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    aupf

    @aupf

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    aupf 发布的帖子

    • 有关减少光线干扰问题

      飞行器下方白色背景有一红色光源,飞行器需要跟着红色光源飞,起飞前红色光源在飞行器身下,起飞后由于光线不同,红色光源的阈值不同,无法识别,怎么解决?谢谢大佬们。

      发布在 OpenMV Cam
      A
      aupf
    • RE: NCC模板匹配提示无法导入search_ex,求助!

      @aupf 我用了dfu升级,还是不好使

      发布在 OpenMV Cam
      A
      aupf
    • RE: NCC模板匹配提示无法导入search_ex,求助!

      我用的是最新的固件啊,3.4.1

      发布在 OpenMV Cam
      A
      aupf
    • RE: NCC模板匹配提示无法导入search_ex,求助!

      0_1559139057187_1.png

      发布在 OpenMV Cam
      A
      aupf
    • NCC模板匹配提示无法导入search_ex,求助!
      # Template Matching Example - Normalized Cross Correlation (NCC)
      #
      # This example shows off how to use the NCC feature of your OpenMV Cam to match
      # image patches to parts of an image... expect for extremely controlled enviorments
      # NCC is not all to useful.
      #
      # WARNING: NCC supports needs to be reworked! As of right now this feature needs
      # a lot of work to be made into somethin useful. This script will reamin to show
      # that the functionality exists, but, in its current state is inadequate.
      
      import time, sensor, image
      from image import SEARCH_EX, SEARCH_DS
      #从imgae模块引入SEARCH_EX和SEARCH_DS。使用from import仅仅引入SEARCH_EX,
      #SEARCH_DS两个需要的部分,而不把image模块全部引入。
      
      # Reset sensor
      sensor.reset()
      
      # Set sensor settings
      sensor.set_contrast(1)
      sensor.set_gainceiling(16)
      # Max resolution for template matching with SEARCH_EX is QQVGA
      sensor.set_framesize(sensor.QQVGA)
      # You can set windowing to reduce the search image.
      #sensor.set_windowing(((640-80)//2, (480-60)//2, 80, 60))
      sensor.set_pixformat(sensor.GRAYSCALE)
      
      # Load template.
      # Template should be a small (eg. 32x32 pixels) grayscale image.
      template = image.Image("/template.pgm")
      #加载模板图片
      
      clock = time.clock()
      
      # Run template matching
      while (True):
          clock.tick()
          img = sensor.snapshot()
      
          # find_template(template, threshold, [roi, step, search])
          # ROI: The region of interest tuple (x, y, w, h).
          # Step: The loop step used (y+=step, x+=step) use a bigger step to make it faster.
          # Search is either image.SEARCH_EX for exhaustive search or image.SEARCH_DS for diamond search
          #
          # Note1: ROI has to be smaller than the image and bigger than the template.
          # Note2: In diamond search, step and ROI are both ignored.
          r = img.find_template(template, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          #find_template(template, threshold, [roi, step, search]),threshold中
          #的0.7是相似度阈值,roi是进行匹配的区域(左上顶点为(10,0),长80宽60的矩形),
          #注意roi的大小要比模板图片大,比frambuffer小。
          #把匹配到的图像标记出来
          if r:
              img.draw_rectangle(r)
      
          print(clock.fps())
      ![0_1559139015910_1.png](https://fcdn.singtown.com/73e6c55d-09b6-4ff9-ac1a-0206164e45fa.png) 
      
      发布在 OpenMV Cam
      A
      aupf