4. edgeimpluse 训练出来的代码报错 Failed to load "trained.tflite两个文件都在盘里
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    • edgeimpluse 训练出来的代码报错 Failed to load "trained.tflite两个文件都在盘里

    • U

      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 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")

      点击运行报这个错误是怎么回事Exception: Failed to load "trained.tflite" , did you copythe .tflite and labels.txt file onto the mass-storagedevice? (Out of fast Frame Buffer Stack Memory! Pleasereduce the resolution of the image you are running thisalgorithm on to bypass this issue!)。我确定我的openmv 在没插入内存卡之前是几百KB的内存大小，插入内存卡之后是29.5G的内存，我也把edge impluse 训练完的三个文件都拖入到了openmv插入电脑后的盘（F盘）里，可还是报这个错。我之前已经做过两次openmv识别的了，都不会这样，是不是这个openmv坏了，还是内存卡坏了

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    • 估计你使用的是OpenMV4 H7，而不是OpenMV4 H7 Plus。
      如果是OpenMV4 H7，用星瞳AI云服务训练，可以生成。

      https://docs.singtown.com/ai/zh/latest/toturial/classify.html

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