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  • 我在运行识别矩形的例程时,发现rect.x()为负值,这是为什么?



    • 我在运行识别矩形的例程时,发现rect.x(),rect.y()为负值,这是为什么?
      代码:

      # Find Rects Example
      #
      # This example shows off how to find rectangles in the image using the quad threshold
      # detection code from our April Tags code. The quad threshold detection algorithm
      # detects rectangles in an extremely robust way and is much better than Hough
      # Transform based methods. For example, it can still detect rectangles even when lens
      # distortion causes those rectangles to look bent. Rounded rectangles are no problem!
      # (But, given this the code will also detect small radius circles too)...
      
      import sensor, image, time
      
      sensor.reset()
      sensor.set_pixformat(sensor.RGB565) # grayscale is faster (160x120 max on OpenMV-M7)
      sensor.set_framesize(sensor.QQVGA)
      sensor.skip_frames(time = 2000)
      clock = time.clock()
      
      while(True):
          clock.tick()
          img = sensor.snapshot()
      
          # `threshold` below should be set to a high enough value to filter out noise
          # rectangles detected in the image which have low edge magnitudes. Rectangles
          # have larger edge magnitudes the larger and more contrasty they are...
      
          for r in img.find_rects(threshold = 10000):
              img.draw_rectangle(r.rect(), color = (255, 0, 0))
              for p in r.corners(): img.draw_circle(p[0], p[1], 5, color = (0, 255, 0))
              print(r)
      
          print("FPS %f" % clock.fps())
      
      

      运行结果:
      0_1564591849019_1564591586(1).png



    • 我测试了代码,不是负数。

      请提供你的硬件版本,固件版本,IDE版本。



    • @kidswong999 当我识别到多个举行时就会出现这负值
      如图
      0_1564802592483_1564802507(1).png

      硬件版本:
      0_1564802719896_IMG20190803112432.jpg
      是这个吧?

      怎么看固件版本啊?

      IDE版本
      0_1564803029523_1564802996(1).png



    • 我这里挺正常的。

      0_1564835730395_ca275b02-4559-4b96-97d5-34096901a6a1-image.png



    • @kidswong999 请问大佬知不知道产生负值的原因?