>|h3{ddlZddlZddlmZmZmZddlZddlZ ddl Z ddl m Z ddl mZddlmZedZdej$d <d Zd Z d3d efd ZdedefdZdej2d ededededeeeeej2ff dZdeddfdZdej2deeeeeefdej2fdZdej2deeeeeefdededej2f dZdeej2de dedeej2fdZ! d4dej2ded eeefd!edeeeeeeff d"Z"dej2deeeeeefdeej2fd#Z#dej2d$eej2deeeeeefd ededededej2fd%Z$dedej2deeeeeefd$eej2dej2f d&Z%dej2d'ej2d(ed)ed*ed+ed,edej2fd-Z&dej2d.e'd)ed*ed+ed,edej2fd/Z(dej2d0e d1ed)ed*ed+ed,edej2fd2Z)y)5N)ListTupleOptional)DeepFace)FacialRecognition)Loggerzcommons.realtime)module2TF_CPP_MIN_LOG_LEVELprrdb_pathc 8t|t|}ttjgd||||} d} d} d} t j } t j|} |j\}}|snr|j}g}| durt||| }t|| }t|| }t|||| }t|r| d znd} | dkDxr| |zdk(} | rt|| }t|||| }t!|||||||}|j} t j } t"j%dnK| durGt j | z |kDr-d} d} t j } t"j%dt'| | |} t j(d| |n| t j*d dzt-dk(rn|j/t j0y)a Run real time face recognition and facial attribute analysis Args: 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). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8' (default is opencv). distance_metric (string): Metric for measuring similarity. Options: 'cosine', 'euclidean', 'euclidean_l2' (default is cosine). enable_face_analysis (bool): Flag to enable face analysis (default is True). source (Any): The source for the video stream (default is 0, which represents the default camera). time_threshold (int): The time threshold (in seconds) for face recognition (default is 5). frame_threshold (int): The frame threshold for face recognition (default is 5). Returns: None enable_face_analysis model_name)r detected_facerdetector_backenddistance_metricrNFrT)imgr target_size)rfaces_coordinates)rrframe_thresholdnum_frames_with_faces)rrrdetected_faces)rrr!rrrrfreezedzfreeze released)rtictime_thresholdrrq)build_demography_modelsbuild_facial_recognition_modelsearch_identitynpzerostimecv2 VideoCapturereadcopygrab_facial_areasextract_facial_areashighlight_facial_areascountdown_to_freezelenperform_demography_analysisperform_facial_recognitionloggerinfocountdown_to_releaseimshowwaitKeyordreleasedestroyAllWindows)rrrrrsourcer$rr_ freezed_imgfreezerr#cap has_framerraw_imgrr!s Y/var/www/html/test/engine/venv/lib/python3.12/site-packages/deepface/modules/streaming.pyanalysisrGsL1EF0JGKhh}-)'  AK F ))+C  6 "C  3 ((* U? 1*: !  2cM^_N(SDUVC%"3 /&; CBEEVAW$9A$=]^ !*Q._3H?3Z^_3_F,L]^2)=&7#1 1&7#1#%5$3)"hhj iik I& t^ c 1N BFK))+C KK) **{Tbc  5!4#+F ;;q>D CH , O TKKMrreturncvtj|}tj|d|jS)aN Build facial recognition model Args: model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). Returns input_shape (tuple): input shape of given facial recognitio n model. rz is built)r build_modelr7r8 input_shape)rmodels rFr'r's3 (33zJE KK:,i()   rHrrrc hd} tj|||||dd}t |dk(ry |d}|jddk(ry |jd} | d }tjd |tj|ttf|dd } t | d k(r| d} | d} | dz} | dddddddf} ntj|} |jdd| fS#t$r9}d|t|vrtj d|dg}n|Yd}~ d}~wwxYw)a Search an identity in facial database. Args: detected_face (np.ndarray): extracted individual facial image 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). detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8' (default is opencv). distance_metric (string): Metric for measuring similarity. Options: 'cosine', 'euclidean', 'euclidean_l2' (default is cosine). Returns: result (tuple): result consisting of following objects identified image path (str) identified image itself (np.ndarray) NFT)img_pathrrrrenforce_detectionsilentzNo item found in zNo item is found in z6.So, no facial recognition analysis will be performed.r)NNidentityzHello, )rOrrrPalignr facer/)rfind ValueErrorstrr7warnr4shapeilocr8 extract_facesIDENTIFIED_IMG_SIZEr,imreadsplit) rrrrr target_pathdfserrdf candidate target_objs target_obj target_imgs rFr(r(so0Kmm"!-+# $ 3x1} QB xx{a IJ'K KK'+'((((*=>) K ;1 ^ ' c 1dd + ZZ ,   S !" %z 11W  wi (CH 4 KK&wi0HH CI  sC// D18.D,,D1rc|durytjdtjdtjdtjdtjdtjd y) z Build demography analysis models Args: enable_face_analysis (bool): Flag to enable face analysis (default is True). Returns: None FNAgerzAge model is just builtGenderzGender model is just builtEmotionzEmotion model is just built)rrKr7r8rs rFr&r&s`u$ E* KK)* H- KK,- I. KK-.rHrrcd|D]*\}}}}tj|||f||z||zfdd,|S)a Highlight detected faces with rectangles in the given image Args: img (np.ndarray): image itself faces_coordinates (list): list of face coordinates as tuple with x, y, w and h Returns: img (np.ndarray): image with highlighted facial areas Croror )r, rectangle)rrxywhs rFr2r2sH(D 1a cAq6AE1q5><CD JrHrrc |D]_\}}}}tj|t|||zz t||dz zt||dz zftjddda|S)a Highlight time to freeze in the image's facial areas Args: img (np.ndarray): image itself faces_coordinates (list): list of face coordinates as tuple with x, y, w and h frame_threshold (int): how many sequantial frames required with face(s) to freeze num_frames_with_faces (int): how many sequantial frames do we have with face(s) Returns: img (np.ndarray): image with counter values ?r )r,putTextrYintFONT_HERSHEY_SIMPLEX)rrrrrqrrrsrts rFr3r3!sw (  1a  #8?#JK L QU^SQW- .  $ $      JrHr#r$c ||Stj}t|||z z dz}tj|ddddtj|t |dtj ddd|S)a: Highlight time to release the freezing in the image top left area Args: img (np.ndarray): image itself tic (float): time specifying when freezing started time_threshold (int): freeze time threshold Returns: img (np.ndarray): image with time to release the freezing r ) r})Z2rni)(rr )r+rzr,rpryrYr{)rr#r$toc time_lefts rFr9r9>sw { ))+CNcCi0145IMM#x<=KK  I      JrHr thresholdc tj|||d}|Dcgc]+}|dd|kDr|dd|dd|dd|ddf-}}|Scc}w#gcYSxYw)a Find facial area coordinates in the given image Args: img (np.ndarray): image itself detector_backend (string): face detector backend. Options: 'opencv', 'retinaface', 'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8' (default is opencv). target_size (tuple): input shape of the facial recognition model. threshold (int): threshold for facial area, discard smaller ones Returns result (list): list of tuple with x, y, w and h coordinates r)rOrrexpand_percentage facial_arearsrqrrrt)rr])rrrr face_objsface_objfacess rFr0r0\s**-#  &   &s+i7 ',',',',          sA0AAAAcg}|D]M\}}}}|t|t||zt|t||zf}|j|O|S)a0 Extract facial areas as numpy array from given image Args: img (np.ndarray): image itself faces_coordinates (list): list of facial area coordinates as tuple with x, y, w and h values Returns: detected_faces (list): list of detected facial area images )rzappend)rrr!rqrrrsrtrs rFr1r1sgN'- 1aCFSQZ/Q#a!e*1DDE m,- rHr!c t|D]7\}\}} } } ||} t| ||||\} }| &t||| || | | }9|S)a  Perform facial recognition Args: img (np.ndarray): image itself detected_faces (list): list of extracted detected face images as numpy faces_coordinates (list): list of facial area coordinates as tuple with x, y, w and h values 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' (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, OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face). Returns: img (np.ndarray): image with identified face informations r)rrhlabelrqrrrsrt) enumerater(overlay_identified_face)rr!rrrrridxrqrrrsrtr target_labelrhs rFr6r6s6''89 \aAq&s+ #2'-+! $  j   %!  , JrHc |dur|St|D]l\}\}}}}||} tj| dddd} t| dk(r9| d} t || d||||}t || d | d dd |||| }n|S) a Perform demography analysis on given image Args: enable_face_analysis (bool): Flag to enable face analysis. img (np.ndarray): image itself faces_coordinates (list): list of face coordinates as tuple with x, y, w and h values detected_faces (list): list of extracted detected face images as numpy Returns: img (np.ndarray): image with analyzed demography information F)agegenderemotionskipT)rOactionsrrPrQrr)remotion_probasrqrrrsrtrdominant_genderr )r apparent_agerrqrrrsrt)rranalyzer4overlay_emotionoverlay_age_gender) rrrr!rrqrrrsrtr demographies demographys rFr5r5s"u$ &'89 \aAq&s+ ''"0##   |  ! "!_ #j6KqTUYZ^_` #E*/015 # 4 JrHrhrrqrrrsrtc  |tz dkDr||ztz|jdkri|||tz |||z||ztzf<|j}d}tj|||z|f||ztz|dzfdtj tj |||d|z d|tj||||z|dzftjdtdtj||t|dz z|f|d t|d z zz|ttdz z fd dtj||d t|d z zz|ttdz z f||z|ttdz z fd d|S||ztz|jdkr|tz dkDr||||z||ztz|tz |f<|j}d}tj||tz ||zdz f|||zfdtj tj |||d|z d|tj|||tz ||zdz ftjdtdtj||t|dz z||zf|t|dz zt|d z z ||zttdz zfd dtj||t|dz zt|d z z ||zttdz zf|||zttdz zfd d|S|tz dkDr|tz dkDrv|||tz ||tz |f<|j}d}tj||tz |f||dzfdtj tj |||d|z d|tj|||tz |dzftjdtdtj||t|dz z|f|t|dz zt|d z z |ttdz z fd dtj||t|dz zt|d z z |ttdz z f||ttdz z fd d|S||ztz|jdkr||ztz|jdkr||||z||ztz||z||ztzf<|j}d}tj|||z||zdz f||ztz||zfdtj tj |||d|z d|tj||||z||zdz ftjdtdtj||t|dz z||zf|t|dz zt|d z z||zttdz zfd dtj||t|dz zt|d z z||zttdz zf||z||zttdz zfd d|Stjd  |S#t$r)} tjt!| Yd } ~ |Sd } ~ wwxYw)a  Overlay the identified face onto image itself Args: img (np.ndarray): image itself target_img (np.ndarray): identified face's image label (str): name of the identified face x (int): x coordinate of the face on the given image y (int): y coordinate of the face on the given image w (int): w coordinate of the face on the given image h (int): h coordinate of the face on the given image Returns: img (np.ndarray): image with overlayed identity rr 皙?.rr}?rxrrvrnz/cannot put facial recognition info on the imageN)r^r[r/r,rpFILLED addWeightedryr{ TEXT_COLORlinerzr7r8 ExceptionerrorrY) rrhrrqrrrsrtoverlayopacityrcs rFrrs,a " "Q &1q53F+FST+U  ''!+AA 3335  hhjGG MMQ Q,,a"f5   OOG    KKQB((  HHSQZ#QQU^#Q-@1-D)E%EF   HHQQU^#Q-@1-D)E%EFQC 3a 7889  l J]U( (399Q< 7A@SRSJ''G9'FRRX\R]J hhjGG 1u""SYYq\1  UAJ U( (!a% 0  JJ   #q7{AsC 1 $  $ $a ( AJ  JJ   #q7{AsC%..0?x"9-*+1-  )C/  L=01 q5& &1 5"f R'77O!eOQ& !$o6,,# URZR519*:!:;A U*B%!)r!11A5$JJ $ $q ("f R'77O"55O!a%' !$o6,,# //"4B%!)r!11 //"4u<B%!)r!11A5$JJ g?B JrHrrc tj|d|t|d|}d}|tz ttdz zdkDrqt j |t|dz z|f|t|dz zt|dz z |ttdz z f|t|dz zt|dz z|ttdz z fg} t j|| gd|d t j||t|dz z|tz ttdz zf||zt|dz z |ttdz z f|t jt j|||t|d z z|ttd z z ft jd d d|S||ztzttdz z |jdkrt j |t|dz z||zf|t|dz zt|dz z ||zttdz zf|t|dz zt|dz z||zttdz zfg} t j|| gd|d t j||t|dz z||zttdz zf||zt|dz z ||ztzttdz z f|t jt j|||t|d z z||zttdz zft jd d d|S)a Overlay the analyzed age and gender of face onto image itself Args: img (np.ndarray): image itself apparent_age (float): analyzed apparent age gender (str): analyzed gender x (int): x coordinate of the face on the given image y (int): y coordinate of the face on the given image w (int): w coordinate of the face on the given image h (int): h coordinate of the face on the given image Returns: img (np.ndarray): image with overlay age and gender analsis results z years old rrrrrxr}rrUg @g@r )rorrw) r7debugrzr^r)arrayr, drawContoursrprryr{r[) rrrrqrrrsrtanalysis_reportinfo_box_colortriangle_coordinatess rFrres  LLL>VH56\*+1VH5O#N %81%+B'C CciiPQl R!xxSQZQ'AE NSR[0EC 3a 788 AE NSR[0EC 3a 788     ! "      QU^QUS)+D'EE F  $ $    JrH)zVGG-FaceopencvcosineTrrr))*osr+typingrrrnumpyr)pandasrr,deepfacer!deepface.models.FacialRecognitionrdeepface.commons.loggerrr7environr^rrYrGtupler'ndarrayr(boolr&rzr2r3floatr9r0r1r6r5rdictrrrHrFrs$ (( ?* ) *&) !"   B BJ s u N2::N2 N2N2 N2  N2  8C=(2::. ./ N2b/$/4/$ (,U3S#3E-F(GZZ" E#sC"456  ZZ : "** $);> bjj>\_" "'*"9>sCx"UX" %S#s" #$"J (,U3S#3E-F(G "**&1 1$1E#sC"4561 1  1  11ZZ1h-- -E#sC"456-$ - ZZ -`x x x x x  x  x xZZxvo o%)o.1o69o>AoFIoZZodq q#(q25q:=qBEqJMqRUqZZqrH