@kidswong999
你的代码还是报错了，再帮我们看一下吧

@kidswong999 在 我想实现openmv识别到矩形后，舵机开始转动，请问这样的代码如何实现？ 中说：

import sensor, image, time

import time
from servo import Servos
from machine import I2C, Pin

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 灰度更快(160x120 max on OpenMV-M7)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

i2c = I2C(sda=Pin('P5'), scl=Pin('P4'))
servo = Servos(i2c, address=0x40, freq=50, min_us=500, max_us=2500, degrees=180)
rects = img.find_rects(threshold = 10000)

while(True):
clock.tick()
img = sensor.snapshot()

# 下面的`threshold`应设置为足够高的值，以滤除在图像中检测到的具有
# 低边缘幅度的噪声矩形。最适用与背景形成鲜明对比的矩形。

rects = img.find_rects(threshold = 10000):
for f in rects:
    img.draw_rectangle(r.rect(), color = (255, 0, 0))
    for p in r.corners(): img.draw_circle(p[0], p[1], 5, color = (0, 255, 0))
    print(r)

if rects:
    servo.position(0, 0)
    time.sleep_ms(500)
    servo.position(0, 180)
    time.sleep_ms(500)


print("FPS %f" % clock.fps())

还是运行不了啊，再帮我们看一下吧

@kidswong999 识别到矩形后，舵机也没有转动，这是全部代码，两个功能分别都可以实现，但合起来无法联动，帮我看一下哪有问题？

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 灰度更快(160x120 max on OpenMV-M7)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

while(True):
    clock.tick()
    img = sensor.snapshot()

    # 下面的`threshold`应设置为足够高的值，以滤除在图像中检测到的具有
    # 低边缘幅度的噪声矩形。最适用与背景形成鲜明对比的矩形。

    for r in img.find_rects(threshold = 10000):
        img.draw_rectangle(r.rect(), color = (255, 0, 0))
        for p in r.corners(): img.draw_circle(p[0], p[1], 5, color = (0, 255, 0))
        print(r)

    print("FPS %f" % clock.fps())

import time
from servo import Servos
from machine import I2C, Pin

i2c = I2C(sda=Pin('P5'), scl=Pin('P4'))
servo = Servos(i2c, address=0x40, freq=50, min_us=500, max_us=2500, degrees=180)
rects = img.find_rects(threshold = 10000)
if rects:

    
    servo.position(0, 0)
    time.sleep_ms(500)
    servo.position(0, 180)
    time.sleep_ms(500)

矩形识别到后会返回几个值，是不是把控制舵机的while true改成while什么就可以？

控制舵机

# Servo Shield Example.
#
# This example demonstrates the servo shield. Please follow these steps:
#
#   1. Connect a servo to any PWM output.
#   2. Connect a 3.7v battery (or 5V source) to VIN and GND.
#   3. Copy pca9685.py and servo.py to OpenMV and reset it.
#   4. Connect and run this script in the IDE.

import time
from servo import Servos
from machine import I2C, Pin

i2c = I2C(sda=Pin('P5'), scl=Pin('P4'))
servo = Servos(i2c, address=0x40, freq=50, min_us=500, max_us=2500, degrees=180)

while True:
    for i in range(0, 8):
        servo.position(i, 0)
    time.sleep_ms(500)
    for i in range(0, 8):
        servo.position(i, 180)
    time.sleep_ms(500)

矩形识别

# Find Rects Example
#
# 这个例子展示了如何使用april标签代码中的四元检测代码在图像中找到矩形。 四元检测算法以非常稳健的方式检测矩形，并且比基于Hough变换的方法好得多。 例如，即使镜头失真导致这些矩形看起来弯曲，它仍然可以检测到矩形。 圆角矩形是没有问题的！
# (但是，这个代码也会检测小半径的圆)...

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565) # 灰度更快(160x120 max on OpenMV-M7)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()

while(True):
    clock.tick()
    img = sensor.snapshot()

    # 下面的`threshold`应设置为足够高的值，以滤除在图像中检测到的具有
    # 低边缘幅度的噪声矩形。最适用与背景形成鲜明对比的矩形。

    for r in img.find_rects(threshold = 10000):
        img.draw_rectangle(r.rect(), color = (255, 0, 0))
        for p in r.corners(): img.draw_circle(p[0], p[1], 5, color = (0, 255, 0))
        print(r)

    print("FPS %f" % clock.fps())

openmv能不能和微信小程序相连接，就是openmv识别出二维码的相应信息后，传到小程序上面