load_mnist.py

# -*- coding: utf-8 -*-  

import struct
import numpy as np


def loadLabelSet(filename):  
  
    binfile = open(filename, 'rb') # 读二进制文件  
    buffers = binfile.read()  
  
    head = struct.unpack_from('>II', buffers, 0) # 取label文件前2个整形数  
  
    labelNum = head[1]  
    offset = struct.calcsize('>II')  # 定位到label数据开始的位置  
  
    numString = '>' + str(labelNum) + "B" # fmt格式：'>60000B'  
    labels = struct.unpack_from(numString, buffers, offset) # 取label数据  
  
    binfile.close()  
    labels = np.reshape(labels, [labelNum]) # 转型为列表(一维数组)  
  
    return labels

def loadImageSet(filename):  
  
    binfile = open(filename, 'rb') # 读取二进制文件  
    buffers = binfile.read()  
  
    head = struct.unpack_from('>IIII', buffers, 0) # 取前4个整数，返回一个元组  
  
    offset = struct.calcsize('>IIII')  # 定位到data开始的位置  
    imgNum = head[1]  
    width = head[2]  
    height = head[3]  
  
    bits = imgNum * width * height  # data一共有60000*28*28个像素值  
    bitsString = '>' + str(bits) + 'B'  # fmt格式：'>47040000B'  
  
    imgs = struct.unpack_from(bitsString, buffers, offset) # 取data数据，返回一个元组  
  
    binfile.close()  
    imgs = np.reshape(imgs, [imgNum, width * height]) # reshape为[60000,784]型数组  
  
    return imgs