• 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
  • 我们只解决官方正版的OpenMV的问题(STM32),其他的分支有很多兼容问题,我们无法解决。
  • 如果有产品硬件故障问题,比如无法开机,论坛很难解决。可以直接找售后维修
  • 发帖子之前,请确认看过所有的视频教程,https://singtown.com/learn/ 和所有的上手教程http://book.openmv.cc/
  • 每一个新的提问,单独发一个新帖子
  • 帖子需要目的,你要做什么?
  • 如果涉及代码,需要报错提示全部代码文本,请注意不要贴代码图片
  • 必看:玩转星瞳论坛了解一下图片上传,代码格式等问题。
  • 用该代码,2代表2,3代表1,但是方框只会显示一个颜色,而且无论什么数字都能被方框罩住



    • # 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 environments
      # 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 remain to show
      # that the functionality exists, but, in its current state is inadequate.
      
      import time
      import sensor
      import image
      from image import SEARCH_EX
      
      # from image import SEARCH_DS
      
      # Reset sensor
      sensor.reset()#摄像头重置
      
      # Set sensor settings
      sensor.set_contrast(1)#设置对比度
      sensor.set_gainceiling(16)#自动增益
      # Max resolution for template matching with SEARCH_EX is QQVGA
      sensor.set_framesize(sensor.QQVGA)#分辨率大小,最大支持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)#灰度
      
      # Load template.
      # Template should be a small (eg. 32x32 pixels) grayscale image.
      #template1 = image.Image("/1.pgm")#模板图片pgm格式
      template2 = image.Image("/2.pgm")#模板图片pgm格式
      template3 = image.Image("/3.pgm")#模板图片pgm格式
      
      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.
          """
          r1 = img.find_template(#调用模板匹配函数![1_1722223662403_8f4de3c4653a29c6a9df40b2281ef50.jpg](https://fcdn.singtown.com/92922a81-8e2d-4111-ae6e-6fefb02ad501.jpg) ![0_1722223662402_288e461d9390ea8d52ccbd8164ab3e0.jpg](https://fcdn.singtown.com/e7a5c6e7-7e3c-40eb-9e85-f0e2ec517e66.jpg) 
              template1, 0.70, step=4, search=SEARCH_EX
          )  # , roi=(10, 0, 60, 60))#template图片,0.7匹配阈值,roi设置了是在规定区域寻找图像,不设置了默认整个区域寻找
          if r1:#如果找到模板图片
              img.draw_rectangle(r1,color=(0,0,0))
          """
          r2 = img.find_template(#调用模板匹配函数
              template2, 0.70, step=4, search=SEARCH_EX
          )  # , roi=(10, 0, 60, 60))#template图片,0.7匹配阈值,roi设置了是在规定区域寻找图像,不设置了默认整个区域寻找
          if r2:#如果找到模板图片
              img.draw_rectangle(r2,color=(255,0,0))
      
          r3 = img.find_template(#调用模板匹配函数
              template3, 0.70, step=4, search=SEARCH_EX
          )  # , roi=(10, 0, 60, 60))#template图片,0.7匹配阈值,roi设置了是在规定区域寻找图像,不设置了默认整个区域寻找
          if r3:#如果找到模板图片
              img.draw_rectangle(r3,color=(0,0,0))
      
          print(clock.fps())