这个程序是用来跟踪一个移动的树莓皮车使用摄像机。我收到一个错误，上面写着：
未定义“位置x”
但我不确定如何准确地定义它。此外，我没有使用覆盆子pi摄像头，而是使用罗技c270网络摄像头。这会影响代码的工作方式吗？提前谢谢你的帮助！

from picamera.array import PiRGBArray

from picamera import PiCamera

import cv2

import serial

import syslog

import time

import numpy as np

import RPi.GPIO as GPIO

# 定義捕捉的畫面尺寸

width = 320

height = 240

tracking_width = 40

tracking_height = 40

auto_mode = 0

# 如下定義小車前後左右的功能函數

def t_stop():

    GPIO.output(11, False)

    GPIO.output(12, False)

    GPIO.output(15, False)

    GPIO.output(16, False)

def t_up():

    GPIO.output(11, True)

    GPIO.output(12, False)

    GPIO.output(15, True)

    GPIO.output(16, False)

    time.sleep(0.05)

    GPIO.output(11, False)

    GPIO.output(12, False)

    GPIO.output(15, False)

    GPIO.output(16, False)

    time.sleep(0.3)

def t_down():

    GPIO.output(11, False)

    GPIO.output(12, True)

    GPIO.output(15, False)

    GPIO.output(16, True)

def t_left():

    GPIO.output(11, False)

    GPIO.output(12, True)

    GPIO.output(15, True)

    GPIO.output(16, False)

    time.sleep(0.05)

    GPIO.output(11, False)

    GPIO.output(12, False)

    GPIO.output(15, False)

    GPIO.output(16, False)

    time.sleep(0.3)

def t_right():

    GPIO.output(11, True)

    GPIO.output(12, False)

    GPIO.output(15, False)

    GPIO.output(16, True)

    time.sleep(0.05)

    GPIO.output(11, False)

    GPIO.output(12, False)

    GPIO.output(15, False)

    GPIO.output(16, False)

    time.sleep(0.3)

def t_open():

    GPIO.setup(22,GPIO.OUT)

    GPIO.output(22,GPIO.LOW)

def t_close():

    GPIO.setup(22,GPIO.IN)

def check_for_direction(position_x):

    GPIO.setmode(GPIO.BOARD)

    GPIO.setwarnings(False)

    GPIO.setup(11,GPIO.OUT)

    GPIO.setup(12,GPIO.OUT)

    GPIO.setup(15,GPIO.OUT)

    GPIO.setup(16,GPIO.OUT)

    GPIO.setup(38,GPIO.OUT)

if position_x == 0 or position_x == width:

    print( 'out of bound')

    t_stop()

if position_x <= ((width-tracking_width)/2 - tracking_width):

    print ('move right!')

    t_right()

elif position_x >= ((width-tracking_width)/2 + tracking_width):

    print('move left!')

    t_left()

else:

# print 'move front'

    t_up()

# initialize the camera and grab a reference to the raw camera capture

    camera = PiCamera()

camera.resolution = (width, height)

camera.framerate = 32

rawCapture = PiRGBArray(camera, size=(width, height))

rawCapture2 = PiRGBArray(camera, size=(width, height))

# allow the camera to warmup

time.sleep(0.1)

# set the ROI (Region of Interest)

c,r,w,h = (width/2 - tracking_width/2), (height/2 - tracking_height/2), tracking_width, tracking_height

track_window = (c,r,w,h)

# capture single frame of tracking image

camera.capture(rawCapture2, format='bgr')

# create mask and normalized histogram

roi = rawCapture2.array[r:r+h, c:c+w]

hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)

mask = cv2.inRange(hsv_roi, np.array([0,30,32]), np.array([180,255,255]))

roi_hist = cv2.calcHist([hsv_roi], [0], mask, [180], [0,180])

cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)

term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 80, 1)

# capture frames from the camera

for frame in camera.capture_continuous(rawCapture, format='bgr', use_video_port=True):

# grab the raw NumPy array representing the image, then initialize the timestamp

# and occupied/unoccupied text

    image = frame.array

# filtering for tracking algorithm

    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

    dst = cv2.calcBackProject([hsv], [0], roi_hist, [0,180], 1)

    ret, track_window = cv2.meanShift(dst, track_window, term_crit)

    x,y,w,h = track_window

    cv2.rectangle(image, (x,y), (x+w,y+h), 255, 2)

    cv2.putText(image, 'Tracked', (x-25, y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)

# show the frame

    cv2.imshow("Raspberry Pi RC Car", image)

    key = cv2.waitKey(1) & 0xFF

    check_for_direction(x)

    time.sleep(0.01)

# clear the stream in preparation for the next frame

    rawCapture.truncate(0)