钾ie"dZddlZddlZddlZddlZddlZddlmZddl m Z ddl m Z ddl mZddlmZej"eZGd d Zy) zW Face recognition service using DeepFace (ArcFace) and pgvector for similarity search. N)DeepFace) ContentFile)CosineDistance) FaceRecord)FacePreprocessorceZdZdZdZdej defdZ dde de de fd Z dd e de fd Zdefd Zd edefdZy)FaceRecognitionServicez{ Provides face registration and identification using ArcFace embeddings and pgvector cosine similarity search. c"t|_yN)r preprocessor)selfs 7/var/www/face-recognition/faces/services/recognition.py__init__zFaceRecognitionService.__init__s ,.preprocessed_facereturnc |dzjtj}d} tjdd5}|j }t j|t j|t jdddtj|ddd}|rt|d k(r td |d d }t|d k7rtjd t|||r6t j"j%|rt!j&|SSS#1swYxYw#|r6t j"j%|rt!j&|wwwxYw#t$rt($r<}tj+dt-|tdt-||d}~wwxYw)a Extract a 512-dimensional ArcFace embedding from a preprocessed face image. Args: preprocessed_face: Preprocessed face as float32 numpy array, shape (160, 160, 3), values in [0, 1]. Returns: List of 512 float values representing the face embedding. Raises: RuntimeError: If DeepFace fails to extract the embedding. N.jpgF)suffixdeleteArcFaceskip)img_path model_namedetector_backendenforce_detectionrz DeepFace returned no embeddings. embeddingiz:Expected 512-dim embedding, got %d-dim. Proceeding anyway.z(DeepFace embedding extraction failed: %sz"Failed to extract face embedding: )astypenpuint8tempfileNamedTemporaryFilenamecv2imwritecvtColor COLOR_RGB2BGRr representlen RuntimeErrorloggerwarningospathexistsunlink Exceptionerrorstr)rr face_uint8 temp_pathtmp_fileresultsres rextract_embeddingz(FaceRecognitionService.extract_embeddings/ +c199"((CJI! )00!% ( IKK! Z1B1BC #,,&(%+&+ #g,!"3&'IJJ#AJ{3 y>S(NNTI ! !:IIi(";9?> !:IIi(";9    LLCSV L4SVH=  sG$E7D:AD.A2D:56E7.D73D:::E44E77G 7GGNr%metadatac|i}|jj|}|j|}t|dr?|j d|j }t |d|d}t||}n|dzjtj} tj| tj} tjd| \} } | s tdt| j!|d}t#|||} | j$j'|j(|d | j't*j-d || j.t1|| S) a% Register a new face: 1. Preprocess image via FacePreprocessor 2. Extract 512-dim ArcFace embedding 3. Save FaceRecord to database Args: name: Name to associate with the face. image_input: Image as file path, PIL Image, numpy array, or file-like. metadata: Optional metadata dict. Returns: The saved FaceRecord instance. Raises: ValueError: If no face is detected. RuntimeError: If embedding extraction fails. readrr%r)r%rz+Failed to encode preprocessed face to JPEG.)r%rr<Fsavez7Registered face for '%s' (id=%d) with %d-dim embedding.)r preprocessr;hasattrseekr>getattrrr r!r"r&r(r)imencoder,tobytesrphotor@r%r-infoidr+)rr% image_inputr< preprocessedr photo_content photo_name photo_filer6face_bgrsuccessbufferrecords r register_facez$FaceRecognitionService.register_face]sR*  H((33K@ **<8  ; '   Q ',,.M fdmDJ$]DJ',44RXX>J||J0A0ABH!ll68 threshold=%.4f)r rAr;robjectscountfloatannotaterorder_byfirstrZroundr-rHr%rI)rrJrTrKquery_embeddingnearestrZrYs r identify_facez$FaceRecognitionService.identify_faces ((33K@ 00>    # # % * !!!%L      ' '' _E ( Xj ! UW  ? !!!%L  ))* y sX~q1J KKU      (jj!(A.   KKY    !!!!(A.  rcxtjjjdddd}t |S)z Return all registered faces with id, name, created_at, metadata. Excludes embeddings for performance. Returns: List of dicts with face record info. rIr% created_atr<)rr\allvalueslist)rrecordss rlist_registered_facesz,FaceRecognitionService.list_registered_facess8$$((*11 &,  G}rface_idcV tjj|}|jr|jj d|j t j d||jy#tj$rt jd|YywxYw)z Delete a registered face by ID. Args: face_id: The ID of the face record to delete. Returns: True if the record was deleted, False if not found. )rIFr?z!Deleted face record id=%d ('%s').Tz)Face record id=%d not found for deletion.) rr\getrGrr-rHr% DoesNotExistr.)rrmrRs r delete_facez"FaceRecognitionService.delete_faces ''++w+7F|| ###/ MMO KK;Wfkk R&&  NNF P sA9A<<)B('B(r )g?)__name__ __module__ __qualname____doc__rr!ndarrayrjr;r5dictrrSr^rerlintboolrqrrr r s} /=2::=$=@8<>>04> >@QEQDQf t 34rr )ruloggingr#r/r&numpyr!deepfacerdjango.core.files.baserpgvector.djangor faces.modelsr preprocessingr getLoggerrrr-r rzrrrsH .*#+   8 $||r