python练习7 Scipy

python练习7 Scipy

一、Scipy聚类kmeans

SciPy is an open-source software for mathematics, science, and engineering.

聚类实例：

import numpy as np
from scipy.cluster.vq import vq, kmeans, whiten
import matplotlib.pyplot as pltfe=np.array([[1.9,2.0],[1.7,2.5],[1.6,3.1],[0.1,0.1],[0.8,0.3],[0.4,0.3],[0.22,0.1],[0.4, 0.3],[0.4,0.5],[1.8,1.9]])                     book=np.array((fe[0],fe[1]))
print(type(book))
print("book:n",book)codebook,distortion=kmeans(fe,book)
#可以写kmeans（wf,2),2表示两个质心，同时启用iter参数
print("codebook:",codebook) #codebook聚类中心
print("distortion: ", distortion) #distortion控制方差大小plt.scatter(fe[:,0], fe[:,1], c='g')  #scatter提供散点图
plt.scatter(codebook[:, 0], codebook[:, 1], c='r')
plt.show()

运行结果：红色的为聚类中心

二、对图像色彩聚类

1.用PIL生成小尺寸的图并提取色彩

①resize或者thumbnail生成缩略图

②getcolors()返回图像中的颜色列表

import os
from PIL import Image
import matplotlib.pyplot as pltos.chdir(r'D:pythonAds2021')
im=np.array(Image.open('girl.png'))#用缩略图聚类
def colorz(filename,n=3):img=Image.open(filename)img&#ate(-90)img.thumbnail((200,200))w,h=img.sizeprint(w,h)print('w*h=',w*h)plt.axis('off')plt.imshow(img)plt.show()points=[]for count,color lors(w*h):  points.append(color)return points
colorz('girl.png',3)

 2.取出图像的色彩和频次

import numpy as np
from scipy.cluster.vq import vq, kmeans, whiten
import matplotlib.pyplot as pltpoints=colorz('girl.jpg',3)
print(points[0:10])fe = np.array(points,dtype=float)   #聚类需要是Float或者Double
print(fe[0:10])
book =np.array((fe[100],fe[1],fe[8],fe[8]))   #聚类中心，初始值
print(type(book))
print("book: n",book)#codebook, distortion = kmeans(fe,book)
codebook, distortion = kmeans(fe,7)   #7是聚类中心个数
# 可以写kmeans(wf,2)， 2表示两个质心，同时启用iter参数print("codebook:", codebook)   #聚类中心
centers=np.array(codebook,dtype=int)  #色彩的均值计算出来一般是浮点数，需要转化为整数int
print(centers)
print("distortion: ", distortion)fe=np.array(points)
plt.scatter(fe[:,0], fe[:,2], c='b')
plt.scatter(codebook[:, 0], codebook[:,2], c='r')   #聚类中心
plt.show()

运行结果：如下7个聚类中心

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三、把色彩聚类加入到Flask框架里