diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py index 43df4a1..cf2c827 100644 --- a/deepface/DeepFace.py +++ b/deepface/DeepFace.py @@ -54,10 +54,11 @@ def build_model(model_name: str, task: str = "facial_recognition") -> Any: Args: model_name (str): model identifier - VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, - ArcFace, SFace, GhostFaceNet, Yolo-Face for face recognition + ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, Yolov11s and + Yolov11m for face recognition - Age, Gender, Emotion, Race for facial attributes - - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n', 'yolov11s','yolov11m', yunet, - fastmtcnn or centerface for face detectors + - 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 default is facial_recognition @@ -68,18 +69,18 @@ def build_model(model_name: str, task: str = "facial_recognition") -> Any: def verify( - img1_path: Union[str, np.ndarray, List[float]], - img2_path: Union[str, np.ndarray, List[float]], - model_name: str = "VGG-Face", - detector_backend: str = "opencv", - distance_metric: str = "cosine", - enforce_detection: bool = True, - align: bool = True, - expand_percentage: int = 0, - normalization: str = "base", - silent: bool = False, - threshold: Optional[float] = None, - anti_spoofing: bool = False, + img1_path: Union[str, np.ndarray, List[float]], + img2_path: Union[str, np.ndarray, List[float]], + model_name: str = "VGG-Face", + detector_backend: str = "opencv", + distance_metric: str = "cosine", + enforce_detection: bool = True, + align: bool = True, + expand_percentage: int = 0, + normalization: str = "base", + silent: bool = False, + threshold: Optional[float] = None, + anti_spoofing: bool = False, ) -> Dict[str, Any]: """ Verify if an image pair represents the same person or different persons. @@ -93,7 +94,8 @@ def verify( or pre-calculated embeddings. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet and Yolo-Face (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip' @@ -164,14 +166,14 @@ def verify( def analyze( - img_path: Union[str, np.ndarray], - actions: Union[tuple, list] = ("emotion", "age", "gender", "race"), - enforce_detection: bool = True, - detector_backend: str = "opencv", - align: bool = True, - expand_percentage: int = 0, - silent: bool = False, - anti_spoofing: bool = False, + img_path: Union[str, np.ndarray], + actions: Union[tuple, list] = ("emotion", "age", "gender", "race"), + enforce_detection: bool = True, + detector_backend: str = "opencv", + align: bool = True, + expand_percentage: int = 0, + silent: bool = False, + anti_spoofing: bool = False, ) -> List[Dict[str, Any]]: """ Analyze facial attributes such as age, gender, emotion, and race in the provided image. @@ -187,8 +189,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). @@ -263,20 +265,20 @@ def analyze( def find( - img_path: Union[str, np.ndarray], - db_path: str, - model_name: str = "VGG-Face", - distance_metric: str = "cosine", - enforce_detection: bool = True, - detector_backend: str = "opencv", - align: bool = True, - expand_percentage: int = 0, - threshold: Optional[float] = None, - normalization: str = "base", - silent: bool = False, - refresh_database: bool = True, - anti_spoofing: bool = False, - batched: bool = False, + img_path: Union[str, np.ndarray], + db_path: str, + model_name: str = "VGG-Face", + distance_metric: str = "cosine", + enforce_detection: bool = True, + detector_backend: str = "opencv", + align: bool = True, + expand_percentage: int = 0, + threshold: Optional[float] = None, + normalization: str = "base", + silent: bool = False, + refresh_database: bool = True, + anti_spoofing: bool = False, + batched: bool = False, ) -> Union[List[pd.DataFrame], List[List[Dict[str, Any]]]]: """ Identify individuals in a database @@ -289,7 +291,8 @@ def find( in the database will be considered in the decision-making process. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet and Yolo-Face (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). distance_metric (string): Metric for measuring similarity. Options: 'cosine', 'euclidean', 'euclidean_l2' (default is cosine). @@ -298,8 +301,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). @@ -369,15 +372,15 @@ def find( def represent( - img_path: Union[str, np.ndarray], - model_name: str = "VGG-Face", - enforce_detection: bool = True, - detector_backend: str = "opencv", - align: bool = True, - expand_percentage: int = 0, - normalization: str = "base", - anti_spoofing: bool = False, - max_faces: Optional[int] = None, + img_path: Union[str, np.ndarray], + model_name: str = "VGG-Face", + enforce_detection: bool = True, + detector_backend: str = "opencv", + align: bool = True, + expand_percentage: int = 0, + normalization: str = "base", + anti_spoofing: bool = False, + max_faces: Optional[int] = None, ) -> List[Dict[str, Any]]: """ Represent facial images as multi-dimensional vector embeddings. @@ -388,16 +391,16 @@ def represent( include information for each detected face. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet and Yolo-Face - (default is VGG-Face.). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face.). enforce_detection (boolean): If no face is detected in an image, raise an exception. Default is True. 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). @@ -441,15 +444,15 @@ def represent( def stream( - db_path: str = "", - model_name: str = "VGG-Face", - detector_backend: str = "opencv", - distance_metric: str = "cosine", - enable_face_analysis: bool = True, - source: Any = 0, - time_threshold: int = 5, - frame_threshold: int = 5, - anti_spoofing: bool = False, + db_path: str = "", + model_name: str = "VGG-Face", + detector_backend: str = "opencv", + distance_metric: str = "cosine", + enable_face_analysis: bool = True, + source: Any = 0, + time_threshold: int = 5, + frame_threshold: int = 5, + anti_spoofing: bool = False, ) -> None: """ Run real time face recognition and facial attribute analysis @@ -459,11 +462,12 @@ def stream( in the database will be considered in the decision-making process. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet and Yolo-Face (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', - 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). @@ -499,15 +503,15 @@ def stream( def extract_faces( - img_path: Union[str, np.ndarray], - detector_backend: str = "opencv", - enforce_detection: bool = True, - align: bool = True, - expand_percentage: int = 0, - grayscale: bool = False, - color_face: str = "rgb", - normalize_face: bool = True, - anti_spoofing: bool = False, + img_path: Union[str, np.ndarray], + detector_backend: str = "opencv", + enforce_detection: bool = True, + align: bool = True, + expand_percentage: int = 0, + grayscale: bool = False, + color_face: str = "rgb", + normalize_face: bool = True, + anti_spoofing: bool = False, ) -> List[Dict[str, Any]]: """ Extract faces from a given image @@ -517,8 +521,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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. Set to False to avoid the exception for low-resolution images (default is True). @@ -584,11 +588,11 @@ def cli() -> None: def detectFace( - img_path: Union[str, np.ndarray], - target_size: tuple = (224, 224), - detector_backend: str = "opencv", - enforce_detection: bool = True, - align: bool = True, + img_path: Union[str, np.ndarray], + target_size: tuple = (224, 224), + detector_backend: str = "opencv", + enforce_detection: bool = True, + align: bool = True, ) -> Union[np.ndarray, None]: """ Deprecated face detection function. Use extract_faces for same functionality. @@ -601,8 +605,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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. Set to False to avoid the exception for low-resolution images (default is True). diff --git a/deepface/models/face_detection/Yolo.py b/deepface/models/face_detection/Yolo.py index 548e4f7..ee756c5 100644 --- a/deepface/models/face_detection/Yolo.py +++ b/deepface/models/face_detection/Yolo.py @@ -94,6 +94,8 @@ class YoloDetectorClient(Detector): right_eye = None left_eye = None + + # yolo-facev8 is detecting eyes through keypoints, while for v11 keypoints are always None if result.keypoints is not None: # right_eye_conf = result.keypoints.conf[0][0] # left_eye_conf = result.keypoints.conf[0][1] diff --git a/deepface/modules/demography.py b/deepface/modules/demography.py index cc5112e..2258c1e 100644 --- a/deepface/modules/demography.py +++ b/deepface/modules/demography.py @@ -35,8 +35,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). diff --git a/deepface/modules/detection.py b/deepface/modules/detection.py index 4ed9076..eecca85 100644 --- a/deepface/modules/detection.py +++ b/deepface/modules/detection.py @@ -38,8 +38,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv) + '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. Default is True. Set to False to avoid the exception for low-resolution images. diff --git a/deepface/modules/modeling.py b/deepface/modules/modeling.py index fa884ac..57a5e76 100644 --- a/deepface/modules/modeling.py +++ b/deepface/modules/modeling.py @@ -37,7 +37,7 @@ def build_model(task: str, model_name: str) -> Any: task (str): facial_recognition, facial_attribute, face_detector, spoofing model_name (str): model identifier - VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, - ArcFace, SFace, GhostFaceNet for face recognition + ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, Yolov11s and Yolov11m for face recognition - Age, Gender, Emotion, Race for facial attributes - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n', 'yolov11s', 'yolov11m', yunet, fastmtcnn or centerface for face detectors @@ -61,10 +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 + "Yolov8": YoloFacialRecognition.YoloFacialRecognitionClientV8n, + "Yolov11n": YoloFacialRecognition.YoloFacialRecognitionClientV11n, + "Yolov11s": YoloFacialRecognition.YoloFacialRecognitionClientV11s, + "Yolov11m": YoloFacialRecognition.YoloFacialRecognitionClientV11m }, "spoofing": { "Fasnet": FasNet.Fasnet, diff --git a/deepface/modules/recognition.py b/deepface/modules/recognition.py index d254d66..25b3645 100644 --- a/deepface/modules/recognition.py +++ b/deepface/modules/recognition.py @@ -45,7 +45,8 @@ def find( in the database will be considered in the decision-making process. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). distance_metric (string): Metric for measuring similarity. Options: 'cosine', 'euclidean', 'euclidean_l2'. @@ -54,7 +55,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip'. + 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8','yolov11n', 'yolov11s', + 'yolov11m', 'centerface' or 'skip'. align (boolean): Perform alignment based on the eye positions. @@ -359,7 +361,8 @@ def __find_bulk_embeddings( employees (list): list of exact image paths model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). detector_backend (str): face detector model name @@ -474,7 +477,8 @@ def find_batched( (used for anti-spoofing). model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). distance_metric (string): Metric for measuring similarity. Options: 'cosine', 'euclidean', 'euclidean_l2'. @@ -483,7 +487,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip'. + 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', + 'yolov11m', 'centerface' or 'skip'. align (boolean): Perform alignment based on the eye positions. diff --git a/deepface/modules/representation.py b/deepface/modules/representation.py index c1e2a5f..b8fcd29 100644 --- a/deepface/modules/representation.py +++ b/deepface/modules/representation.py @@ -30,7 +30,7 @@ def represent( include information for each detected face. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, Yolov11s and Yolov11m enforce_detection (boolean): If no face is detected in an image, raise an exception. Default is True. Set to False to avoid the exception for low-resolution images. diff --git a/deepface/modules/streaming.py b/deepface/modules/streaming.py index ca51989..21cc6e7 100644 --- a/deepface/modules/streaming.py +++ b/deepface/modules/streaming.py @@ -42,11 +42,12 @@ def analysis( in the database will be considered in the decision-making process. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', - 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). @@ -190,10 +191,11 @@ def search_identity( db_path (string): Path to the folder containing image files. All detected faces in the database will be considered in the decision-making process. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', - 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). Returns: @@ -374,8 +376,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', + 'centerface' or 'skip' (default is opencv). threshold (int): threshold for facial area, discard smaller ones Returns result (list): list of tuple with x, y, w and h coordinates @@ -443,8 +445,8 @@ 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', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv). + '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). model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, diff --git a/deepface/modules/verification.py b/deepface/modules/verification.py index 1c03e5c..83b6f98 100644 --- a/deepface/modules/verification.py +++ b/deepface/modules/verification.py @@ -44,11 +44,12 @@ def verify( or pre-calculated embeddings. model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, - OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). + OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace, GhostFaceNet, Yolov8, Yolov11n, + Yolov11s and Yolov11m (default is VGG-Face). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', - 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m', 'centerface' or 'skip' - (default is opencv) + '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).