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    kynd 发布的帖子

    • openMV的识别问题

      为啥图像的cx不变,cy会变,而且识别的图像中心的十字一直在图像的左上方而不在白框内?

      发布在 OpenMV Cam
      K
      kynd
    • RE: 更换摄像头识别数字就会卡屏?

      @kidswong999 噢解决了感谢!

      发布在 OpenMV Cam
      K
      kynd
    • RE: 更换摄像头识别数字就会卡屏?

      问题是我#之后显示indentationerror咋 解决

      发布在 OpenMV Cam
      K
      kynd
    • RE: 更换摄像头识别数字就会卡屏?

      摄像头是H7 R1的

      发布在 OpenMV Cam
      K
      kynd
    • RE: 更换摄像头识别数字就会卡屏?
      # 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.
      
      # Always pass UART 3 for the UART number for your OpenMV Cam.
      # The second argument is the UART baud rate. For a more advanced UART control
      # example see the BLE-Shield driver.
      
      import json
      from pyb import UART
      import time, sensor, image
      from image import SEARCH_EX, SEARCH_DS
      from pyb import UART
      
      uart = UART(3,9600)
      uart.init(9600,bits=8,parity=None,stop=1)
      #while(True):
          #uart.write("Hello World!\r")
          #time.sleep_ms(1000)
      
      
      # 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.
      
      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")
      
      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(template1, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r1:
              img.draw_rectangle(r1)
              print(1)
              uart.write("1")
              a=1
      
          r2 = img.find_template(template2, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r2:
              img.draw_rectangle(r2)
              print(2)
              uart.write("2")
              a=2
      
          r3 = img.find_template(template3, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r3:
              img.draw_rectangle(r3)
              print(3)
              uart.write("3")
              a=3
      
          r4 = img.find_template(template4, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r4:
              img.draw_rectangle(r4)
              print(4)
              uart.write("4")
              a=4
      
          r5 = img.find_template(template5, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r5:
              img.draw_rectangle(r5)
              print(5)
              uart.write("5")
              a=5
      
          r6 = img.find_template(template6, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r6:
              img.draw_rectangle(r6)
              print(6)
              uart.write("6")
              a=6
      
          r8 = img.find_template(template1, 0.40, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r8:
              img.draw_rectangle(r8)
              print(8)
              uart.write("8")
              a=8
      
          r7 = img.find_template(template7, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))
          if r7:
              img.draw_rectangle(r7)
              print(7)
              uart.write("7")
              a=7
      
              while(True):
                  output = json.dumps(a) 
                  print(output) 
                  uart.write(output)
      
      发布在 OpenMV Cam
      K
      kynd
    • openmv的数字识别问题

      可以识别数字,但是每次运行时识别到放在程序最后的那个数字就会卡屏是什么原因?求解

      发布在 OpenMV Cam
      K
      kynd
    • 更换摄像头识别数字就会卡屏?

      使用原来的摄像头识别数字没问题,换成新的摄像头后,其他程序都没变,但是运行时就会卡主,需要重新连接USB才能运行,这是为什么?

      发布在 OpenMV Cam
      K
      kynd