l2_norm opencv torch比较

目录

opencv

 pytorch:

sklearn

opencv

  

   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      l2_norm=cv2.norm(features, cv2.NORM_L2)
     
    
   

    

     

    
    

     

      if l2_norm > 0:
     
    
   

    

     

    
    

     

       features = features / l2_norm
     
    
  
 

  

   

    

     

    
    

     

      import cv2
     
    
   

    

     

    
    

     

      import numpy as np
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      features=np.array([1,2,3])
     
    
   

    

     

    
    

     

      l2_norm=cv2.norm(features, cv2.NORM_L2)
     
    
   

    

     

    
    

     

      if l2_norm > 0:
     
    
   

    

     

    
    

     

       features = features / l2_norm
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      print(features)
     
    
   

    

     

    
    

     

      print(l2_norm,l2_norm**2)
     
    
  
 

结果：

[0.26726124 0.53452248 0.80178373]
3.7416573867739413 14.0

 pytorch:

  

   

    

     

    
    

     

      def l2_norm(input,axis=1):
     
    
   

    

     

    
    

     

       norm = torch.norm(input,2,axis
     
    
  
 

文章来源: blog.csdn.net，作者：网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/115412457