mediapipe手势识别示例代码

以下是一个简单的 Mediapipe 手势识别示例代码，需要安装 Mediapipe 和 OpenCV 库：

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():
        ret, frame = cap.read()
        if not ret:
            print("Ignoring empty camera frame.")
            continue

        frame = cv2.cvtColor(cv2.flip(frame, 1), cv2.COLOR_BGR2RGB)
        frame.flags.writeable = False
        results = hands.process(frame)
        frame.flags.writeable = True
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

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

                # 获取手指关节点坐标
                finger_tips = []
                for landmark in hand_landmarks.landmark:
                    if landmark.visibility < 0 or landmark.presence < 0:
                        continue
                    x, y = int(landmark.x * frame.shape[1]), int(landmark.y * frame.shape[0])
                    if landmark.id in [8, 12, 16, 20]:
                        finger_tips.append((x, y))

                # 检测手势
                if len(finger_tips) == 4:
                    cv2.putText(frame, "OK", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
                elif len(finger_tips) == 0:
                    cv2.putText(frame, "Fist", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
                else:
                    cv2.putText(frame, "Unknown", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

        cv2.imshow('MediaPipe Hands', frame)

        if cv2.waitKey(10) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

这个示例代码可以实时从摄像头读取图像，使用 Mediapipe 进行手部关键点检测，并根据手指关节点坐标判断手势类型。在检测到 OK 手势时，在视频中显示“OK”，在检测到拳头时，在视频中显示“Fist”。