mediapipe实现手部、嘴巴和眼睛的分割代码

以下是使用MediaPipe实现手部、嘴巴和眼睛分割的示例代码：

import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
mp_face_mesh = mp.solutions.face_mesh
mp_face_detection = mp.solutions.face_detection

# 初始化Hand和Face Mesh模型
hands = mp_hands.Hands()
face_mesh = mp_face_mesh.FaceMesh()
face_detection = mp_face_detection.FaceDetection()

# 打开摄像头
cap = cv2.VideoCapture(0)

while True:
    success, image = cap.read()
    if not success:
        print("Could not read from camera.")
        break

    # 调整图像的大小和颜色空间
    image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
    image.flags.writeable = False

    # 检测手部关键点
    hands_results = hands.process(image)
    if hands_results.multi_hand_landmarks:
        for hand_landmarks in hands_results.multi_hand_landmarks:
            mp_drawing.draw_landmarks(image, hand_landmarks, mp_hands.HAND_CONNECTIONS)

    # 检测面部关键点
    face_mesh_results = face_mesh.process(image)
    if face_mesh_results.multi_face_landmarks:
        for face_landmarks in face_mesh_results.multi_face_landmarks:
            mp_drawing.draw_landmarks(image, face_landmarks, mp_face_mesh.FACE_CONNECTIONS)

    # 检测面部特征点
    face_detection_results = face_detection.process(image)
    if face_detection_results.detections:
        for detection in face_detection_results.detections:
            mp_drawing.draw_detection(image, detection)

    # 显示图像
    cv2.imshow('MediaPipe Hands and Face Mesh', cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
    if cv2.waitKey(5) & 0xFF == 27:
        break

# 释放资源
hands.close()
face_mesh.close()
face_detection.close()
cap.release()
cv2.destroyAllWindows()

这段代码使用了MediaPipe提供的Hands、Face Mesh和Face Detection模型，分别检测手部关键点、面部关键点和面部特征点，并在图像上绘制出检测结果。您可以根据需要修改代码，以实现更多的功能。