• 免费好用的星瞳AI云服务上线!简单标注,云端训练,支持OpenMV H7和OpenMV H7 Plus。可以替代edge impulse。 https://forum.singtown.com/topic/9519
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  • openmv怎么识别物体后求出相应的坐标?求大佬解答



    • import sensor, image, time, os, tf, uos, gc
      
      sensor.reset()
      sensor.set_pixformat(sensor.RGB565)
      sensor.set_framesize(sensor.QVGA)
      sensor.set_windowing((240, 240))
      sensor.skip_frames(time=2000)
      
      net = None
      labels = None
      
      try:
          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()
      
          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())
      
              # 获取物体的坐标
              
              cx = x + (w // 2)
              cy = y + (h // 2)
              print("物体坐标:({},{})".format(cx, cy))
      
              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")
      


    • 你的代码是分类,你要用FOMO目标点检测。https://singtown.com/learn/50918/