import cv2
import mediapipe as mp
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils
import urllib.request

# download image as class.jpg
url = 'http://apmonitor.com/pds/uploads/Main/students_walking.jpg'
urllib.request.urlretrieve(url, 'class.jpg')
IMAGE_FILES = ['class.jpg']
with mp_face_detection.FaceDetection(
    model_selection=1, min_detection_confidence=0.5) as face_detection:
  for idx, file in enumerate(IMAGE_FILES):
    image = cv2.imread(file)
    # Convert the BGR image to RGB and process it with MediaPipe Face Detection.
    results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

    # Draw face detections of each face.
    if not results.detections:
      continue
    annotated_image = image.copy()
    for detection in results.detections:
      print('Nose tip:')
      print(mp_face_detection.get_key_point(
          detection, mp_face_detection.FaceKeyPoint.NOSE_TIP))
      mp_drawing.draw_detection(annotated_image, detection)
    cv2.imwrite('annotated_image' + str(idx) + '.png', annotated_image)
import cv2
import mediapipe as mp
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils
import urllib.request

# download image as class.jpg
url = 'http://apmonitor.com/pds/uploads/Main/students_walking.jpg'
urllib.request.urlretrieve(url, 'class.jpg')
IMAGE_FILES = ['class.jpg']
with mp_face_detection.FaceDetection(
    model_selection=1, min_detection_confidence=0.5) as face_detection:
  for idx, file in enumerate(IMAGE_FILES):
    image = cv2.imread(file)
    # Convert the BGR image to RGB and process it with MediaPipe Face Detection.
    results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

    # Draw face detections of each face.
    if not results.detections:
      continue
    annotated_image = image.copy()
    for detection in results.detections:
      print('Nose tip:')
      print(mp_face_detection.get_key_point(
          detection, mp_face_detection.FaceKeyPoint.NOSE_TIP))
      mp_drawing.draw_detection(annotated_image, detection)
    cv2.imwrite('annotated_image' + str(idx) + '.png', annotated_image)
# download image as class.jpg # Convert the BGR image to RGB and process it with MediaPipe Face Detection. # Draw face detections of each face.