nao机器人通过opencv走黑线，并识别到绿色方块蹲下抓取后继续巡线的python2代码

以下是一个 Python 2 代码，使用 OpenCV 库和 NAOqi SDK，实现了 NAO 机器人通过摄像头识别黑色线条并跟随它，当识别到绿色方块时停下并蹲下抓取，然后继续跟随黑色线条：

import cv2
from naoqi import ALProxy

# NAOqi SDK连接设置
robotIp = "NAO_IP"
port = 9559
videoClient = ALProxy("ALVideoDevice", robotIp, port)
motion = ALProxy("ALMotion", robotIp, port)

# 摄像头设置
nameId = videoClient.subscribeCamera("python_client", 0, 2, 11, 5)
width = 640
height = 480
fps = 10

# 黑色线条识别和跟随
following = True
while following:
    # 获取图像
    img = videoClient.getImageRemote(nameId)
    img = np.fromstring(img[6], dtype=np.uint8)
    img = img.reshape((height, width, 3))
    
    # 图像处理
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    _, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
    _, contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    
    # 找到最长的轮廓
    maxContour = max(contours, key=cv2.contourArea)
    moments = cv2.moments(maxContour)
    
    # 计算中心点
    if moments['m00'] != 0:
        cx = int(moments['m10'] / moments['m00'])
        cy = int(moments['m01'] / moments['m00'])
        
        # 跟随线条
        if cx > width / 2 + 50:
            motion.post.moveTo(0.1, 0, 0)
        elif cx < width / 2 - 50:
            motion.post.moveTo(-0.1, 0, 0)
        else:
            motion.post.moveTo(0, 0, 0)
    
    # 绿色方块识别和抓取
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    lower_green = np.array([40, 50, 50])
    upper_green = np.array([80, 255, 255])
    mask = cv2.inRange(hsv, lower_green, upper_green)
    _, greenContours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    if len(greenContours) > 0:
        motion.post.stopMove()
        motion.post.goToPosture("Crouch", 1.0)
        motion.post.openHand("RHand")
        motion.post.closeHand("RHand")
        motion.post.goToPosture("StandInit", 1.0)
        following = True

# 摄像头和连接清理
videoClient.unsubscribe(nameId)

这个代码中，我们添加了一个 `following` 标志来控制是否跟随黑色线条。当机器人识别到绿色方块时，它会停下来，蹲下并抓取方块，然后站起来并重新开始跟随黑色线条。