AttributeError: 'cv2.VideoCapture' object has no attribute 'get_frame'

Question

Traceback (most recent call last): File "c:\Users\user\Desktop\face_recognition\face_recog.py", line 103, in <module> frame = face_recog.get_frame() File "c:\Users\user\Desktop\face_recognition\face_recog.py", line 41, in get_frame frame = self.capture.get_frame(self) AttributeError: 'cv2.VideoCapture' object has no attribute 'get_frame'def get_frame(self): # Grab a single frame of video frame = self.capture.get_frame()

    # Resize frame of video to 1/4 size for faster face recognition processing
    small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)

    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
    rgb_small_frame = small_frame[:, :, ::-1]

    # Only process every other frame of video to save time
    if self.process_this_frame:
        # Find all the faces and face encodings in the current frame of video
        self.face_locations = face_recognition.face_locations(rgb_small_frame)
        self.face_encodings = face_recognition.face_encodings(rgb_small_frame, self.face_locations)

        self.face_names = []
        for face_encoding in self.face_encodings:
            # See if the face is a match for the known face(s)
            distances = face_recognition.face_distance(self.known_face_encodings, face_encoding)
            min_value = min(distances)

            # tolerance: How much distance between faces to consider it a match. Lower is more strict.
            # 0.6 is typical best performance.
            name = "Unknown"
            if min_value < 0.6:
                index = np.argmin(distances)
                name = self.known_face_names[index]

            self.face_names.append(name)

    self.process_this_frame = not self.process_this_frame

    # Display the results
    for (top, right, bottom, left), name in zip(self.face_locations, self.face_names):
        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
        top *= 4
        right *= 4
        bottom *= 4
        left *= 4

        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # Draw a label with a name below the face
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    return frame

def get_jpg_bytes(self):
    frame = self.get_frame()
    # We are using Motion JPEG, but OpenCV defaults to capture raw images,
    # so we must encode it into JPEG in order to correctly display the
    # video stream.
    ret, jpg = cv2.imencode('.jpg', frame)
    return jpg.tobytes()

    # show the frame
    cv2.imshow("Frame", frame)
    key = cv2.waitKey(1) & 0xFF

    # if the `q` key was pressed, break from the loop
    if key == ord("q"):
        break

# do a bit of cleanup
cv2.destroyAllWindows()
print('finish')