new_contents: import face_recognition
  import cv2
  
  # This is a demo of blurring faces in video.
  
  # PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
  # OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
  # specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.
  
  # Get a reference to webcam #0 (the default one)
  video_capture = cv2.VideoCapture(0)
  
  # Initialize some variables
  face_locations = []
  
  while True:
      # Grab a single frame of video
      ret, frame = video_capture.read()
  
      # Resize frame of video to 1/4 size for faster face detection processing
      small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
  
      # Find all the faces and face encodings in the current frame of video
      face_locations = face_recognition.face_locations(small_frame, model="cnn")
  
      # Display the results
      for top, right, bottom, left in face_locations:
          # 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
  
          # Extract the region of the image that contains the face
          face_image = frame[top:bottom, left:right]
  
          # Blur the face image
          face_image = cv2.GaussianBlur(face_image, (99, 99), 30)
  
          # Put the blurred face region back into the frame image
          frame[top:bottom, left:right] = face_image
  
      # Display the resulting image
      cv2.imshow('Video', frame)
  
      # Hit 'q' on the keyboard to quit!
      if cv2.waitKey(1) & 0xFF == ord('q'):
          break
  
  # Release handle to the webcam
  video_capture.release()
  cv2.destroyAllWindows()
  
subject: Add an example of automatically blurring faces in images or videos