faceReader.py

import face_recognition
import cv2
import FaceEncode


video_capture = cv2.VideoCapture(0)

##########
FaceEncode.initialize()
known_face_encodings=[]
known_face_names=[]
known_face_encodings=FaceEncode.get_encodings()
known_face_names=FaceEncode.get_face_names()


face_locations = []
face_encodings = []
face_names = []
process_this_frame = True

while True:
    
    ret, frame = video_capture.read()
    small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
    rgb_small_frame = small_frame[:, :, ::-1]
    if process_this_frame:
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)

        face_names = []
        for face_encoding in face_encodings:
            
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Unknown"

            if True in matches:
                first_match_index = matches.index(True)
                name = known_face_names[first_match_index]

            face_names.append(name)

    process_this_frame = not process_this_frame


   
    for (top, right, bottom, left), name in zip(face_locations, face_names):
        
        top *= 4
        right *= 4
        bottom *= 4
        left *= 4

        cv2.rectangle(frame, (left, top), (right, bottom), (255, 255, 255), 2)

        
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (255, 255, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (0, 0, 255), 1)
        #speech_output(name)
    
    cv2.imshow('Face recognition', frame)

    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

video_capture.release()
cv2.destroyAllWindows()