4. 代码也不报错，连接openmv运行就会自动终止运行，串行终端提示这个是怎么回事啊？
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    • 代码也不报错，连接openmv运行就会自动终止运行，串行终端提示这个是怎么回事啊？

    • C
       

      import sensor, image, time, os, tf, uos, gc, pyb, machine,math,tf
from pyb import UART
uart = UART(3, 9600)
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((240, 240))
sensor.skip_frames(time=2000)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)

net = None
labels = None

ROI = (20,20,200,200)

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:
    print(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) + ')')

clock = time.clock()

def compare():
	img1 = sensor.snapshot()
	img1.draw_rectangle(ROI)
	statistics = img1.get_statistics(roi = ROI)
	img2 = sensor.snapshot()
	img2.draw_rectangle(ROI)
	statistics2 = img2.get_statistics(roi = ROI)
	num1 = statistics.mode()
	num2 = statistics.mode()
	if(abs(num1-num2)>20):return 1
	else:return 0
	
	
def rubbish():
    clock.tick()
    
    pyb.delay(1000)

    img = sensor.snapshot()

    # default settings just do one detection... change them to search the image...
    for obj in net.classify(img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):
        print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect())
        img.draw_rectangle(obj.rect())
        # This combines the labels and confidence values into a list of tuples
        predictions_list = list(zip(labels, obj.output()))

        for i in range(len(predictions_list)):
            print("%s = %f" % (predictions_list[i][0], predictions_list[i][1]))
	
    print(clock.fps(), "fps")
    if (sum(predictions_list[i][1])/len(predictions_list[i][1]))>0.8:
        print(prediction_list[i][1])
        uart.write(predictions_list[i][0])
    else:
        rubbish()

if(compare()==1):
	rubbish()
	while(True):
		if uart.any():
			notice = uart.readline().decode()
		if notice =='G':
			rubbish()

      0_1697433161873_7e1ff1f6-dc6a-4763-a249-7594dacd3c77-image.png

      0
    • C

      这个代码是哪里有问题吗？怎么运行不了也拍不了照片，传不了值？自动就停止运行了？跟arduino连接也没反应

      0
    • C
       

      import sensor, image, time, os, tf, uos, gc, pyb, machine,math,tf
from pyb import UART
uart = UART(3, 9600)
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((240, 240))
sensor.skip_frames(time=2000)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)

net = None
labels = None

ROI = (20,20,200,200)

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:
    print(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) + ')')

clock = time.clock()

def compare():
	img1 = sensor.snapshot()
	img1.draw_rectangle(ROI)
	statistics = img1.get_statistics(roi = ROI)
	img2 = sensor.snapshot()
	img2.draw_rectangle(ROI)
	statistics2 = img2.get_statistics(roi = ROI)
	num1 = statistics.mode()
	num2 = statistics.mode()
	if(abs(num1-num2)>50):  return 1
    #print("1")return 0
	
	
def rubbish():
    clock.tick()
    
    pyb.delay(1000)

    img = sensor.snapshot()

    # default settings just do one detection... change them to search the image...
    for obj in net.classify(img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):
        print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect())
        img.draw_rectangle(obj.rect())
        # This combines the labels and confidence values into a list of tuples
        predictions_list = list(zip(labels, obj.output()))

        for i in range(len(predictions_list)):
            print("%s = %f" % (predictions_list[i][0], predictions_list[i][1]))
	
    print(clock.fps(), "fps")
    if (sum(predictions_list[i][1])/len(predictions_list[i][1]))>0.8:
        print(prediction_list[i][1])
        uart.write(predictions_list[i][0])
    

while(True):
    res = compare()
    if(res==1):
        print(OK)
        rubbish()
        while(True):
            if uart.any():
                notice = uart.readline().decode()
            if notice =='G':
                rubbish()
      0
    • C

      刚刚又改了一下代码，发现不报错了，但是串行终端没有输出数据，这个代码是哪里出问题了呀？

      0

    • 错误太多，实在没法改。

      0