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  • 在运行模板匹配时出现Region of interest is smaller than template该怎么解决?



    • 0_1563591248489_1563591145(1).png

      # 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("/2.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())
      
      

      以下是问题截图:
      0_1563591262616_1563591145(1).png0_1563591328944_5c1399b2-9518-4e11-80d6-ae5ed69dc819-image.png



    • 你的模版的尺寸太大了。



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    • 此回复已被删除!