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') #
