text: import cv2
  import mediapipe as mp
  
  
  mp_face_detection = mp.solutions.face_detection
  mp_drawing = mp.solutions.drawing_utils
  
  # For webcam input:
  cap = cv2.VideoCapture(0)
  with mp_face_detection.FaceDetection(
      model_selection=0, min_detection_confidence=0.5) as face_detection:
    while cap.isOpened():
      success, image = cap.read()
      if not success:
        print("Ignoring empty camera frame.")
        # If loading a video, use 'break' instead of 'continue'.
        continue
  
      # To improve performance, optionally mark the image as not writeable to
      # pass by reference.
      image.flags.writeable = False
      image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
      results = face_detection.process(image)
  
      # Draw the face detection annotations on the image.
      image.flags.writeable = True
      image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
      if results.detections:
        for detection in results.detections:
          mp_drawing.draw_detection(image, detection)
      # Flip the image horizontally for a selfie-view display.
      cv2.imshow('MediaPipe Face Detection', cv2.flip(image, 1))
      if cv2.waitKey(5) == 27:
        break
  cap.release()