# 圆形检测例程
#
# 这个例子展示了如何用Hough变换在图像中找到圆。
# https://en.wikipedia.org/wiki/Circle_Hough_Transform
#
# 请注意，find_circles（）方法将只能找到完全在图像内部的圆。圈子之外的
# 图像/ roi被忽略...

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 灰度更快
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

while(True):
    clock.tick()

    #lens_corr(1.8)畸变矫正
    img = sensor.snapshot().lens_corr(1.8)

    # Circle对象有四个值: x, y, r (半径), 和 magnitude。
    # magnitude是检测圆的强度。越高越好

    # roi 是一个用以复制的矩形的感兴趣区域(x, y, w, h)。如果未指定，
    # ROI 即图像矩形。操作范围仅限于roi区域内的像素。

    # x_stride 是霍夫变换时需要跳过的x像素的数量。若已知圆较大，可增加
    # x_stride 。

    # y_stride 是霍夫变换时需要跳过的y像素的数量。若已知直线较大，可增加
    # y_stride 。

    # threshold 控制从霍夫变换中监测到的圆。只返回大于或等于阈值的圆。
    # 应用程序的阈值正确值取决于图像。注意：一条圆的大小是组成圆所有
    # 索贝尔滤波像素大小的总和。

    # x_margin 控制所检测的圆的合并。 圆像素为 x_margin 、 y_margin 和  
    # r_margin的部分合并。

    # y_margin 控制所检测的圆的合并。 圆像素为 x_margin 、 y_margin 和
    # r_margin 的部分合并。

    # r_margin 控制所检测的圆的合并。 圆像素为 x_margin 、 y_margin 和
    # r_margin 的部分合并。

    # r_min，r_max和r_step控制测试圆的半径。
    # 缩小测试圆半径的数量可以大大提升性能。
    # threshold = 3500比较合适。如果视野中检测到的圆过多，请增大阈值；
    # 相反，如果视野中检测到的圆过少，请减少阈值。
    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):
        img.draw_circle(c.x(), c.y(), c.r(), color = (255, 0, 0))
        圆 =img.find_circles()
        if(圆):
           print("找到了",c)
        else:
           print("五")

import sensor, image, time,pyb
from pyb import UART
import json
from pyb import LED

led1 = pyb.LED(2)
led2 = pyb.LED(3)

red_threshold   =  (20, 59, 39, 127, 125, -73)
#green_threshold = (23, 35, -23, -39, 10, 25)
#blue_threshold  = (36, 12, 22, -41, -52, -11)



G_X=0
G_Y=0
R_X=0
R_Y=0
Y_X=0
Y_Y=0
G_data=0
R_data=0
Y_data = 0
add_data=0
data=0
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.
K=5000#the value should be measured
uart = UART(3, 115200)
uart.init(115200, bits=8, parity=None, stop=1)  #8位数据位，无校验位，1位停止位

def find_max(blobs):
    max_size=0
    for blob in blobs:
        if blob[2]*blob[3] > max_size:
            max_blob=blob
            max_size = blob[2]*blob[3]
    return max_blob

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    blobs = img.find_blobs([red_threshold],x_stride =15,y_stride = 15)

    if len(blobs) == 1:
        # Draw a rect around the blob.
        b = blobs[0]
        img.draw_rectangle(b[0:4]) # rect
        img.draw_cross(b[5], b[6]) # cx, cy
        Lm = (b[2]+b[3])/2
        length = K/Lm

    if blobs:
       max_blob = find_max(blobs)
       #img.draw_cross(max_blob.cx(),max_blob.cy())   #绘制圆外框
       img.draw_rectangle(max_blob.rect())#绘制矩形
       img.draw_cross(max_blob.cx(), max_blob.cy())#绘制十字
       #img.draw_circle(max_blob.cx(),max_blob.cy(),max_blob.cx()-max_blob.x(), color = (168, 11, 133))

       R_X =int(max_blob.cx())
       R_Y =int(max_blob.cy())
       d=int(length)
       data=bytearray([0xb3,0xb3,R_X,R_Y,d,1,0x5b])
       uart.write(data)    #打印XY轴的偏移坐标
       print("RX轴偏移坐标 : ",R_X)
       print("RY轴偏移坐标 : ",R_Y)
       print("距离坐标：",d)

       #led1.on()
       #led2.on()

    else:
       print("NO FIND")
       data=bytearray([0xb3,0xb3,0,0,0,0x5b])
       uart.write(data)    #打印XY轴的偏移坐标
       #led1.off()
       #led2.off()

这是我更改阈值之前的代码，即使找不到需要的颜色也只是会输出no find，

但是只要更改一下阈值

import sensor, image, time,pyb
from pyb import UART
import json
from pyb import LED

led1 = pyb.LED(2)
led2 = pyb.LED(3)

red_threshold   =  (39, 6, -56, -10, 41, 10)
#green_threshold = (23, 35, -23, -39, 10, 25)
#blue_threshold  = (36, 12, 22, -41, -52, -11)



G_X=0
G_Y=0
R_X=0
R_Y=0
Y_X=0
Y_Y=0
G_data=0
R_data=0
Y_data = 0
add_data=0
data=0
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.
K=5000#the value should be measured
uart = UART(3, 115200)
uart.init(115200, bits=8, parity=None, stop=1)  #8位数据位，无校验位，1位停止位

def find_max(blobs):
    max_size=0
    for blob in blobs:
        if blob[2]*blob[3] > max_size:
            max_blob=blob
            max_size = blob[2]*blob[3]
    return max_blob

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.
    blobs = img.find_blobs([red_threshold],x_stride =15,y_stride = 15)

    if len(blobs) == 1:
        # Draw a rect around the blob.
        b = blobs[0]
        img.draw_rectangle(b[0:4]) # rect
        img.draw_cross(b[5], b[6]) # cx, cy
        Lm = (b[2]+b[3])/2
        length = K/Lm

    if blobs:
       max_blob = find_max(blobs)
       #img.draw_cross(max_blob.cx(),max_blob.cy())   #绘制圆外框
       img.draw_rectangle(max_blob.rect())#绘制矩形
       img.draw_cross(max_blob.cx(), max_blob.cy())#绘制十字
       #img.draw_circle(max_blob.cx(),max_blob.cy(),max_blob.cx()-max_blob.x(), color = (168, 11, 133))

       R_X =int(max_blob.cx())
       R_Y =int(max_blob.cy())
       d=int(length)
       data=bytearray([0xb3,0xb3,R_X,R_Y,d,1,0x5b])
       uart.write(data)    #打印XY轴的偏移坐标
       print("RX轴偏移坐标 : ",R_X)
       print("RY轴偏移坐标 : ",R_Y)
       print("距离坐标：",d)

       #led1.on()
       #led2.on()

    else:
       print("NO FIND")
       data=bytearray([0xb3,0xb3,0,0,0,0x5b])
       uart.write(data)    #打印XY轴的偏移坐标
       #led1.off()
       #led2.off()

就会出现这个