
     typedef void* IFaceLandmarker;
     IFaceLandmarker new_insightface();
     IFaceLandmarker new_zq();
+    IFaceLandmarker new_scrfd_landmarker();
     int extract_face_keypoints(IFaceLandmarker m, const unsigned char* rgbdata, int img_width, int img_height, const Rect* face, Point2fVector* keypoints); 
 #ifdef __cplusplus
 }

src/face/landmarker/insightface/insightface.cpp

@@ -6,34 +6,12 @@
 #endif // OV_VULKAN
 
 namespace ovface {
-InsightfaceLandmarker::InsightfaceLandmarker() {
-	insightface_landmarker_net_ = new ncnn::Net();
-	initialized = false;
-#ifdef OV_VULKAN
-    insightface_landmarker_net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-InsightfaceLandmarker::~InsightfaceLandmarker() {
-	insightface_landmarker_net_->clear();
-}
-
-int InsightfaceLandmarker::LoadModel(const char * root_path) {
-	std::string fl_param = std::string(root_path) + "/param";
-	std::string fl_bin = std::string(root_path) + "/bin";
-	if (insightface_landmarker_net_->load_param(fl_param.c_str()) == -1 ||
-		insightface_landmarker_net_->load_model(fl_bin.c_str()) == -1) {
-		return 10000;
-	}
-	initialized = true;
-	return 0;
-}
 
 int InsightfaceLandmarker::ExtractKeypoints(const unsigned char* rgbdata, 
     int img_width, int img_height,
 	const ov::Rect & face, std::vector<ov::Point2f>* keypoints) {
 	keypoints->clear();
-	if (!initialized) {
+	if (!initialized_) {
 		return 10000;
 	}
 
@@ -42,7 +20,7 @@ int InsightfaceLandmarker::ExtractKeypoints(const unsigned char* rgbdata,
 	}
 
 	// 1 enlarge the face rect
-	Rect face_enlarged = face; 
+    ov::Rect face_enlarged = face; 
 	const float enlarge_scale = 1.5f;
 	EnlargeRect(enlarge_scale, &face_enlarged);
 
@@ -61,7 +39,7 @@ int InsightfaceLandmarker::ExtractKeypoints(const unsigned char* rgbdata,
     }
 
 	// 4 do inference
-	ncnn::Extractor ex = insightface_landmarker_net_->create_extractor();
+	ncnn::Extractor ex = net_->create_extractor();
 	ncnn::Mat in = ncnn::Mat::from_pixels_resize(img_face,
 		ncnn::Mat::PIXEL_RGB, face_enlarged.width, face_enlarged.height, 192, 192);
 	ex.input("data", in);

src/face/landmarker/insightface/insightface.hpp

@@ -7,17 +7,10 @@
 namespace ovface {
 class InsightfaceLandmarker : public Landmarker {
 public:
-	InsightfaceLandmarker();
-	~InsightfaceLandmarker();
-
-	int LoadModel(const char* root_path);
 	int ExtractKeypoints(const unsigned char* rgbdata, 
         int img_width, int img_height,
 		const ov::Rect& face, std::vector<ov::Point2f>* keypoints);
 
-private:
-	ncnn::Net* insightface_landmarker_net_;
-	bool initialized;
 };
 
 }

src/face/landmarker/landmarker.cpp

@@ -1,6 +1,7 @@
 #include "../landmarker.h"
 #include "zqlandmarker/zqlandmarker.hpp"
 #include "insightface/insightface.hpp"
+#include "scrfd/scrfd.hpp"
 
 IFaceLandmarker new_zq() {
     return new ovface::ZQLandmarker();
@@ -10,6 +11,10 @@ IFaceLandmarker new_insightface() {
     return new ovface::InsightfaceLandmarker();
 }
 
+IFaceLandmarker new_scrfd_landmarker() {
+    return new ovface::ScrfdLandmarker();
+}
+
 int extract_face_keypoints(
     IFaceLandmarker m, 
     const unsigned char* rgbdata, 
@@ -39,4 +44,8 @@ Landmarker* InsightfaceLandmarkerFactory::CreateLandmarker() {
 	return new InsightfaceLandmarker();
 }
 
+Landmarker* ScrfdLandmarkerFactory::CreateLandmarker() {
+	return new ScrfdLandmarker();
+}
+
 }

src/face/landmarker/landmarker.hpp

@@ -7,7 +7,6 @@ namespace ovface {
 // 抽象类
 class Landmarker: public ov::Estimator {
 public:
-	virtual ~Landmarker() {};
 	virtual int ExtractKeypoints(const unsigned char* rgbdata, 
         int img_width, int img_height,
 		const Rect& face, std::vector<Point2f>* keypoints) = 0;
@@ -35,6 +34,13 @@ public:
 	~InsightfaceLandmarkerFactory() {}
 };
 
+class ScrfdLandmarkerFactory : public LandmarkerFactory {
+public:
+	ScrfdLandmarkerFactory(){}
+	Landmarker* CreateLandmarker();
+	~ScrfdLandmarkerFactory() {}
+};
+
 }
 
 #endif // !_FACE_LANDMARKER_H_

src/face/landmarker/scrfd/scrfd.cpp

@@ -0,0 +1,57 @@
+#include "scrfd.hpp"
+
+#ifdef OV_VULKAN
+#include "gpu.h"
+#endif // OV_VULKAN
+
+namespace ovface {
+
+int ScrfdLandmarker::ExtractKeypoints(const unsigned char* rgbdata, 
+    int img_width, int img_height,
+	const ov::Rect & face, std::vector<ov::Point2f>* keypoints) {
+	keypoints->clear();
+	if (!initialized_) {
+		return 10000;
+	}
+
+	if (rgbdata == 0){
+		return 10001;
+	}
+	// 1 enlarge the face rect
+    ov::Rect box = face; 
+	const float enlarge_scale = 1.5f;
+	EnlargeRect(enlarge_scale, &box);
+
+	// 2 square the rect
+	RectifyRect(&box);
+
+    box = box & Rect(0, 0, img_width, img_height);
+
+    size_t total_size = box.width * box.height * 3 * sizeof(unsigned char);
+    unsigned char* img_face = (unsigned char*)malloc(total_size);
+    const unsigned char *start_ptr = rgbdata;
+    for(size_t i = 0; i < box.height; ++i) {
+        const unsigned char* srcCursor = start_ptr + ((i + box.y) * img_width + box.x) * 3; 
+        unsigned char* dstCursor = img_face + i * box.width * 3;
+        memcpy(dstCursor, srcCursor, sizeof(unsigned char) * 3 * box.width);
+    }
+    
+    ncnn::Extractor ex = net_->create_extractor();
+    ncnn::Mat ncnn_in = ncnn::Mat::from_pixels_resize(img_face, ncnn::Mat::PIXEL_RGB, box.width, box.height, 192, 192);
+    ncnn_in.substract_mean_normalize(means, norms);
+    ex.input("input.1",ncnn_in);
+    ncnn::Mat ncnn_out;
+    ex.extract("482",ncnn_out);
+    float *scoredata = (float*)ncnn_out.data;
+    for(int i = 0; i < 468; i++)
+    {
+        ov::Point2f pt;
+        pt.x = scoredata[i*3]*box.width/192 + box.x;
+        pt.y = scoredata[i*3+1]*box.height/192 + box.y;
+        keypoints->push_back(pt);
+    }
+
+    free(img_face);
+    return 0;
+}
+}

src/face/landmarker/scrfd/scrfd.hpp

@@ -0,0 +1,22 @@
+#ifndef _FACE_SCRFD_LANDMARKER_H_
+#define _FACE_SCRFD_LANDMARKER_H_
+
+#include "../landmarker.hpp"
+#include "net.h"
+
+namespace ovface {
+class ScrfdLandmarker : public Landmarker {
+public:
+	int ExtractKeypoints(const unsigned char* rgbdata, 
+        int img_width, int img_height,
+		const ov::Rect& face, std::vector<ov::Point2f>* keypoints);
+
+private:
+    const float means[3] = { 127.5f, 127.5f,  127.5f };
+    const float norms[3] = { 1/127.5f, 1 / 127.5f, 1 / 127.5f };
+};
+
+}
+
+#endif // !_FACE_SCRFD_ANDMARKER_H_
+

src/face/landmarker/zqlandmarker/zqlandmarker.cpp

@@ -1,39 +1,16 @@
 #include "zqlandmarker.hpp"
-#include <string>
 
 #ifdef OV_VULKAN
 #include "gpu.h"
 #endif // OV_VULKAN
 
 namespace ovface {
-ZQLandmarker::ZQLandmarker() {
-	zq_landmarker_net_ = new ncnn::Net();
-	initialized = false;
-#ifdef OV_VULKAN
-    zq_landmarker_net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-ZQLandmarker::~ZQLandmarker() {
-	zq_landmarker_net_->clear();
-}
-
-int ZQLandmarker::LoadModel(const char * root_path) {
-	std::string fl_param = std::string(root_path) + "/param";
-	std::string fl_bin = std::string(root_path) + "/bin";
-	if (zq_landmarker_net_->load_param(fl_param.c_str()) == -1 ||
-		zq_landmarker_net_->load_model(fl_bin.c_str()) == -1) {
-		return 10000;
-	}
-	initialized = true;
-	return 0;
-}
 
 int ZQLandmarker::ExtractKeypoints(const unsigned char* rgbdata, 
     int img_width, int img_height,
 	const ov::Rect & face, std::vector<ov::Point2f>* keypoints) {
 	keypoints->clear();
-	if (!initialized) {
+	if (!initialized_) {
 		return 10000;
 	}
 
@@ -49,7 +26,7 @@ int ZQLandmarker::ExtractKeypoints(const unsigned char* rgbdata,
         unsigned char* dstCursor = img_face + i * face.width * 3;
         memcpy(dstCursor, srcCursor, sizeof(unsigned char) * 3 * face.width);
     }
-	ncnn::Extractor ex = zq_landmarker_net_->create_extractor();
+	ncnn::Extractor ex = net_->create_extractor();
 	ncnn::Mat in = ncnn::Mat::from_pixels_resize(img_face,
 		ncnn::Mat::PIXEL_RGB, face.width, face.height, 112, 112);
 	in.substract_mean_normalize(meanVals, normVals);

src/face/landmarker/zqlandmarker/zqlandmarker.hpp

@@ -7,19 +7,13 @@
 namespace ovface {
 class ZQLandmarker : public Landmarker {
 public:
-	ZQLandmarker();
-	~ZQLandmarker();
-
-	int LoadModel(const char* root_path);
 	int ExtractKeypoints(const unsigned char* rgbdata, 
         int img_width, int img_height,
 		const ov::Rect& face, std::vector<ov::Point2f>* keypoints);
 
 private:
-	ncnn::Net* zq_landmarker_net_;
 	const float meanVals[3] = { 127.5f, 127.5f, 127.5f };
 	const float normVals[3] = { 0.0078125f, 0.0078125f, 0.0078125f };
-	bool initialized;
 };
 
 }

src/face/recognizer/mobilefacenet/mobilefacenet.cpp

@@ -5,29 +5,6 @@
 #endif // OV_VULKAN
 
 namespace ovface {
-Mobilefacenet::Mobilefacenet() {
-	mobileface_net_ = new ncnn::Net();
-	initialized_ = false;
-#ifdef OV_VULKAN
-    mobileface_net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-Mobilefacenet::~Mobilefacenet() {
-	mobileface_net_->clear();
-}
-
-int Mobilefacenet::LoadModel(const char * root_path) {
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (mobileface_net_->load_param(param_file.c_str()) == -1 ||
-		mobileface_net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
-
-	initialized_ = true;
-	return 0;
-}
 
 int Mobilefacenet::ExtractFeature(const unsigned char* rgbdata, 
     int img_width, int img_height,
@@ -52,7 +29,7 @@ int Mobilefacenet::ExtractFeature(const unsigned char* rgbdata,
 	ncnn::Mat in = ncnn::Mat::from_pixels_resize(img_face,
 		ncnn::Mat::PIXEL_RGB, face.width, face.height, 112, 112);
 	feature->resize(kFaceFeatureDim);
-	ncnn::Extractor ex = mobileface_net_->create_extractor();
+	ncnn::Extractor ex = net_->create_extractor();
 	ex.input("data", in);
 	ncnn::Mat out;
 	ex.extract("fc1", out);

src/face/recognizer/mobilefacenet/mobilefacenet.hpp

@@ -9,18 +9,11 @@ namespace ovface {
 
 class Mobilefacenet : public Recognizer {
 public:
-	Mobilefacenet();
-	~Mobilefacenet();
-
-	int LoadModel(const char* root_path);
 	int ExtractFeature(const unsigned char* rgbdata, 
         int img_width, int img_height,
         const ov::Rect& face,
         std::vector<float>* feature);
 
-private:
-	ncnn::Net* mobileface_net_;
-	bool initialized_;
 };
 
 }

src/face/recognizer/recognizer.hpp

@@ -7,7 +7,6 @@
 namespace ovface {
 class Recognizer: public ov::Estimator {
 public:
-	virtual ~Recognizer() {};
 	virtual int ExtractFeature(const unsigned char* rgbdata, 
         int img_width, int img_height,
         const ov::Rect& face,

src/face/tracker/tracker.cpp

@@ -45,8 +45,8 @@ int Tracker::Track(const std::vector<FaceInfo>& curr_faces, std::vector<TrackedF
     for (int i = 0; i < num_faces; ++i) {
         auto& face = curr_faces.at(i);
         for (auto scored_tracked_face : scored_tracked_faces) {
-            ComputeIOU(scored_tracked_face.face_info_.location_,
-                face.location_, &scored_tracked_face.iou_score_);
+            ComputeIOU(scored_tracked_face.face_info_.rect,
+                face.rect, &scored_tracked_face.iou_score_);
         }
         if (scored_tracked_faces.size() > 0) {
             std::partial_sort(scored_tracked_faces.begin(),
@@ -61,10 +61,10 @@ int Tracker::Track(const std::vector<FaceInfo>& curr_faces, std::vector<TrackedF
 			scored_tracked_faces.pop_front();
 			TrackedFaceInfo &tracked_face = matched_face;
 			if (matched_face.iou_score_ < maxScore_) {
-				tracked_face.face_info_.location_.x = (tracked_face.face_info_.location_.x + face.location_.x) / 2;
-				tracked_face.face_info_.location_.y = (tracked_face.face_info_.location_.y + face.location_.y) / 2;
-				tracked_face.face_info_.location_.width = (tracked_face.face_info_.location_.width + face.location_.width) / 2;
-				tracked_face.face_info_.location_.height = (tracked_face.face_info_.location_.height + face.location_.height) / 2;
+				tracked_face.face_info_.rect.x = (tracked_face.face_info_.rect.x + face.rect.x) / 2;
+				tracked_face.face_info_.rect.y = (tracked_face.face_info_.rect.y + face.rect.y) / 2;
+				tracked_face.face_info_.rect.width = (tracked_face.face_info_.rect.width + face.rect.width) / 2;
+				tracked_face.face_info_.rect.height = (tracked_face.face_info_.rect.height + face.rect.height) / 2;
 			} else {
 				tracked_face.face_info_ = face;
 			}

src/hand/detecter/detecter.cpp

@@ -23,7 +23,7 @@ int extract_hand_rois(IHandDetecter d, const unsigned char* rgbdata, int img_wid
         ov::ObjectInfo o = detected[i];
         rois->items[i] = ObjectInfo{
             o.rect,
-            o.prob,
+            o.score,
             o.label,
             NULL
         };

src/hand/detecter/detecter.hpp

@@ -5,7 +5,6 @@
 namespace ovhand {
 class Detecter: public ov::Estimator {
 public:
-    virtual ~Detecter() {};
     virtual int Detect(const unsigned char*rgbdata,
         int img_width, int img_height,
         std::vector<ov::ObjectInfo>& rois) = 0;

src/hand/detecter/nanodet/nanodet.cpp

@@ -62,7 +62,7 @@ static void generate_nanodet_proposals(const ncnn::Mat& cls_pred, const ncnn::Ma
                     softmax->load_param(pd);
 
                     ncnn::Option opt;
-                    opt.num_threads = 1;
+                    // opt.num_threads = 1;
                     opt.use_packing_layout = false;
 
                     softmax->create_pipeline(opt);
@@ -101,7 +101,7 @@ static void generate_nanodet_proposals(const ncnn::Mat& cls_pred, const ncnn::Ma
                 obj.rect.width = x1 - x0;
                 obj.rect.height = y1 - y0;
                 obj.label = label;
-                obj.prob = score;
+                obj.score= score;
 
                 objects.push_back(obj);
             }
@@ -109,29 +109,6 @@ static void generate_nanodet_proposals(const ncnn::Mat& cls_pred, const ncnn::Ma
     }
 }
 
-Nanodet::Nanodet() : 
-    net_ (new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-Nanodet::~Nanodet() {
-    net_->clear();
-}
-
-int Nanodet::LoadModel(const char * root_path) {
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (net_->load_param(param_file.c_str()) == -1 ||
-		net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
-	initialized_ = true;
-	return 0;
-}
-
 int Nanodet::Detect(const unsigned char* rgbdata,
     int img_width, int img_height, 
     std::vector<ov::ObjectInfo>& rois) {

src/hand/detecter/nanodet/nanodet.hpp

@@ -9,17 +9,11 @@ namespace ovhand {
 
 class Nanodet : public Detecter {
 public:
-    Nanodet();
-    ~Nanodet();
-
-    int LoadModel(const char* root_path);
     int Detect(const unsigned char* rgbadata,
         int img_width, int img_height,
         std::vector<ov::ObjectInfo>& rois);
 
 private:
-	ncnn::Net* net_;
-    bool initialized_;
     const int target_size = 320;
     const float mean_vals[3] = {103.53f, 116.28f, 123.675f};
     const float norm_vals[3] = {1.f / 57.375f, 1.f / 57.12f, 1.f / 58.395f};

src/hand/detecter/yolox/yolox.cpp

@@ -46,7 +46,7 @@ static void generate_yolox_proposals(std::vector<ov::GridAndStride> grid_strides
                 obj.rect.width = w;
                 obj.rect.height = h;
                 obj.label = class_idx;
-                obj.prob = box_prob;
+                obj.score= box_prob;
 
                 objects.push_back(obj);
             }
@@ -57,28 +57,9 @@ static void generate_yolox_proposals(std::vector<ov::GridAndStride> grid_strides
     } // point anchor loop
 }
 
-Yolox::Yolox() : 
-    net_ (new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-Yolox::~Yolox() {
-    net_->clear();
-}
-
 int Yolox::LoadModel(const char * root_path) {
     register_yolov5focus(net_);
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (net_->load_param(param_file.c_str()) == -1 ||
-		net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
-	initialized_ = true;
-	return 0;
+    return Estimator::LoadModel(root_path);
 }
 
 int Yolox::Detect(const unsigned char* rgbdata,
@@ -116,7 +97,6 @@ int Yolox::Detect(const unsigned char* rgbdata,
     in_pad.substract_mean_normalize(mean_vals, norm_vals);
 
     ncnn::Extractor ex = net_->create_extractor();
-    ex.set_num_threads(4);
     ex.input("input", in_pad);
     ncnn::Mat out;
     ex.extract("output", out);

src/hand/detecter/yolox/yolox.hpp

@@ -9,17 +9,12 @@ namespace ovhand {
 
 class Yolox : public Detecter {
 public:
-    Yolox();
-    ~Yolox();
-
-    int LoadModel(const char* root_path);
+    int LoadModel(const char * root_path);
     int Detect(const unsigned char* rgbadata,
         int img_width, int img_height,
         std::vector<ov::ObjectInfo>& rois);
 
 private:
-	ncnn::Net* net_;
-    bool initialized_;
     const int target_size = 416;
     const float mean_vals[3] = {255.f * 0.485f, 255.f * 0.456, 255.f * 0.406f};
     const float norm_vals[3] = {1 / (255.f * 0.229f), 1 / (255.f * 0.224f), 1 / (255.f * 0.225f)};

src/hand/pose/estimator.hpp

@@ -7,7 +7,6 @@
 namespace ovhand {
 class PoseEstimator: public ov::Estimator {
 public:
-    virtual ~PoseEstimator() {};
     virtual int Detect(const unsigned char*rgbdata,
         int img_width, int img_height,
         const ov::Rect& rect,

src/hand/pose/handpose/handpose.cpp

@@ -6,28 +6,6 @@
 #endif // OV_VULKAN
 
 namespace ovhand {
-HandPose::HandPose() : 
-    net_ (new ncnn::Net()),
-	initialized_(false) {
-#ifdef OV_VULKAN
-    net_->opt.use_vulkan_compute = true;
-#endif // OV_VULKAN
-}
-
-HandPose::~HandPose() {
-    net_->clear();
-}
-
-int HandPose::LoadModel(const char * root_path) {
-	std::string param_file = std::string(root_path) + "/param";
-	std::string bin_file = std::string(root_path) + "/bin";
-	if (net_->load_param(param_file.c_str()) == -1 ||
-		net_->load_model(bin_file.c_str()) == -1) {
-		return 10000;
-	}
-	initialized_ = true;
-	return 0;
-}
 
 int HandPose::Detect(const unsigned char* rgbdata,
     int img_width, int img_height,

src/hand/pose/handpose/handpose.hpp

@@ -9,18 +9,12 @@ namespace ovhand {
 
 class HandPose : public PoseEstimator {
 public:
-    HandPose();
-    ~HandPose();
-
-    int LoadModel(const char* root_path);
     int Detect(const unsigned char* rgbdata,
         int img_width, int img_height,
         const ov::Rect& rect,
         std::vector<ov::Point2f>& keypoints);
 
 private:
-	ncnn::Net* net_;
-    bool initialized_;
     const float meanVals[3] = { 128.0f, 128.0f,  128.0f };
     const float normVals[3] = { 0.00390625f, 0.00390625f, 0.00390625f };
 };

src/pose/detecter/detecter.cpp

@@ -18,7 +18,7 @@ int extract_pose_rois(IPoseDetecter d, const unsigned char* rgbdata, int img_wid
         ov::ObjectInfo o = detected[i];
         rois->items[i] = ObjectInfo{
             o.rect,
-            o.prob,
+            o.score,
             o.label,
             NULL
         };

src/pose/detecter/detecter.hpp

@@ -7,7 +7,6 @@ namespace ovpose {
 
 class Detecter: public ov::Estimator {
 public:
-    virtual ~Detecter(){};
     virtual int ExtractROIs(const unsigned char* rgbadata,
         int img_width, int img_height,
         std::vector<ov::ObjectInfo>* rois) = 0;

src/pose/detecter/ultralight/ultralight.cpp

@@ -55,7 +55,6 @@ int Ultralight::ExtractROIs(const unsigned char* rgbdata,
     in.substract_mean_normalize(mean_vals, norm_vals);
 
     ncnn::Extractor ex = roi_net_->create_extractor();
-    ex.set_num_threads(4);
     ex.input("data", in);
     ncnn::Mat out;
     ex.extract("output", out);
@@ -99,7 +98,7 @@ int Ultralight::ExtractROIs(const unsigned char* rgbdata,
         ov::Rect rect = ov::Rect(x1, y1, x2-x1, y2-y1);
         ov::ObjectInfo roi;
         roi.rect = rect;
-        roi.prob = score;
+        roi.score = score;
         rois->push_back(roi);
     }
     return 0;
@@ -124,7 +123,6 @@ int Ultralight::ExtractKeypoints(const unsigned char* rgbdata,
     in.substract_mean_normalize(meanVals, normVals);
 
     ncnn::Extractor ex = pose_net_->create_extractor();
-    ex.set_num_threads(4);
     ex.input("data", in);
     ncnn::Mat out;
     ex.extract("hybridsequential0_conv7_fwd", out);
@@ -152,7 +150,7 @@ int Ultralight::ExtractKeypoints(const unsigned char* rgbdata,
 
         ov::Keypoint keypoint;
         keypoint.p = ov::Point2f(max_x * w / (float)out.w+rect.x, max_y * h / (float)out.h+rect.y);
-        keypoint.prob = max_prob;
+        keypoint.score = max_prob;
         keypoints->push_back(keypoint);
     }