Python数字识别

KeyError

#Network.py
import matplotlib.pyplot as plt
from scipy.special import expit as s
import numpy as np
class NeuralNetwork:
    #初始化神经网络
    def __init__(self,input_nodes,hidden_nodes,output_nodes,learingrate):
        self.inodes = input_nodes
        self.hnodes = hidden_nodes
        self.onodes = output_nodes
        #学习率
        self.lr = learingrate
        #权重
        self.w_ih = ( np.random.rand(self.hnodes,self.inodes) - 0.5 )
        self.w_ho = ( np.random.rand(self.onodes,self.hnodes) - 0.5 )
        pass
    #优化权重
    def train(self,inputs,trues):
        input_list=np.array(inputs,ndmin=2).T
        hi = np.dot(self.w_ih,input_list)
        ho = s(hi)
        oi = np.dot(self.w_ho,ho)
        oo = s(oi)
        true_list = np.array(trues,ndmin=2).T
        ho_error = true_list-oo
        ih_error = np.dot(self.w_ho.T,ho_error)
        self.w_ho += self.lr * np.dot(( ho_error * oo * (1.0 - oo)),np.transpose(ho))
        self.w_ih += self.lr * np.dot(( ih_error * ho * (1.0 - ho)),np.transpose(input_list)) 
    #计算输出
    def query(self,inputs):
        input_list=np.array(inputs,ndmin=2).T
        hi = np.dot(self.w_ih,input_list)
        ho = s(hi)
        oi = np.dot(self.w_ho,ho)
        oo = s(oi)
        return oo
    def __repr__(self):
        return 'A NetWork'
    __str__=__repr__
    pass

#main.py
import Network
n=Network.NeuralNetwork(10000,100,10,0.1)
file=open('mnist_train.csv','r')
file_test=open('mnist_test.csv','r')
test=file_test.readlines()
data=file.readlines()
file.close()
file_test.close()
for i in range(5):
    for mr in data:
        value = mr.split(',')
        inputs = (Network.np.asfarray(value[1:]) / 255.0 * 0.99) + 0.01
        true=Network.np.zeros(10) + 0.01
        true[int(value[0])] = 0.99
        n.train(inputs,true)
def shi(zuo):
        value = test [zuo].split(',')
        image=Network.np.asfarray(value[1:]).reshape((28,28))
        Network.plt.imshow(image,cmap='Greys')
        inputs = (Network.np.asfarray(value[1:]) / 255.0 * 0.99) + 0.01
        a1 = n.query(inputs)
        a2 = max(a1)
        AI = list(a1).index(a2)
        true = value[0]
        print('The AI is',AI)
        print('The true is',true)
        Network.plt.show()
        return AI

这里下载CSV
你也可以用自己的手写数字，但要先把它转换为784x1的CSV

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