课后题作业，如果要是自己数每个像元个数，眼花缭乱当场晕倒，所以写了程序帮助计算
也算一个自己的小练习把
思路很简单，过程繁琐但易懂，初学python，写的非常傻瓜，程序还可以优化。
地面真实像元：
计算分类后像元：
import numpy as npa=[0,0,0,0,0,0]b=[0,0,0,0,0,0]c=[0,0,0,0,0,0]d=[0,0,0,0,0,0]e=[0,0,0,0,0,0]f=[0,0,0,0,0,0]x1=np.array([[4,4,2,1,2,5,3,4,4,4], [3,4,3,4,3,1,5,3,4,0], [4,2,3,0,1,0,2,1,1,4], [1,5,1,5,3,0,4,4,5,2], [2,1,3,1,5,1,0,4,4,1], [5,4,1,2,4,1,3,4,4,2], [5,1,2,1,1,4,2,1,3,1], [2,4,3,1,3,0,4,4,3,4], [4,4,5,4,4,4,5,4,3,2], [1,0,1,3,3,4,4,0,1,1]])x2=np.array([[0,0,0,2,4,0,0,2,2,3], [4,4,1,1,2,0,0,5,3,3], [2,3,3,0,3,2,1,5,1,3], [5,4,5,4,4,4,2,1,4,1], [3,3,4,4,3,0,4,2,0,1], [4,1,4,1,1,4,2,4,4,3], [2,1,5,2,2,1,2,4,3,3], [3,1,2,2,4,3,4,4,5,2], [2,5,0,2,0,4,4,5,3,2], [0,2,4,2,4,1,1,1,4,2]])for i in range(10): for j in range(10): if(x1[i][j]==x2[i][j]): if(x1[i][j]==0): a[0]+=1 elif(x1[i][j]==1): b[1]+=1 elif(x1[i][j]==2): c[2]+=1 elif(x1[i][j]==3): d[3]+=1 elif(x1[i][j]==4): e[4]+=1 elif(x1[i][j]==5): f[5]+=1for i in range(10): for j in range(10): if(x1[i][j]!=x2[i][j]): if(x1[i][j]==0): if(x2[i][j]==1): a[1]+=1 elif(x2[i][j]==2): a[2]+=1 elif(x2[i][j]==3): a[3]+=1 elif(x2[i][j]==4): a[4]+=1 elif(x2[i][j]==5): a[5]+=1 if(x1[i][j]==1): if(x2[i][j]==0): b[0]+=1 elif(x2[i][j]==2): b[2]+=1 elif(x2[i][j]==3): b[3]+=1 elif(x2[i][j]==4): b[4]+=1 elif(x2[i][j]==5): b[5]+=1 elif(x1[i][j]==2): if(x2[i][j]==0): c[0]+=1 elif(x2[i][j]==1): c[1]+=1 elif(x2[i][j]==3): c[3]+=1 elif(x2[i][j]==4): c[4]+=1 elif(x2[i][j]==5): c[5]+=1 elif(x1[i][j]==3): if(x2[i][j]==0): d[0]+=1 elif(x2[i][j]==1): d[1]+=1 elif(x2[i][j]==2): d[2]+=1 elif(x2[i][j]==4): d[4]+=1 elif(x2[i][j]==5): d[5]+=1 elif(x1[i][j]==4): if(x2[i][j]==0): e[0]+=1 elif(x2[i][j]==1): e[1]+=1 elif(x2[i][j]==2): e[2]+=1 elif(x2[i][j]==3): e[3]+=1 elif(x2[i][j]==5): e[5]+=1 elif(x1[i][j]==5): if(x2[i][j]==0): f[0]+=1 elif(x2[i][j]==1): f[1]+=1 elif(x2[i][j]==2): f[2]+=1 elif(x2[i][j]==3): f[3]+=1 elif(x2[i][j]==4): f[4]+=1Confusion_Matrix=np.array([a,b,c,d,e,f])print(Confusion_Matrix)sum_right=0s=0for i in range(len(Confusion_Matrix)): sum_right+=Confusion_Matrix[i][i] s+=sum(Confusion_Matrix[i])*sum(Confusion_Matrix[:,i])K=((sum_right*pow(len(x1),2)-s))/((pow(len(x1),4))-s)ztjd=sum_right/pow(len(x1),2)print("Kappa系数:",K)print("总体精度:"+str(ztjd)+"%")np.savetxt('Confusion_Matrix.csv',Confusion_Matrix, delimiter = ',')
结果如下：