tensorflow加载mnist数据集 tensorflow实现加载mnist数据集
Missayaa 人气:0mnist作为最基础的图片数据集,在以后的cnn,rnn任务中都会用到
import numpy as np import tensorflow as tf import matplotlib.pyplot as plt from tensorflow.examples.tutorials.mnist import input_data #数据集存放地址,采用0-1编码 mnist = input_data.read_data_sets('F:/mnist/data/',one_hot = True) print(mnist.train.num_examples) print(mnist.test.num_examples) trainimg = mnist.train.images trainlabel = mnist.train.labels testimg = mnist.test.images testlabel = mnist.test.labels #打印相关信息 print(type(trainimg)) print(trainimg.shape,) print(trainlabel.shape,) print(testimg.shape,) print(testlabel.shape,) nsample = 5 randidx = np.random.randint(trainimg.shape[0],size = nsample) #输出几张数字的图 for i in randidx: curr_img = np.reshape(trainimg[i,:],(28,28)) curr_label = np.argmax(trainlabel[i,:]) plt.matshow(curr_img,cmap=plt.get_cmap('gray')) plt.title(""+str(i)+"th Training Data"+"label is"+str(curr_label)) print(""+str(i)+"th Training Data"+"label is"+str(curr_label)) plt.show()
程序运行结果如下:
Extracting F:/mnist/data/train-images-idx3-ubyte.gz Extracting F:/mnist/data/train-labels-idx1-ubyte.gz Extracting F:/mnist/data/t10k-images-idx3-ubyte.gz Extracting F:/mnist/data/t10k-labels-idx1-ubyte.gz 55000 10000 <class 'numpy.ndarray'> (55000, 784) (55000, 10) (10000, 784) (10000, 10) 52636th
输出的图片如下:
Training Datalabel is9
下面还有四张其他的类似图片
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