ML之Hierarchical clustering：利用层次聚类算法来把100张图片自动分成红绿蓝三种色调

ML之Hierarchical clustering：利用层次聚类算法来把100张图片自动分成红绿蓝三种色调

目录

输出结果

实现代码

输出结果

实现代码

  

   

    

     

    
    

     

      #!/usr/bin/python
     
    
   

    

     

    
    

     

      # coding:utf-8
     
    
   

    

     

    
    

     

      from PIL import Image, ImageDraw   
     
    
   

    

     

    
    

     

      from HierarchicalClustering import hcluster   
     
    
   

    

     

    
    

     

      from HierarchicalClustering import getheight
     
    
   

    

     

    
    

     

      from HierarchicalClustering import getdepth
     
    
   

    

     

    
    

     

      import numpy as np
     
    
   

    

     

    
    

     

      import os
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      def drawdendrogram(clust, imlist, jpeg= 'clusters.jpg'): 
     
    
   

    

     

    
    

     

       h = getheight(clust)*20 
     
    
   

    

     

    
    

     

       w = 1200
     
    
   

    

     

    
    

     

       depth = getdepth(clust) 
     
    
   

    

     

    
    

     

       scaling = float(w - 150)/depth 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       img = Image.new('RGB', (w, h), (255, 255, 255)) 
     
    
   

    

     

    
    

     

       draw = ImageDraw.Draw(img) 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       draw.line((0, h/2, 10, h/2), fill=(255, 0, 0))   
     
    
   

    

     

    
    

     

       drawnode(draw, clust, 10, int(h/2), scaling, imlist, img)  
     
    
   

    

     

    
    

     

       img.save(jpeg) 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      def drawnode(draw,clust,x,y,scaling,imlist,img): if clust.id < 0: 
     
    
   

    

     

    
    

     

       h1 = getheight(clust.left)*20
     
    
   

    

     

    
    

     

       h2 = getheight(clust.right)*20
     
    
   

    

     

    
    

     

       top = y - (h1 + h2)/2
     
    
   

    

     

    
    

     

       bottom = y + (h1 + h2)/2
     
    
   

    

     

    
    

     

       ll = clust.distance * scaling
     
    
   

    

     

    
    

     

       draw.line((x, top + h1/2, x, bottom - h2/2), fill=(255, 0, 0))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       draw.line((x, top + h1/2, x + ll, top + h1/2), fill=(255, 0, 0))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       draw.line((x, bottom - h2/2, x + ll, bottom - h2/2), fill=(255, 0, 0))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       drawnode(draw, clust.left, x + ll, top + h1/2, scaling, imlist, img)
     
    
   

    

     

    
    

     

       drawnode(draw, clust.right, x + ll, bottom - h2/2, scaling, imlist, img)
     
    
   

    

     

    
    

     
 else: 
     
    
   

    

     

    
    

     

       nodeim = Image.open(imlist[clust.id])
     
    
   

    

     

    
    

     

       nodeim.thumbnail((20, 20))   
     
    
   

    

     

    
    

     

       ns = nodeim.size
     
    
   

    

     

    
    

     
 print (x,y - ns[1]//2)
     
    
   

    

     

    
    

     
 print (x + ns[0])
     
    
   

    

     

    
    

     
 print (img.paste(nodeim, (int(x), int(y - ns[1]//2), int(x + ns[0]),int(y + ns[1] - ns[1]//2))))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      imlist=[]
     
    
   

    

     

    
    

     

      folderpath = r'F:\File_Python\Crawler' 
     
    
   

    

     

    
    

     

      for filename in os.listdir(folderpath): 
     
    
   

    

     

    
    

     
 if os.path.splitext(filename)[1]=='.jpg':
     
    
   

    

     

    
    

     

       imlist.append(os.path.join(folderpath,filename))
     
    
   

    

     

    
    

     

      n=len(imlist)  
     
    
   

    

     

    
    

     

      print(n)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      features =np.zeros((n,3))  
     
    
   

    

     

    
    

     

      for i in range(n): 
     
    
   

    

     

    
    

     

       im=np.array(Image.open(imlist[i])) 
     
    
   

    

     

    
    

     

       R = np.mean(im[:,:,0].flatten()) 
     
    
   

    

     

    
    

     

       G = np.mean(im[:,:,1].flatten())
     
    
   

    

     

    
    

     

       B = np.mean(im[:,:,2].flatten())
     
    
   

    

     

    
    

     

       features[i]=np.array([R,G,B])
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      tree = hcluster(features)   
     
    
   

    

     

    
    

     

      drawdendrogram(tree, imlist, jpeg=r'C:\Users\99386\Desktop\result.jpg')  #
     
    
  
 

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