写一下用opencv-python识别石头剪刀布手势的代码

下面是一个使用OpenCV-Python库识别石头剪刀布手势的示例代码：

import cv2
import numpy as np
import math

# 定义区域的颜色上下限
lower = np.array([0, 20, 70], dtype=np.uint8)
upper = np.array([20, 255, 255], dtype=np.uint8)

# 开启摄像头
cap = cv2.VideoCapture(0)

while True:
    # 读取一帧
    ret, frame = cap.read()
    if not ret:
        break

    # 镜像翻转
    frame = cv2.flip(frame, 1)

    # 转换到HSV空间
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # 创建掩膜
    mask = cv2.inRange(hsv, lower, upper)

    # 进行图像形态学操作
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11, 11))
    mask = cv2.erode(mask, kernel, iterations=2)
    mask = cv2.dilate(mask, kernel, iterations=2)

    # 找到轮廓
    contours, _ = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # 如果找到了轮廓
    if len(contours) > 0:
        # 找到最大的轮廓
        contour = max(contours, key=cv2.contourArea)

        # 计算轮廓的外接圆
        ((x, y), radius) = cv2.minEnclosingCircle(contour)

        # 计算轮廓的重心
        M = cv2.moments(contour)
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

        # 绘制重心和外接圆
        cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
        cv2.circle(frame, center, 5, (0, 0, 255), -1)

        # 如果半径大于10
        if radius > 10:
            # 计算手势方向
            rect = cv2.minAreaRect(contour)
            box = cv2.boxPoints(rect)
            box = np.int0(box)
            cv2.drawContours(frame, [box], 0, (0, 255, 0), 2)
            x1, y1 = box[0]
            x2, y2 = box[1]
            angle = math.atan2(y2 - y1, x2 - x1) * 180.0 / math.pi
            if angle < 0:
                angle += 180
            if angle <= 60:
                gesture = "scissors"
            elif angle <= 120:
                gesture = "rock"
            else:
                gesture = "paper"

            # 在屏幕上显示手势
            cv2.putText(frame, gesture, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255), 2)

    # 显示结果
    cv2.imshow("Frame", frame)
    cv2.imshow("Mask", mask)

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

# 释放摄像头
cap.release()

# 关闭所有窗口
cv2.destroyAllWindows()

代码中使用红色的石头剪刀布手势进行演示，可以根据实际情况调整颜色区间。使用此代码时需要安装OpenCV-Python库，可以通过以下命令进行安装：

pip install opencv-python