神经网络训练模型问题

[l46w]

我是按照视频一步步来的，但是到最后出现了问题，这是因为我的openmv里没有这个库吗，我用的是openmv4 H7plus

[kidswong999]

放一下代码，应该是edge impulse下载下来的。

[l46w]

嗯呢，我放的那个代码就是edge impulse下载下来的，还是这种问题，openmv4有这个神经网络库吗

[kidswong999]

@l46w edge impulse只能在OpenMV4 Plus上运行，OpenMV4 不行

[l46w]

可是我的就是openmv4 H7 Plus啊，为什么还是不行

[kidswong999]

@l46w 你上传一下代码。全部代码文本，请注意不要贴代码图片

[l46w]

Edge Impulse - OpenMV Image Classification Example

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 built in model
labels, net = tf.load_builtin_model('trained')
except Exception as e:
raise Exception(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")

这是模型里跑出来的代码

[kidswong999]

你这个不对，你在edge impulse要选择OpenMV Library而不是OpenMV Firmware