数字识别里面用tf为什么会报这样的错？
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This code run in OpenMV4 H7 or OpenMV4 H7 Plus
import sensor, image, time, os, tf
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.GRAYSCALE) # 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.clock = time.clock()
while(True):
clock.tick()
img = sensor.snapshot().binary([(0,64)])
for obj in tf.classify("trained.tflite", img, min_scale=1.0, scale_mul=0.5, x_overlap=0.0, y_overlap=0.0):
output = obj.output()
number = output.index(max(output))
print(number)
print(clock.fps(), "fps")
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将openmv的固件版本按照https://singtown.com/learn/50903/的办法降级成v4.5.5即以前的版本即可
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但是我之前降级成v4.5.5版本的时候出现了卡烧录90%的问题(OpenMV型号 M7 Plus) 如果你遇见了相同的问题可以试试v4.5.4版本(注：如果卡烧录90%需要使用openmv IDE自带的DFU烧录功能请将openmv重新升级成4.5.6以上版本并尝试降成其他版本
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提供具体的硬件型号，和固件版本。