mediapipe关键点获取图片中手部、嘴巴、眼睛的截图并显示的代码

以下是使用MediaPipe获取手部、嘴巴、眼睛关键点并显示截图的Python代码：

import cv2
import mediapipe as mp

# 初始化MediaPipe手部、嘴巴、眼睛模型
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
mp_face_mesh = mp.solutions.face_mesh
mp_pose = mp.solutions.pose

# 初始化OpenCV视频捕捉
cap = cv2.VideoCapture(0)

# 循环读取视频帧
while True:
  ret, frame = cap.read()
  if not ret:
    break

  # 将捕捉到的帧RGB颜色空间转换为BGR颜色空间
  image = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

  # 在MediaPipe手部、嘴巴、眼睛模型上处理当前帧
  with mp_hands.Hands(min_detection_confidence=0.5, min_tracking_confidence=0.5) as hands:
    with mp_face_mesh.FaceMesh(min_detection_confidence=0.5, min_tracking_confidence=0.5) as face_mesh:
      with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:

        # 将当前帧BGR颜色空间转换为RGB颜色空间
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

        # 在当前帧中检测手部关键点
        results_hands = hands.process(image)

        # 在当前帧中检测嘴巴关键点
        results_face_mesh = face_mesh.process(image)

        # 在当前帧中检测眼睛关键点
        results_pose = pose.process(image)

        # 将当前帧RGB颜色空间转换为BGR颜色空间
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

        # 绘制手部关键点
        if results_hands.multi_hand_landmarks:
          for hand_landmarks in results_hands.multi_hand_landmarks:
            mp_drawing.draw_landmarks(image, hand_landmarks, mp_hands.HAND_CONNECTIONS)

        # 绘制嘴巴关键点
        if results_face_mesh.multi_face_landmarks:
          for face_landmarks in results_face_mesh.multi_face_landmarks:
            mp_drawing.draw_landmarks(image, face_landmarks, mp_face_mesh.FACEMESH_CONTOURS)

        # 绘制眼睛关键点
        if results_pose.pose_landmarks:
          mp_drawing.draw_landmarks(image, results_pose.pose_landmarks, mp_pose.POSE_CONNECTIONS)

  # 显示当前帧
  cv2.imshow('MediaPipe Hand, Face and Eye Detection', image)

  # 按下q键退出循环
  if cv2.waitKey(1) & 0xFF == ord('q'):
    break

# 停止视频捕捉、释放资源和关闭所有窗口
cap.release()
cv2.destroyAllWindows()

这段代码可以实时显示捕捉到的视频，并在视频中绘制手部、嘴巴、眼睛关键点。你可以根据自己的需要修改和优化代码。