通过mediapipe识别摄像头手部并框选的代码

以下是使用 Mediapipe 框选摄像头手部的示例代码：

import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

cap = cv2.VideoCapture(0)

with mp_hands.Hands(
        min_detection_confidence=0.5,
        min_tracking_confidence=0.5) as hands:
    while cap.isOpened():
        success, image = cap.read()
        if not success:
            print("Ignoring empty camera frame.")
            continue

        image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
        image.flags.writeable = False
        results = hands.process(image)

        image.flags.writeable = True
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

        if results.multi_hand_landmarks:
            for hand_landmarks in results.multi_hand_landmarks:
                mp_drawing.draw_landmarks(
                    image, hand_landmarks, mp_hands.HAND_CONNECTIONS)

        cv2.imshow('MediaPipe Hands', image)
        if cv2.waitKey(5) & 0xFF == 27:
            break

cap.release()
cv2.destroyAllWindows()

这段代码使用了 MediaPipe 的 Hands 模型来检测手部关键点，并使用 OpenCV 在摄像头中框选出手部区域。其中，`min_detection_confidence` 和 `min_tracking_confidence` 分别控制检测和跟踪手部的置信度，可以根据需要进行调整。