报错：AttributeError: 'int' object has no attribute 'x'
代码如下
import sensor,image,time,math,pyb,lcd
from image import SEARCH_EX, SEARCH_DS
from pyb import UART,LED
import json
import ustruct
lcd.init()
sensor.reset()
sensor.set_contrast(1)
sensor.set_gainceiling(16)
# Max resolution for template matching with SEARCH_EX is QQVGA
# You can set windowing to reduce the search image.
#sensor.set_windowing(((640-80)//2, (480-60)//2, 80, 60))
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)#QQVGA的分辨率为120*160
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False) # 关闭自动增益
sensor.set_auto_whitebal(False) #关闭白平衡
sensor.set_vflip(True)#垂直方向翻转

templates = ["/1.pgm"]

clock = time.clock()

uart = UART(3,9600)   #定义串口3变量
uart.init(9600, bits=8, parity=None, stop=1) # init with given parameters

def sending_data(cx,cy,cw,ch):
    global uart;
    data = ustruct.pack("<bbhhhhb",      #格式为俩个字符俩个短整型(2字节)
                   0x2C,                      #帧头1
                   0x12,                      #帧头2
                   int(cx), # up sample by 4   #数据1
                   int(cy), # up sample by 4    #数据2
                   int(cw), # up sample by 4    #数据1
                   int(ch), # up sample by 4    #数据2
                   0x5B)
    uart.write(data);   #必须要传入一个字节数组

led = pyb.LED(3)
    # Run template matching
while (True):
    clock.tick()
    img = sensor.snapshot()
    led.on()
    # find_template(template, threshold, [roi, step, search])
    # ROI: The region of interest tuple (x, y, w, h).
    # Step: The loop step used (y+=step, x+=step) use a bigger step to make it faster.
    # Search is either image.SEARCH_EX for exhaustive search or image.SEARCH_DS for diamond search
    #
    # Note1: ROI has to be smaller than the image and bigger than the template.
    # Note2: In diamond search, step and ROI are both ignored.
    for t in templates:
        template = image.Image(t)
        #对每个模板遍历进行模板匹配
        r = img.find_template(template, 0.50, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
    #find_template(template, threshold, [roi, step, search]),threshold中
    #的0.7是相似度阈值,roi是进行匹配的区域（左上顶点为（10，0），长80宽60的矩形），
    #注意roi的大小要比模板图片大，比frambuffer小。
    if r:
            # 如果匹配到了模板，画框、十字并记录中心坐标
       for match in r:
           x = match.x()
           y = match.y()
           w = match.w()
           h = match.h()
           center_x = x + (w // 2)
           center_y = y + (h // 2)
           print(t) #打印模板名字
           FH = bytearray([0x2C,0x12,int(center_x),int(center_y),int(w),int(h),0x5B])
           uart.write(FH)
           print(cx,cy,cw,ch)
           lcd.display(img)
    else:
        FH = bytearray([0x2C,0x12,0,0,0,0,0x5B])
        uart.write(FH)
        img.draw_string(0,0,"no object",color = (120,0,0))
        lcd.display(img)