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@kidswong999 我解决了，就是阈值不对和threshold的值调太大了，谢谢了

@kidswong999

{"l_mean":51, "l_median":54, "l_mode":65, "l_stdev":13, "l_min":9, "l_max":67, "l_lq":42, "l_uq":65, "a_mean":2, "a_median":1, "a_mode":0, "a_stdev":5, "a_min":-8, "a_max":27, "a_lq":0, "a_uq":5, "b_mean":15, "b_median":21, "b_mode":22, "b_stdev":14, "b_min":-33, "b_max":35, "b_lq":15, "b_uq":23}
FPS 30.412698
{"l_mean":53, "l_median":59, "l_mode":65, "l_stdev":14, "l_min":9, "l_max":68, "l_lq":43, "l_uq":65, "a_mean":2, "a_median":1, "a_mode":0, "a_stdev":5, "a_min":-7, "a_max":27, "a_lq":0, "a_uq":4, "b_mean":17, "b_median":22, "b_mode":22, "b_stdev":11, "b_min":-32, "b_max":34, "b_lq":17, "b_uq":23}
FPS 30.413361
FPS 30.413797
FPS 30.414231
{"l_mean":52, "l_median":51, "l_mode":65, "l_stdev":12, "l_min":9, "l_max":86, "l_lq":43, "l_uq":65, "a_mean":2, "a_median":1, "a_mode":0, "a_stdev":4, "a_min":-8, "a_max":25, "a_lq":0, "a_uq":4, "b_mean":14, "b_median":21, "b_mode":22, "b_stdev":15, "b_min":-35, "b_max":34, "b_lq":15, "b_uq":24}
FPS 30.413971
{"l_mean":53, "l_median":55, "l_mode":65, "l_stdev":12, "l_min":22, "l_max":68, "l_lq":44, "l_uq":65, "a_mean":3, "a_median":1, "a_mode":0, "a_stdev":5, "a_min":-8, "a_max":27, "a_lq":0, "a_uq":5, "b_mean":14, "b_median":21, "b_mode":22, "b_stdev":15, "b_min":-35, "b_max":35, "b_lq":15, "b_uq":23}

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()

while(True):
    clock.tick()
    img = sensor.snapshot().lens_corr(1.8)
    for c in img.find_rects(threshold = 10000):
        area = c.rect()
        #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 30<statistics.l_mode()<100 and 15<statistics.a_mode()<127 and 15<statistics.b_mode()<127:#if the circle is red
            img.draw_rectangle(area,color = (255, 0, 0))#识别到的红色圆形用红色的圆框出来
        #elif 30<statistics.l_mode()<100 and -64<statistics.a_mode()<8 and -32<statistics.b_mode()<32:#if the circle is red
        #    img.draw_circle(c.x(), c.y(), c.r(), color = (0, 255, 0))#识别到的红色圆形用红色的圆框出来
        else:
            img.draw_rectangle(area, color = (255, 255, 255))
            #将非红色的圆用白色的矩形框出来
    print("FPS %f" % clock.fps())

@kidswong999 在 怎么在圆形的形状加颜色组合代码里，修改成矩形的呢？ 中说：

find_rects

像素统计那一块该怎么改

我用面包板把舵机的GND分成两条线，一条接电池负极，一条接OpenMV的GND这样没问题吧。舵机我用其他板子实验过是正常的，OpenMV的话昨晚我还成功控制一次，今天就不行了。

@kidswong999 还是不行，我特意换了你们店的舵机，按照视频操作也没反应，反而把共地线拔了舵机在抖动。

@kidswong999 搞定了，重启几次就没事了，多谢了

# Untitled - By: 帅景 - 周三 4月 6 2022
import sensor, image, time,pyb
from pyb import Pin, Timer

red_threshold   = (85, 25, 93, 16, 42, 21)
blue_threshold = (52, 61, -128, 10, -118, -23)
green_threshold = (9, 53, -49, -7, -8, 11)
# 设置绿色的阈值，括号里面的数值分别是L A B 的最大值和最小值（minL, maxL, minA,
# maxA, minB, maxB），LAB的值在图像左侧三个坐标图中选取。如果是灰度图，则只需
# 设置（min, max）两个数字即可。

# 你可能需要调整上面的阈值来跟踪绿色的东西…
# 在Framebuffer中选择一个区域来复制颜色设置。

led1 = pyb.LED(1)#红色
led2 = pyb.LED(2)#绿色
led3 = pyb.LED(3)#蓝色

sensor.reset()                      # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA)   # Set frame size to QVGA (320x240)
sensor.skip_frames(time = 2000)     # Wait for settings take effect.
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)     #关掉白平衡和自动增益
clock = time.clock()                # Create a clock object to track the FPS.
tim = Timer(4, freq=1000) # Frequency in Hz
ch2 = tim.channel(2, Timer.PWM, pin=Pin("P8"), pulse_width_percent=45)

while(True):
    clock.tick() # 追踪两个snapshots()之间经过的毫秒数.
    img = sensor.snapshot() # 拍一张照片并返回图像。

  #  pixels_threshold=30
    blobs = img.find_blobs([red_threshold],pixels_threshold=150)
    #find_blobs(thresholds, invert=False, roi=Auto),thresholds为颜色阈值，
    #是一个元组，需要用括号［ ］括起来。invert=1,反转颜色阈值，invert=False默认
    #不反转。roi设置颜色识别的视野区域，roi是一个元组， roi = (x, y, w, h)，代表
    #从左上顶点(x,y)开始的宽为w高为h的矩形区域，roi不设置的话默认为整个图像视野。
    #这个函数返回一个列表，[0]代表识别到的目标颜色区域左上顶点的x坐标，［1］代表
    #左上顶点y坐标，［2］代表目标区域的宽，［3］代表目标区域的高，［4］代表目标
    #区域像素点的个数，［5］代表目标区域的中心点x坐标，［6］代表目标区域中心点y坐标，
    #［7］代表目标颜色区域的旋转角度（是弧度值，浮点型，列表其他元素是整型），
    #［8］代表与此目标区域交叉的目标个数，［9］代表颜色的编号（它可以用来分辨这个
    #区域是用哪个颜色阈值threshold识别出来的）。
    if blobs:
    #如果找到了目标颜色
        for b in blobs:
        #迭代找到的目标颜色区域
            # Draw a rect around the blob.
            img.draw_rectangle(b[0:4]) # rect
            #用矩形标记出目标颜色区域
            led1.on()
            #time.sleep(300)
    else:
            led1.off()
            #time.sleep(300)
    print(clock.fps())              # Note: OpenMV Cam runs about half as fast when connecte

# Untitled - By: yig - 周五 4月 1 2022
from pyb import Servo
import time

s1 = Servo(1) # P7

while(1):

    s1.angle(45)
    time.sleep(600)
    s1.angle(90)
    time.sleep(600)
    s1.angle(0)
    time.sleep(600)
    s1.angle(-60)
    time.sleep(600)
    s1.angle(-90)
    time.sleep(600)