• OpenMV VSCode 扩展发布了,在插件市场直接搜索OpenMV就可以安装
  • 如果有产品硬件故障问题,比如无法开机,论坛很难解决。可以直接找售后维修
  • 发帖子之前,请确认看过所有的视频教程,https://singtown.com/learn/ 和所有的上手教程http://book.openmv.cc/
  • 每一个新的提问,单独发一个新帖子
  • 帖子需要目的,你要做什么?
  • 如果涉及代码,需要报错提示全部代码文本,请注意不要贴代码图片
  • 必看:玩转星瞳论坛了解一下图片上传,代码格式等问题。
  • MemoryError: Out of fast Frame Buffer Stack Memory!



    • Edge Impulse - OpenMV Image Classification Example

      import sensor, image, time, os, tf

      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 = "trained.tflite"
      labels = [line.rstrip('\n') for line in open("labels.txt")]

      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 tf.classify(net, 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")


    • edge impulse只能在OpenMV4Plus上运行。OpenMV4不行。