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  • 在做人脸识别的时候,能够让电脑屏幕显示彩色的图像吗?



    • 在做人脸识别的时候,能够让电脑屏幕显示彩色的图像吗???



    • 没意义啊,因为人脸识别的算法是黑白的



    • @kidswong999 意思就是不能让电脑屏幕显示彩色的吗???因为老师想看看彩色的样子,并且想保存彩色的照片



    • 那你直接在程序里把GRAYSCALE改成RGB565就完事了。



    • @kidswong999 那还能进行人脸识别吗????



    • 你试试不就知道了😅 ,我刚才运行了一下没问题。



    • @kidswong999 啊???我直接运行就卡死了???我们的不一样吗???能麻烦你把代码给我看一下吗???



    • # Face Detection Example
      #
      # This example shows off the built-in face detection feature of the OpenMV Cam.
      #
      # Face detection works by using the Haar Cascade feature detector on an image. A
      # Haar Cascade is a series of simple area contrasts checks. For the built-in
      # frontalface detector there are 25 stages of checks with each stage having
      # hundreds of checks a piece. Haar Cascades run fast because later stages are
      # only evaluated if previous stages pass. Additionally, your OpenMV Cam uses
      # a data structure called the integral image to quickly execute each area
      # contrast check in constant time (the reason for feature detection being
      # grayscale only is because of the space requirment for the integral image).
      
      import sensor, time, image
      
      # Reset sensor
      sensor.reset()
      
      # Sensor settings
      sensor.set_contrast(1)
      sensor.set_gainceiling(16)
      # HQVGA and GRAYSCALE are the best for face tracking.
      sensor.set_framesize(sensor.HQVGA)
      sensor.set_pixformat(sensor.RGB565)
      
      # Load Haar Cascade
      # By default this will use all stages, lower satges is faster but less accurate.
      face_cascade = image.HaarCascade("frontalface", stages=25)
      print(face_cascade)
      
      # FPS clock
      clock = time.clock()
      
      while (True):
          clock.tick()
      
          # Capture snapshot
          img = sensor.snapshot()
      
          # Find objects.
          # Note: Lower scale factor scales-down the image more and detects smaller objects.
          # Higher threshold results in a higher detection rate, with more false positives.
          objects = img.find_features(face_cascade, threshold=0.75, scale_factor=1.25)
      
          # Draw objects
          for r in objects:
              img.draw_rectangle(r)
      
          # Print FPS.
          # Note: Actual FPS is higher, streaming the FB makes it slower.
          print(clock.fps())
      
      


    • @kidswong999 谢谢了