或者支持基于 MobileNetV1 的网络的图像分割吗？

openMVH7plus是否支持运行自己编写的基于 MobileNetV1 的网络的边缘检测模型？

OPENMV4 H7 Plus都支持哪些轻量级神经网络？是否支持EfficientNet、SqueezeNet 、Tiny YOLO等模型的运行？

可以将自己训练的神经网络模型部署到openMV上运行嘛？还是必须使用edeg impluse官网上训练出来的模型？或者可以自己编写模型放到edge impluse官网上训练嘛？

我使用的是MV H7plus

我自己写好的mobilenetV3-small上传至edge impluse训练，并部署到openMV上，这是可以操作的吗？

openMV上可以部署轻量级MobilenetV3 samall并运行吗？有没有大佬知道，求请教？谢谢![

for obj in net.classify(img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):这行代码显示的错误

import sensor, image, time, os, tf, 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

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

    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")

使用edge impluse网站的迁移学习训练出来的代码显示错误怎么解决呀？
很急，有没有大佬帮忙看看