>|hddlmZmZmZmZddlZddlZddlm Z m Z m Z ddl m Z  ddeeejfdededed ed ed ed eeeeffd Zy))AnyDictListUnionN)modeling detection preprocessing)FacialRecognitionimg_path model_nameenforce_detectiondetector_backendalignexpand_percentage normalizationreturnc Dg}tj|}|j} |dk7r%tj|| d| df|d|||} nt j |\} } t| jdk(r| d} t| jdk(rtj| | } tj| d} | jdkDr?| jtjd z jtj} | dd| jd| jd d dd g} | D][} | d } | d}| d}t j | |} |j#| }i}||d<||d<||d<|j%|]|S)a  Represent facial images as multi-dimensional vector embeddings. Args: img_path (str or np.ndarray): The exact path to the image, a numpy array in BGR format, or a base64 encoded image. If the source image contains multiple faces, the result will 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 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. detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8'. align (boolean): Perform alignment based on the eye positions. expand_percentage (int): expand detected facial area with a percentage (default is 0). normalization (string): Normalize the input image before feeding it to the model. Default is base. Options: base, raw, Facenet, Facenet2018, VGGFace, VGGFace2, ArcFace Returns: results (List[Dict[str, Any]]): A list of dictionaries, each containing the following fields: - embedding (List[float]): Multidimensional vector representing facial features. The number of dimensions varies based on the reference model (e.g., FaceNet returns 128 dimensions, VGG-Face returns 4096 dimensions). - facial_area (dict): Detected facial area by face detection in dictionary format. Contains 'x' and 'y' as the left-corner point, and 'w' and 'h' as the width and height. If `detector_backend` is set to 'skip', it represents the full image area and is nonsensical. - face_confidence (float): Confidence score of face detection. If `detector_backend` is set to 'skip', the confidence will be 0 and is nonsensical. skiprF)r target_sizer grayscaler rr)axisgo@)xywh)face facial_area confidencer r!r")imgr embeddingface_confidence)r build_model input_shaper extract_facesr load_imagelenshapecv2resizenp expand_dimsmaxastypefloat32normalize_inputfind_embeddingsappend)r r r rrrr resp_objsmodelrimg_objsr#_img_objregionr"r$resp_objs ^/var/www/html/test/engine/venv/lib/python3.12/site-packages/deepface/modules/representation.py representr> s^I'33J?E##K6!**$QQ8-// ))(3Q syy>Q a&C syy>Q **S+.C..1-Cwwy1}zz"**-5==bjjI %&QSYYq\ RS U   #fo'\* ++=Q))#.  )"(&0"#" # )zVGG-FaceTopencvTrbase)typingrrrrnumpyr.r,deepface.modulesrrr !deepface.models.FacialRecognitionr strndarrayboolintr>r?r=rKs)) @?? !"$fCO$fff f  f  ff $sCx.fr?