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  • Failed to load"trained.tflite"did you copy t



    • 0_168907231ng
      0_1689075386061_977d8b0f-834c-4295-a860-280352f37994-image.png

      我遇到这个问题,好多方法都是了都不行,重新上电都不行,用官方代码也不行

      Edge Impulse - OpenMV Object Detection Example

      import sensor, image, time, os, tf, math, 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
      min_confidence = 0.5

      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:
      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) + ')')

      colors = [ # Add more colors if you are detecting more than 7 types of classes at once.
      (255, 0, 0),
      ( 0, 255, 0),
      (255, 255, 0),
      ( 0, 0, 255),
      (255, 0, 255),
      ( 0, 255, 255),
      (255, 255, 255),
      ]

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

      img = sensor.snapshot()
      
      # detect() returns all objects found in the image (splitted out per class already)
      # we skip class index 0, as that is the background, and then draw circles of the center
      # of our objects
      
      for i, detection_list in enumerate(net.detect(img, thresholds=[(math.ceil(min_confidence * 255), 255)])):
          if (i == 0): continue # background class
          if (len(detection_list) == 0): continue # no detections for this class?
      
          print("********** %s **********" % labels[i])
          for d in detection_list:
              [x, y, w, h] = d.rect()
              center_x = math.floor(x + (w / 2))
              center_y = math.floor(y + (h / 2))
              print('x %d\ty %d' % (center_x, center_y))
              img.draw_circle((center_x, center_y, 12), color=colors[i], thickness=2)
      
      print(clock.fps(), "fps", end="\n\n")


    • 估计你使用的是OpenMV4 H7。
      最简单的办法是用星瞳AI在线服务生成模型。https://docs.singtown.com/ai/zh/latest/toturial/classify.html