NAO机器人采用opencv视觉识别进行自主巡黑线，可以直走与拐弯以及识别到黑色横线停止运动的python2代码

以下是一个简单的Python2代码示例，使用OpenCV库进行黑线跟踪和控制NAO机器人的运动：

import cv2
import numpy as np
from naoqi import ALProxy

# Connect to NAO robot
IP = "NAO_IP"
PORT = 9559
motionProxy = ALProxy("ALMotion", IP, PORT)
postureProxy = ALProxy("ALRobotPosture", IP, PORT)
videoProxy = ALProxy("ALVideoDevice", IP, PORT)

# Set up camera
camera = 0
resolution = 2    # VGA
colorSpace = 11   # RGB
fps = 30
nameId = videoProxy.subscribe("python_GVM", resolution, colorSpace, fps)
print "Subscribed to camera"

# Set up black line tracking
lower_black = np.array([0,0,0])
upper_black = np.array([100,100,100])
kernel = np.ones((5,5),np.uint8)

# Start walking
motionProxy.wakeUp()
postureProxy.goToPosture("StandInit", 0.5)

while True:
    # Get image from camera
    image = videoProxy.getImageRemote(nameId)
    if image is None:
        continue
    image = np.reshape(image[6], (480, 640, 3))
    
    # Convert to grayscale and threshold
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    _, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
    
    # Apply morphology operations
    thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
    thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
    
    # Find contours of black line
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2:]
    if len(contours) > 0:
        # Get bounding box of largest contour
        c = max(contours, key=cv2.contourArea)
        x, y, w, h = cv2.boundingRect(c)
        
        # Draw bounding box
        cv2.rectangle(image, (x,y), (x+w,y+h), (0,255,0), 2)
        
        # Continue moving forward if line is straight
        if w > 200:
            motionProxy.move(0.1, 0, 0)
        # Turn left if line turns left
        elif x < 200:
            motionProxy.move(0.1, 0, 0.5)
        # Turn right if line turns right
        elif x > 440:
            motionProxy.move(0.1, 0, -0.5)
    else:
        # Stop if line is lost
        motionProxy.stop()
    
    # Display image
    cv2.imshow("NAO Camera", image)
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break
    
# Clean up
videoProxy.unsubscribe(nameId)
cv2.destroyAllWindows()

该示例代码将订阅NAO机器人的摄像头，并使用OpenCV库进行图像处理。机器人将跟踪黑色线条并根据线条的位置和方向控制其运动。当机器人识别不到线条时，它将停止运动。请注意，此代码可能需要根据您的具体情况进行修改，例如IP地址和端口号。