通过mediapipe关键点实现手、口、眼识别代码

以下是使用Mediapipe实现手、口、眼识别的Python代码示例：

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_holistic = mp.solutions.holistic

# 初始化模型
hands = mp_hands.Hands()
face_mesh = mp_face_mesh.FaceMesh()
holistic = mp_holistic.Holistic()

cap = cv2.VideoCapture(0)

while True:
    success, image = cap.read()
    if not success:
        continue

    # 将图像从BGR转换为RGB
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    image.flags.writeable = False

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

    # 运行面部关键点检测
    face_results = face_mesh.process(image)
    if face_results.multi_face_landmarks:
        for face_landmarks in face_results.multi_face_landmarks:
            # 绘制面部关键点
            mp_drawing.draw_landmarks(
                image, face_landmarks, mp_face_mesh.FACE_CONNECTIONS)

    # 运行全身关键点检测
    holistic_results = holistic.process(image)
    if holistic_results.pose_landmarks:
        # 绘制身体关键点
        mp_drawing.draw_landmarks(
            image, holistic_results.pose_landmarks, mp_holistic.POSE_CONNECTIONS)
        # 绘制左右眼关键点
        mp_drawing.draw_landmarks(
            image, holistic_results.left_eye_landmarks, mp_holistic.EYE_CONNECTIONS)
        mp_drawing.draw_landmarks(
            image, holistic_results.right_eye_landmarks, mp_holistic.EYE_CONNECTIONS)
        # 绘制嘴巴关键点
        mp_drawing.draw_landmarks(
            image, holistic_results.mouth_landmarks, mp_holistic.MOUTH_CONNECTIONS)

    # 显示图像
    cv2.imshow('MediaPipe', image)
    if cv2.waitKey(5) & 0xFF == 27:
        break

# 释放资源
cap.release()
cv2.destroyAllWindows()

以上代码使用Mediapipe的三个模型进行手、口、眼识别。在程序运行时，摄像头捕获到的图像会经过处理并在图像上绘制出关键点，最终显示在窗口中。