import cv2
import mediapipe as mp
mp_face_detection = mp.solutions.face_detection
mp_drawing = mp.solutions.drawing_utils
IMAGE_FILES = []
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)
results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
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('/tmp/annotated_image' + str(idx) + '.png', annotated_image)
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.")
continue
image.flags.writeable = False
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
results = face_detection.process(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)
cv2.imshow('MediaPipe Face Detection', cv2.flip(image, 1))
if cv2.waitKey(5) & 0xFF == 27:
break
cap.release()