openmv如何与飞控进行通讯，通过openmv识别颜色给飞控一个坐标点，飞控控制无人机飞行

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 3000)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
clock = time.clock()
def draw_hori_line(img, x0, x1, y, color):
    for x in range(x0, x1):
        img.set_pixel(x, y, color)
# 绘制竖直线
def draw_vec_line(img, x, y0, y1, color):
    for y in range(y0, y1):
        img.set_pixel(x, y, color)

while(True):
    clock.tick()
    img = sensor.snapshot().lens_corr(1.8)
    for c in img.find_circles(threshold = 8500, x_margin = 30, y_margin = 30, r_margin = 5,
            r_min = 10, r_max = 11, r_step = 2):
        area = (c.x()-c.r(), c.y()-c.r(), 2*c.r(), 2*c.r())
        #area为识别到的圆的区域，即圆的外接矩形框
        statistics = img.get_statistics(roi=area)#像素颜色统计
        print(statistics)
        #(0,100,0,120,0,120)是红色的阈值，所以当区域内的众数（也就是最多的颜色），范围在这个阈值内，就说明是红色的圆。
        #l_mode()，a_mode()，b_mode()是L通道，A通道，B通道的众数。
        if 19<statistics.l_mode()<53 and -7<statistics.a_mode()<78 and -4<statistics.b_mode()<64:#if the circle is red
            img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))#识别到的红色圆形用红色的圆框出来
        elif 0<statistics.l_mode()<30 and -9<statistics.a_mode()<20 and -34<statistics.b_mode()<17:#if the circle is red
            img.draw_circle(c.x(), c.y(), c.r(), color = (0, 0, 255))#识别到的红色圆形用红色的圆框出来
    print("FPS %f" % clock.fps())

@argl 老哥解决了吗

那请问我该在哪行代码中进行更改找到最小的圆

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
clock = time.clock()
def draw_hori_line(img, x0, x1, y, color):
    for x in range(x0, x1):
        img.set_pixel(x, y, color)
# 绘制竖直线
def draw_vec_line(img, x, y0, y1, color):
    for y in range(y0, y1):
        img.set_pixel(x, y, color)

while(True):
    clock.tick()
    img = sensor.snapshot().lens_corr(1.8)
    for c in img.find_circles(threshold = 3500, x_margin = 10, y_margin = 10, r_margin = 10,
            r_min = 2, r_max = 100, r_step = 2):
        area = (c.x()-c.r(), c.y()-c.r(), 2*c.r(), 2*c.r())
        #area为识别到的圆的区域，即圆的外接矩形框
        statistics = img.get_statistics(roi=area)#像素颜色统计
        print(statistics)
        #(0,100,0,120,0,120)是红色的阈值，所以当区域内的众数（也就是最多的颜色），范围在这个阈值内，就说明是红色的圆。
        #l_mode()，a_mode()，b_mode()是L通道，A通道，B通道的众数。
        if 16<statistics.l_mode()<65 and 6<statistics.a_mode()<108 and -14<statistics.b_mode()<102:#if the circle is red
            img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))#识别到的红色圆形用红色的圆框出来
        elif 0<statistics.l_mode()<35 and -12<statistics.a_mode()<22 and -34<statistics.b_mode()<10:#if the circle is red
            img.draw_circle(c.x(), c.y(), c.r(), color = (0, 0, 255))#识别到的红色圆形用红色的圆框出来
            #将非红色的圆用白色的矩形框出来
    print("FPS %f" % clock.fps())