调用MNIST手写数字数据集相关操作

 

 

 

 

 

 

 

import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np

#加载手写数字数据
mnist = tf.keras.datasets.mnist
(train_x,train_y),(train_x,train_y) = mnist.load_data()
#画图
plt.rcParams["font.family"] = 'SimHei'  # 将字体改为中文
plt.rcParams['axes.unicode_minus'] = False  # 设置了中文字体默认后，坐标的"-"号无法显示，设置这个参数就可以避免

for i in range(4):
    index = np.random.randint(0,5999)
    # print("index:",index)
    img_data = train_x[index,:]
    plt.subplot(2,2,i+1)                              #   划分子图
    plt.axis('off')                                 #   关闭坐标轴
    plt.title('train_x[{}] = {}'.format(i,train_y[index]))             #   子图标题
    plt.imshow(img_data,cmap='gray')

plt.show()