无监督学习洁化简单图像

最近刚开始接触机器学习 用无监督学习的方法处理了一下自己的头像 整体思路是将图片的每一个像素点作为一个元素 利用K均值聚类将将这些像素点分为两类 黑的全黑白的全白 也可以换各种颜色 先看原图

 这是处理之后的图

 换个颜色

 代买如下

import matplotlib.pyplot as plt
import numpy as np
from sklearn.cluster import KMeans
class img():
 def __init__(self,imgname):
 self.imgname imgname
 def img_read(self):
 data plt.imread(self.imgname)
 return data
 def img_to_pixel(self):
 data self.img_read()
 shape data.shape
 pixel []
 for i in range(shape[0]):
 for j in range(shape[1]):
 pixel.append(data[i,j,:])
 return pixel
 def cluster_KMeans(self):
 pixel self.img_to_pixel()
 imgdata self.img_read()
 shape imgdata.shape
 cluster KMeans(n_clusters 2)
 cluster.fit(pixel)
 label cluster.labels_.reshape(shape[0],shape[1],1)
 img_label np.concatenate([imgdata,label],axis 2)
 return img_label
 def plot_img(self):
 img_label self.cluster_KMeans()
 shape img_label.shape
 fig,ax plt.subplots()
 for i in range(shape[0]):
 for j in range(shape[1]):
 if img_label[i,j,3]! 0:
 img_label[i,j,:3] np.array([[[0, 0, 0]]])
 else:
 img_label[i, j, :3] np.array([[[255,255,255]]])
 ax.imshow(img_label[:,:,:3])
 plt.show()
if __name__ __main__ :
 img img( 1.jpg )
 img.plot_img()