• 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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  • 运行的时候显示IndexError:list index out of range 怎么解决?



    • 
      
      import sensor, image, time, math, lcd
      
      from pyb import UART
      from pyb import LED
      uart = UART(3, 115200)
      
      LED(1).on()
      LED(2).on()
      LED(3).on()
      
      lcd.init()
      
      GRAYSCALE_THRESHOLD = [(0, 64)]
      
      ROIS = [ # [ROI, weight]
              (0, 100, 160, 20, 0.7), # You'll need to tweak the weights for you app
              (0, 050, 160, 20, 0.3), # depending on how your robot is setup.
              (0, 000, 160, 20, 0.1)
             ]
      
      weight_sum = 0 #权值和初始化
      for r in ROIS: weight_sum += r[4] # r[4] is the roi weight.
      
      sensor.reset() # Initialize the camera sensor.
      sensor.set_pixformat(sensor.GRAYSCALE) # use grayscale.
      sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
      sensor.skip_frames(30,time = 2000) # Let new settings take affect.
      sensor.set_auto_gain(False) # must be turned off for color tracking
      sensor.set_auto_whitebal(False) # must be turned off for color tracking
      
      clock = time.clock() # Tracks FPS.
      
      def send_frame(cx, cy):
          uart.writechar(0xA5)
          uart.writechar(0x5A)
          uart.writechar(cx)
          uart.writechar(cy)
          uart.writechar(cx + cy)
      
      while(True):
          clock.tick() # Track elapsed milliseconds between snapshots().
          img = sensor.snapshot() # Take a picture and return the image.
      
          centroid_sum = 0
      
          for r in ROIS:
              blobs = img.find_blobs(GRAYSCALE_THRESHOLD, roi=r[0:4], merge=True)
              # r[0:4] is roi tuple.
      
              if blobs:
                  most_pixels = 0
                  largest_blob = 0
                  for i in range(len(blobs)):
      
                      if blobs[i].pixels() > most_pixels:
                          most_pixels = blobs[i].pixels()
                          largest_blob = i
                  img.draw_rectangle(blobs[largest_blob].rect())
                  img.draw_rectangle((0,0,30, 30))
                  #将此区域的像素数最大的颜色块画矩形和十字形标记出来
                  img.draw_cross(blobs[largest_blob].cx(),
                                 blobs[largest_blob].cy())
      
                  centroid_sum += blobs[largest_blob].cx() * r[4] # r[4] is the roi weight.
      
      
          center_pos = (centroid_sum / weight_sum) # Determine center of line.
      
          deflection_angle = 0
      
          deflection_angle = -math.atan((center_pos-80)/60)
      
      
          deflection_angle = math.degrees(deflection_angle)
      
      
          print("Turn Angle: %f" % deflection_angle)
          send_frame(blobs[largest_blob].cx(), blobs[largest_blob].cy())
          lcd.display(img)
          print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
      
      
      


    • 代码的逻辑有问题。

      如果没有找到色块,blobs[largest_blob].cx()就会错误。