sklearn-kmeans 人脸图像聚类
人脸图像聚类
题目
作者：龙晨天
对给定人脸图像数据集，可视化并输出聚类性能。
２.代码（该代码由某位大佬完成，我仅仅搬运，帮助更多的人）
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
import matplotlib.image as imgplt
import numpy as np
from sklearn.metrics import normalized_mutual_info_score,adjusted_rand_score
import os
import pandas as pd
from sklearn.utils.linear_assignment_ import linear_assignment
def cluster_acc(y_true, y_pred):
y_true = np.array(y_true).astype(np.int64)
assert y_pred.size == y_true.size
D = max(y_pred.max(), y_true.max()) + 1
w = np.zeros((D, D), dtype=np.int64)
for i in range(y_pred.size):
w[y_pred[i], y_true[i]] += 1
ind = linear_assignment(w.max() - w)
return sum([w[i, j] for i, j in ind]) * 1.0 / y_pred.size
def getinfo():
# 获取文件并构成向量
#预测值为1维，把一张图片的三维压成1维，那么n张图片就是二维
global total_photo
file = os.listdir(r'D:\作品\python\face_images\\')
i = 0
for subfile in file:
photo = os.listdir(r'D:\作品\python\face_images\\' + subfile) #文件路径自己改
for name in photo:
photo_name.append(r'D:\作品\python\face_images\\'+ subfile+'\\'+name)
target.append(i)
i += 1
for path in photo_name:
photo = imgplt.imread(path)
photo = photo.reshape(1, -1)
photo = pd.DataFrame(photo)
total_photo = total_photo.append(photo, ignore_index=True)
total_photo = total_photo.values
def kmeans():
clf = KMeans(n_clusters=10)
clf.fit(total_photo)
y_predict = clf.predict(total_photo)
centers = clf.cluster_centers_
result = centers[y_predict]
result = result.astype("int64")
result = result.reshape(200, 200, 180, 3)#图像的矩阵大小为200,180,3
return result,y_predict
def draw():
fig,ax = plt.subplots(nrows=10,ncols=20,sharex = True,sharey = True,figsize = [15,8],dpi = 80)
plt.subplots_adjust(wspace = 0,hspace = 0)
count = 0
for i in range(10):
for j in range(20):
ax[i,j].imshow(result[count])
count += 1
plt.xticks([])
plt.yticks([])
plt.show()
def score():
ACC = cluster_acc(target, y_predict) # y 真实值 y_predict 预测值
NMI = normalized_mutual_info_score(target, y_predict)
ARI = adjusted_rand_score(target, y_predict)
print(" ACC = ", ACC)
print(" NMI = ", NMI)
print(" ARI = ", ARI)
if __name__ == '__main__':
photo_name = []
target = []
total_photo = pd.DataFrame()
getinfo()
result,y_predict = kmeans()
score()
draw()
３. 输出
说明：当个只会做搬运工的废物，再此代表需求者向这位大佬致敬
作者：龙晨天
