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yolov11n and yolov11m added to model selection

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roberto-corno-nttdata 2024-12-07 23:00:16 +01:00
parent 2c2dc7b1f0
commit 38261e07e5
15 changed files with 173 additions and 86 deletions
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4
benchmarks/Evaluate-Results.ipynb vendored
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@ -29,8 +29,8 @@
"outputs": [],
"source": [
"alignment = [False, True]\n",
"models = [\"Facenet512\", \"Facenet\", \"VGG-Face\", \"ArcFace\", \"Dlib\", \"GhostFaceNet\", \"SFace\", \"OpenFace\", \"DeepFace\", \"DeepID\"]\n",
"detectors = [\"retinaface\", \"mtcnn\", \"fastmtcnn\", \"dlib\", \"yolov8\", \"yolov11n\", \"yolov11m\", \"yunet\", \"centerface\", \"mediapipe\", \"ssd\", \"opencv\", \"skip\"]\n",
"models = [\"Facenet512\", \"Facenet\", \"VGG-Face\", \"ArcFace\", \"Dlib\", \"GhostFaceNet\", \"SFace\", \"OpenFace\", \"DeepFace\", \"DeepID\", \"yolov8\", \"yolov11n\", \"yolov11s\", \"yolov11m\"]\n",
"detectors = [\"retinaface\", \"mtcnn\", \"fastmtcnn\", \"dlib\", \"yolov8\", \"yolov11n\", \"yolov11s\", \"yolov11m\", \"yunet\", \"centerface\", \"mediapipe\", \"ssd\", \"opencv\", \"skip\"]\n",
"distance_metrics = [\"euclidean\", \"euclidean_l2\", \"cosine\"]"
]
},

16
deepface/DeepFace.py
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@ -56,7 +56,7 @@ def build_model(model_name: str, task: str = "facial_recognition") -> Any:
- VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib,
ArcFace, SFace, GhostFaceNet for face recognition
- Age, Gender, Emotion, Race for facial attributes
- opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n', 'yolov11m', yunet,
- opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n', 'yolov11s','yolov11m', yunet,
fastmtcnn or centerface for face detectors
- Fasnet for spoofing
task (str): facial_recognition, facial_attribute, face_detector, spoofing
@ -96,7 +96,7 @@ def verify(
OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',
@ -187,7 +187,7 @@ def analyze(
Set to False to avoid the exception for low-resolution images (default is True).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',
@ -298,7 +298,7 @@ def find(
Set to False to avoid the exception for low-resolution images (default is True).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
align (boolean): Perform alignment based on the eye positions (default is True).
@ -396,7 +396,7 @@ def represent(
(default is True).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
align (boolean): Perform alignment based on the eye positions (default is True).
@ -462,7 +462,7 @@ def stream(
OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',
@ -517,7 +517,7 @@ def extract_faces(
as a string, numpy array (BGR), or base64 encoded images.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
enforce_detection (boolean): If no face is detected in an image, raise an exception.
@ -601,7 +601,7 @@ def detectFace(
added to resize the image (default is (224, 224)).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
enforce_detection (boolean): If no face is detected in an image, raise an exception.

6
deepface/commons/weight_utils.py
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@ -127,7 +127,7 @@ def download_all_models_in_one_shot() -> None:
MODEL_URL as SSD_MODEL,
WEIGHTS_URL as SSD_WEIGHTS,
)
from deepface.models.face_detection.Yolo import (
from deepface.models.YoloModel import (
WEIGHT_URLS as YOLO_WEIGHTS,
WEIGHT_NAMES as YOLO_WEIGHT_NAMES,
YoloModel
@ -170,6 +170,10 @@ def download_all_models_in_one_shot() -> None:
"filename": YOLO_WEIGHT_NAMES[YoloModel.V11N.value],
"url": YOLO_WEIGHTS[YoloModel.V11N.value],
},
{
"filename": YOLO_WEIGHT_NAMES[YoloModel.V11S.value],
"url": YOLO_WEIGHTS[YoloModel.V11S.value],
},
{
"filename": YOLO_WEIGHT_NAMES[YoloModel.V11M.value],
"url": YOLO_WEIGHTS[YoloModel.V11M.value],

37
deepface/models/YoloClientBase.py Normal file
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@ -0,0 +1,37 @@
# built-in dependencies
from typing import Any
# project dependencies
from deepface.models.YoloModel import YoloModel, WEIGHT_URLS, WEIGHT_NAMES
from deepface.commons import weight_utils
from deepface.commons.logger import Logger
logger = Logger()
class YoloClientBase:
def __init__(self, model: YoloModel):
self.model = self.build_model(model)
def build_model(self, model: YoloModel) -> Any:
"""
Build a yolo detector model
Returns:
model (Any)
"""
# Import the optional Ultralytics YOLO model
try:
from ultralytics import YOLO
except ModuleNotFoundError as e:
raise ImportError(
"Yolo is an optional detector, ensure the library is installed. "
"Please install using 'pip install ultralytics'"
) from e
weight_file = weight_utils.download_weights_if_necessary(
file_name=WEIGHT_NAMES[model.value], source_url=WEIGHT_URLS[model.value]
)
# Return face_detector
return YOLO(weight_file)

21
deepface/models/YoloModel.py Normal file
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@ -0,0 +1,21 @@
from enum import Enum
class YoloModel(Enum):
V8N = 0
V11N = 1
V11S = 2
V11M = 3
# Model's weights paths
WEIGHT_NAMES = ["yolov8n-face.pt",
"yolov11n-face.pt",
"yolov11s-face.pt",
"yolov11m-face.pt"]
# Google Drive URL from repo (https://github.com/derronqi/yolov8-face) ~6MB
WEIGHT_URLS = ["https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb",
"https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11n-face.pt",
"https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11s-face.pt",
"https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11m-face.pt"]

79
deepface/models/face_detection/Yolo.py
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@ -1,61 +1,22 @@
# built-in dependencies
import os
from typing import Any, List
from enum import Enum
from typing import List
# 3rd party dependencies
import numpy as np
# project dependencies
from deepface.models.YoloClientBase import YoloClientBase
from deepface.models.YoloModel import YoloModel
from deepface.models.Detector import Detector, FacialAreaRegion
from deepface.commons import weight_utils
from deepface.commons.logger import Logger
logger = Logger()
# Model's weights paths
WEIGHT_NAMES = ["yolov8n-face.pt",
"yolov11n-face.pt",
"yolov11m-face.pt"]
# Google Drive URL from repo (https://github.com/derronqi/yolov8-face) ~6MB
WEIGHT_URLS = ["https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb",
"https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11n-face.pt",
"https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11m-face.pt"]
class YoloModel(Enum):
V8N = 0
V11N = 1
V11M = 2
class YoloClient(Detector):
class YoloDetectorClient(YoloClientBase, Detector):
def __init__(self, model: YoloModel):
self.model = self.build_model(model)
def build_model(self, model: YoloModel) -> Any:
"""
Build a yolo detector model
Returns:
model (Any)
"""
# Import the optional Ultralytics YOLO model
try:
from ultralytics import YOLO
except ModuleNotFoundError as e:
raise ImportError(
"Yolo is an optional detector, ensure the library is installed. "
"Please install using 'pip install ultralytics'"
) from e
weight_file = weight_utils.download_weights_if_necessary(
file_name=WEIGHT_NAMES[model.value], source_url=WEIGHT_URLS[model.value]
)
# Return face_detector
return YOLO(weight_file)
super().__init__(model)
def detect_faces(self, img: np.ndarray) -> List[FacialAreaRegion]:
"""
@ -80,21 +41,24 @@ class YoloClient(Detector):
# For each face, extract the bounding box, the landmarks and confidence
for result in results:
if result.boxes is None or result.keypoints is None:
if result.boxes is None:
continue
# Extract the bounding box and the confidence
x, y, w, h = result.boxes.xywh.tolist()[0]
confidence = result.boxes.conf.tolist()[0]
# right_eye_conf = result.keypoints.conf[0][0]
# left_eye_conf = result.keypoints.conf[0][1]
right_eye = result.keypoints.xy[0][0].tolist()
left_eye = result.keypoints.xy[0][1].tolist()
right_eye = None
left_eye = None
if result.keypoints is not None:
# right_eye_conf = result.keypoints.conf[0][0]
# left_eye_conf = result.keypoints.conf[0][1]
right_eye = result.keypoints.xy[0][0].tolist()
left_eye = result.keypoints.xy[0][1].tolist()
# eyes are list of float, need to cast them tuple of int
left_eye = tuple(int(i) for i in left_eye)
right_eye = tuple(int(i) for i in right_eye)
# eyes are list of float, need to cast them tuple of int
left_eye = tuple(int(i) for i in left_eye)
right_eye = tuple(int(i) for i in right_eye)
x, y, w, h = int(x - w / 2), int(y - h / 2), int(w), int(h)
facial_area = FacialAreaRegion(
@ -111,16 +75,21 @@ class YoloClient(Detector):
return resp
class YoloClientV8n(YoloClient):
class YoloDetectorClientV8n(YoloDetectorClient):
def __init__(self):
super().__init__(YoloModel.V8N)
class YoloClientV11n(YoloClient):
class YoloDetectorClientV11n(YoloDetectorClient):
def __init__(self):
super().__init__(YoloModel.V11N)
class YoloClientV11m(YoloClient):
class YoloDetectorClientV11s(YoloDetectorClient):
def __init__(self):
super().__init__(YoloModel.V11S)
class YoloDetectorClientV11m(YoloDetectorClient):
def __init__(self):
super().__init__(YoloModel.V11M)

44
deepface/models/facial_recognition/Yolo.py Normal file
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@ -0,0 +1,44 @@
# built-in dependencies
from typing import List
# 3rd party dependencies
import numpy as np
# project dependencies
from deepface.models.YoloClientBase import YoloClientBase
from deepface.models.YoloModel import YoloModel
from deepface.models.FacialRecognition import FacialRecognition
from deepface.commons.logger import Logger
logger = Logger()
class YoloFacialRecognitionClient(YoloClientBase, FacialRecognition):
def __init__(self, model: YoloModel):
super().__init__(model)
self.model_name = "Yolo"
self.input_shape = None
self.output_shape = 512
def forward(self, img: np.ndarray) -> List[float]:
return self.model.embed(img)[0].tolist()
class YoloFacialRecognitionClientV8n(YoloFacialRecognitionClient):
def __init__(self):
super().__init__(YoloModel.V8N)
class YoloFacialRecognitionClientV11n(YoloFacialRecognitionClient):
def __init__(self):
super().__init__(YoloModel.V11N)
class YoloFacialRecognitionClientV11s(YoloFacialRecognitionClient):
def __init__(self):
super().__init__(YoloModel.V11S)
class YoloFacialRecognitionClientV11m(YoloFacialRecognitionClient):
def __init__(self):
super().__init__(YoloModel.V11M)

2
deepface/modules/demography.py
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@ -35,7 +35,7 @@ def analyze(
Set to False to avoid the exception for low-resolution images (default is True).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',

2
deepface/modules/detection.py
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@ -38,7 +38,7 @@ def extract_faces(
as a string, numpy array (BGR), or base64 encoded images.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv)
enforce_detection (boolean): If no face is detected in an image, raise an exception.

16
deepface/modules/modeling.py
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@ -12,6 +12,7 @@ from deepface.models.facial_recognition import (
Dlib,
Facenet,
GhostFaceNet,
Yolo as YoloFacialRecognition,
)
from deepface.models.face_detection import (
FastMtCnn,
@ -21,7 +22,7 @@ from deepface.models.face_detection import (
Dlib as DlibDetector,
RetinaFace,
Ssd,
Yolo,
Yolo as YoloFaceDetector,
YuNet,
CenterFace,
)
@ -38,7 +39,7 @@ def build_model(task: str, model_name: str) -> Any:
- VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib,
ArcFace, SFace, GhostFaceNet for face recognition
- Age, Gender, Emotion, Race for facial attributes
- opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n', 'yolov11m', yunet,
- opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n', 'yolov11s', 'yolov11m', yunet,
fastmtcnn or centerface for face detectors
- Fasnet for spoofing
Returns:
@ -60,6 +61,10 @@ def build_model(task: str, model_name: str) -> Any:
"ArcFace": ArcFace.ArcFaceClient,
"SFace": SFace.SFaceClient,
"GhostFaceNet": GhostFaceNet.GhostFaceNetClient,
"yolov8": YoloFacialRecognition.YoloFacialRecognitionClientV8n,
"yolov11n": YoloFacialRecognition.YoloFacialRecognitionClientV11n,
"yolov11s": YoloFacialRecognition.YoloFacialRecognitionClientV11s,
"yolov11m": YoloFacialRecognition.YoloFacialRecognitionClientV11m
},
"spoofing": {
"Fasnet": FasNet.Fasnet,
@ -77,9 +82,10 @@ def build_model(task: str, model_name: str) -> Any:
"dlib": DlibDetector.DlibClient,
"retinaface": RetinaFace.RetinaFaceClient,
"mediapipe": MediaPipe.MediaPipeClient,
"yolov8": Yolo.YoloClientV8n,
"yolov11n": Yolo.YoloClientV11n,
"yolov11m": Yolo.YoloClientV11m,
"yolov8": YoloFaceDetector.YoloDetectorClientV8n,
"yolov11n": YoloFaceDetector.YoloDetectorClientV11n,
"yolov11s": YoloFaceDetector.YoloDetectorClientV11s,
"yolov11m": YoloFaceDetector.YoloDetectorClientV11m,
"yunet": YuNet.YuNetClient,
"fastmtcnn": FastMtCnn.FastMtCnnClient,
"centerface": CenterFace.CenterFaceClient,

4
deepface/modules/recognition.py
View File

@ -54,7 +54,7 @@ def find(
Default is True. Set to False to avoid the exception for low-resolution images.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8','yolov11n','yolov11m', 'centerface' or 'skip'.
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8','yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'.
align (boolean): Perform alignment based on the eye positions.
@ -483,7 +483,7 @@ def find_batched(
Default is True. Set to False to avoid the exception for low-resolution images.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'.
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'.
align (boolean): Perform alignment based on the eye positions.

13
deepface/modules/representation.py
View File

@ -36,7 +36,7 @@ def represent(
Default is True. Set to False to avoid the exception for low-resolution images.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'.
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'.
align (boolean): Perform alignment based on the eye positions.
@ -122,11 +122,12 @@ def represent(
confidence = img_obj["confidence"]
# resize to expected shape of ml model
img = preprocessing.resize_image(
img=img,
# thanks to DeepId (!)
target_size=(target_size[1], target_size[0]),
)
if target_size is not None:
img = preprocessing.resize_image(
img=img,
# thanks to DeepId (!)
target_size=(target_size[1], target_size[0]),
)
# custom normalization
img = preprocessing.normalize_input(img=img, normalization=normalization)

8
deepface/modules/streaming.py
View File

@ -45,7 +45,7 @@ def analysis(
OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',
@ -192,7 +192,7 @@ def search_identity(
model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512,
OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',
'euclidean', 'euclidean_l2' (default is cosine).
@ -374,7 +374,7 @@ def grab_facial_areas(
Args:
img (np.ndarray): image itself
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
threshold (int): threshold for facial area, discard smaller ones
Returns
@ -443,7 +443,7 @@ def perform_facial_recognition(
db_path (string): Path to the folder containing image files. All detected faces
in the database will be considered in the decision-making process.
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv).
distance_metric (string): Metric for measuring similarity. Options: 'cosine',
'euclidean', 'euclidean_l2' (default is cosine).

2
deepface/modules/verification.py
View File

@ -47,7 +47,7 @@ def verify(
OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11m', 'centerface' or 'skip'
'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip'
(default is opencv)
distance_metric (string): Metric for measuring similarity. Options: 'cosine',

5
tests/visual-test.py
View File

@ -22,6 +22,10 @@ model_names = [
"ArcFace",
"SFace",
"GhostFaceNet",
"yolov8",
"yolov11n",
"yolov11s",
"yolov11m"
]
detector_backends = [
@ -35,6 +39,7 @@ detector_backends = [
"yunet",
"yolov8",
"yolov11n",
"yolov11s",
"yolov11m",
"centerface",
]