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If the source image contains multiple faces, the result will include information for each detected face. 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). distance_metric (string): Metric for measuring similarity. Options: 'cosine', 'euclidean', 'euclidean_l2'. 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). threshold (float): Specify a threshold to determine whether a pair represents the same person or different individuals. This threshold is used for comparing distances. If left unset, default pre-tuned threshold values will be applied based on the specified model name and distance metric (default is None). normalization (string): Normalize the input image before feeding it to the model. Default is base. Options: base, raw, Facenet, Facenet2018, VGGFace, VGGFace2, ArcFace silent (boolean): Suppress or allow some log messages for a quieter analysis process. Returns: results (List[pd.DataFrame]): A list of pandas dataframes. Each dataframe corresponds to the identity information for an individual detected in the source image. The DataFrame columns include: - 'identity': Identity label of the detected individual. - 'target_x', 'target_y', 'target_w', 'target_h': Bounding box coordinates of the target face in the database. - 'source_x', 'source_y', 'source_w', 'source_h': Bounding box coordinates of the detected face in the source image. - 'threshold': threshold to determine a pair whether same person or different persons - 'distance': Similarity score between the faces based on the specified model and distance metric TzPassed db_path does not exist!ds__z_v2.pkl-identityhash embeddingtarget_xtarget_ytarget_wtarget_hwbNrbrz,-th item does not have some required keys - z.Consider to delete r#)pathzNo item found in Fr$z Even though z) represented before, it's replaced later.zFound z newly added image(s), z removed image(s), z replaced image(s).) employeesr target_sizerrrrrzThere are now z representations in zfind function duration z secondsz Searching z in z length datastorerr.r grayscalerrrface facial_areaskiprrrrrrr%xsource_xysource_ywsource_whsource_hinfz;Source and target embeddings must have same dimensions but :z. 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Options: VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). target_size (tuple): expected input shape of facial recognition model detector_backend (str): face detector model name enforce_detection (bool): set this to False if you want to proceed when you cannot detect any face align (bool): enable or disable alignment of image before feeding to facial recognition model expand_percentage (int): expand detected facial area with a percentage (default is 0). normalization (bool): normalization technique silent (bool): enable or disable informative logging Returns: representations (list): pivot list of dict with image name, hash, embedding and detected face area's coordinates zFinding representations)descdisableFr/z&Exception while extracting faces from z: Nrr"r1r2r3r4r%r5r7r9r;) rr rXr rarGrYerrorrrVr[r rb)r-rr.rrrrrrrnemployee file_hashimg_objserrimg_obj img_content img_region embedding_objimg_representations rr]r]1sjPO &: "33H=   ..!'!1"3"3H x=A   " " (%!% ! ! ! ! $ %fo $]3 . 8 8()&7%+"/ ! &31%5k%B"&&$, )%7$.sO$.sO$.sO$.sO  G:x U  LLA(2cRUhZX YH sC  D&C??D) VGG-FacecosineTopencvTrNbaseF)r)rrTTrrF)$rErOtypingrrrrrrDnumpynppandasr^rdeepface.commons.loggerr deepface.commonsr deepface.modulesr r r r!deepface.models.FacialRecognitionrrYrndarrayboolintrer_rrWtupler]rrrs 33 +*NN? 8 9 !#"$!%HCO$H HH H  H  H HHHH H ",,HVS &!#$"eCyeee e  e  eee e $ucz er