初始化比如设置曝光，只能在一开始初始化吗，不能在程序中再改变吗？比如最开始要曝光，最后有一部分程序要关掉

这几个数据是

什么

@kidswong999 我没让他打印为什么在打印

@kidswong999

可以了把报错的地方一改就行了

THRESHOLD = (8, 40, -18, 0, -3, 19)
import sensor, image, time
from pyb import UART
from pid import PID
import ustruct
rho_pid = PID(p=0.17, i=0)
theta_pid = PID(p=0.001, i=0)
sensor.reset()
sensor.set_vflip(True)
sensor.set_hmirror(True)
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()
uart = UART(3, 115200)
output=0

while(True):
    clock.tick()
    img = sensor.snapshot().binary([THRESHOLD])
    line = img.get_regression([(100,100)], robust = True)
    if (line):
        rho_err = abs(line.rho())-img.width()/2
        if line.theta()>90:
            theta_err = line.theta()-180
        else:
            theta_err = line.theta()
        img.draw_line(line.line(), color = 127)
        print(rho_err,line.magnitude(),rho_err)
        if line.magnitude()>8:
            #if -40<b_err<40 and -30<t_err<30:
            rho_output = rho_pid.get_pid(rho_err,1)
            theta_output = theta_pid.get_pid(theta_err,1)
            output = rho_output+theta_output
        else:
           output=0.0 
    else:
       output=0.0 
       pass
    date=bytearray([0x2C,0x12,int(output),0x00,0x00,0x00,0x5B])
	uart.write(date)

我遇到这个问题，好多方法都是了都不行，重新上电都不行，用官方代码也不行
，

Edge Impulse - OpenMV Object Detection Example

import sensor, image, time, os, tf, math, uos, gc

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.set_windowing((240, 240)) # Set 240x240 window.
sensor.skip_frames(time=2000) # Let the camera adjust.

net = None
labels = None
min_confidence = 0.5

try:
# load the model, alloc the model file on the heap if we have at least 64K free after loading
net = tf.load("trained.tflite", load_to_fb=uos.stat('trained.tflite')[6] > (gc.mem_free() - (64*1024)))
except Exception as e:
raise Exception('Failed to load "trained.tflite", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

try:
labels = [line.rstrip('\n') for line in open("labels.txt")]
except Exception as e:
raise Exception('Failed to load "labels.txt", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

colors = [ # Add more colors if you are detecting more than 7 types of classes at once.
(255, 0, 0),
( 0, 255, 0),
(255, 255, 0),
( 0, 0, 255),
(255, 0, 255),
( 0, 255, 255),
(255, 255, 255),
]

clock = time.clock()
while(True):
clock.tick()

img = sensor.snapshot()

# detect() returns all objects found in the image (splitted out per class already)
# we skip class index 0, as that is the background, and then draw circles of the center
# of our objects

for i, detection_list in enumerate(net.detect(img, thresholds=[(math.ceil(min_confidence * 255), 255)])):
    if (i == 0): continue # background class
    if (len(detection_list) == 0): continue # no detections for this class?

    print("********** %s **********" % labels[i])
    for d in detection_list:
        [x, y, w, h] = d.rect()
        center_x = math.floor(x + (w / 2))
        center_y = math.floor(y + (h / 2))
        print('x %d\ty %d' % (center_x, center_y))
        img.draw_circle((center_x, center_y, 12), color=colors[i], thickness=2)

print(clock.fps(), "fps", end="\n\n")