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')  #