• 安装星瞳实验室APP,快速收到回复。扫描二维码或者点击 https://singtown.com/app/
  • 必看:玩转星瞳论坛了解一下图片上传,代码格式等问题。
  • 一个提问,一个帖子,标题为问题的介绍
  • 请贴出具体的代码,与报错提示。
  • 代码一定要让别人可以运行的文本,不要贴图片
  • 模板识别和颜色识别能串起来一起用吗



    • 另外想问一下,模板识别想识别0到9,但是它会报错,说是请降低像素,减少在运行的数量,降低像素还是不能解决。最后减少了3个数字它才能正常的运行,这怎么解决?



    • 请发具体的代码,与报错提示。



    • 0_1533461120482_16.png
      import time, sensor, image
      from image import SEARCH_EX, SEARCH_DS

      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.

      template0 = image.Image("/0.pgm")
      template1 = image.Image("/1.pgm")
      template2 = image.Image("/2.pgm")
      template3 = image.Image("/3.pgm")
      template4 = image.Image("/4.pgm")
      template5 = image.Image("/5.pgm")
      template6 = image.Image("/6.pgm")
      template7 = image.Image("/7.pgm")
      template8 = image.Image("/8.pgm")
      template9 = image.Image("/9.pgm")

      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.
      r0 = img.find_template(0, 0.70, step=4, search=SEARCH_EX)
      if r0:
          print('0')
      r1 = img.find_template(1, 0.70, step=4, search=SEARCH_EX) 
      if r1:
          print('1')
      r2 = img.find_template(2, 0.70, step=4, search=SEARCH_EX)
      if r2:
          print('2')
      r3 = img.find_template(3, 0.70, step=4, search=SEARCH_EX) 
      if r3:
          print('3')
      r4 = img.find_template(4, 0.70, step=4, search=SEARCH_EX)
      if r4:
          print('4')
      r5 = img.find_template(5, 0.70, step=4, search=SEARCH_EX) 
      if r5:
          print('5')
      r6 = img.find_template(6, 0.70, step=4, search=SEARCH_EX)
      if r6:
          print('6')
      r7 = img.find_template(7, 0.70, step=4, search=SEARCH_EX) 
      if r7:
          print('7')
      r8 = img.find_template(8, 0.70, step=4, search=SEARCH_EX) 
      if r8:
          print('8')
      r9 = img.find_template(9, 0.70, step=4, search=SEARCH_EX) 
      if r9:
          print('9')


    • import time, sensor, image
      from image import SEARCH_EX, SEARCH_DS

      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.

      template0 = image.Image("/0.pgm")
      template1 = image.Image("/1.pgm")
      template2 = image.Image("/2.pgm")
      template3 = image.Image("/3.pgm")
      template4 = image.Image("/4.pgm")
      template5 = image.Image("/5.pgm")
      template6 = image.Image("/6.pgm")
      template7 = image.Image("/7.pgm")
      template8 = image.Image("/8.pgm")
      template9 = image.Image("/9.pgm")

      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.
      r0 = img.find_template(template0, 0.70, step=4, search=SEARCH_EX)
      if r0:
          print('0')
      r1 = img.find_template(template1, 0.70, step=4, search=SEARCH_EX) 
      if r1:
          print('1')
      r2 = img.find_template(template2, 0.70, step=4, search=SEARCH_EX)
      if r2:
          print('2')
      r3 = img.find_template(template3, 0.70, step=4, search=SEARCH_EX) 
      if r3:
          print('3')
      r4 = img.find_template(template4, 0.70, step=4, search=SEARCH_EX)
      if r4:
          print('4')
      r5 = img.find_template(template5, 0.70, step=4, search=SEARCH_EX) 
      if r5:
          print('5')
      r6 = img.find_template(template6, 0.70, step=4, search=SEARCH_EX)
      if r6:
          print('6')
      r7 = img.find_template(template7, 0.70, step=4, search=SEARCH_EX) 
      if r7:
          print('7')
      r8 = img.find_template(template8, 0.70, step=4, search=SEARCH_EX) 
      if r8:
          print('8')
      r9 = img.find_template(template9, 0.70, step=4, search=SEARCH_EX) 
      if r9:
          print('9')