【Python】将MNIST数据集转化为图片

本文为转载
原作者：Jimmy
原文地址：使用Python将MNIST数据集转化为图片

train datasets

import numpy as np  
import struct  

from PIL import Image  
import os  

data_file = 'somePath/train-images.idx3-ubyte' #需要修改的路径  
# It's 47040016B, but we should set to 47040000B  
data_file_size = 47040016  
data_file_size = str(data_file_size - 16) + 'B'  

data_buf = open(data_file, 'rb').read()  

magic, numImages, numRows, numColumns = struct.unpack_from(  
    '>IIII', data_buf, 0)  
datas = struct.unpack_from(  
    '>' + data_file_size, data_buf, struct.calcsize('>IIII'))  
datas = np.array(datas).astype(np.uint8).reshape(  
    numImages, 1, numRows, numColumns)  

label_file = 'somePath/train-labels.idx1-ubyte' #需要修改的路径  

# It's 60008B, but we should set to 60000B  
label_file_size = 60008  
label_file_size = str(label_file_size - 8) + 'B'  

label_buf = open(label_file, 'rb').read()  

magic, numLabels = struct.unpack_from('>II', label_buf, 0)  
labels = struct.unpack_from(  
    '>' + label_file_size, label_buf, struct.calcsize('>II'))  
labels = np.array(labels).astype(np.int64)  

datas_root = '/somePath/mnist_train' #需要修改的路径  
if not os.path.exists(datas_root):  
    os.mkdir(datas_root)  

for i in range(10):  
    file_name = datas_root + os.sep + str(i)  
    if not os.path.exists(file_name):  
        os.mkdir(file_name)  

for ii in range(numLabels):  
    img = Image.fromarray(datas[ii, 0, 0:28, 0:28])  
    label = labels[ii]  
    file_name = datas_root + os.sep + str(label) + os.sep + \  
        'mnist_train_' + str(ii) + '.png'  
    img.save(file_name)  

test datasets

import numpy as np  
import struct  

from PIL import Image  
import os  

data_file = 'somePath/t10k-images.idx3-ubyte' #需要修改的路径  

# It's 7840016B, but we should set to 7840000B  
data_file_size = 7840016  
data_file_size = str(data_file_size - 16) + 'B'  

data_buf = open(data_file, 'rb').read()  

magic, numImages, numRows, numColumns = struct.unpack_from(  
    '>IIII', data_buf, 0)  
datas = struct.unpack_from(  
    '>' + data_file_size, data_buf, struct.calcsize('>IIII'))  
datas = np.array(datas).astype(np.uint8).reshape(  
    numImages, 1, numRows, numColumns)  

label_file = 'somePath/t10k-labels.idx1-ubyte'#需要修改的路径  

# It's 10008B, but we should set to 10000B  
label_file_size = 10008  
label_file_size = str(label_file_size - 8) + 'B'  

label_buf = open(label_file, 'rb').read()  

magic, numLabels = struct.unpack_from('>II', label_buf, 0)  
labels = struct.unpack_from(  
    '>' + label_file_size, label_buf, struct.calcsize('>II'))  
labels = np.array(labels).astype(np.int64)  

datas_root = 'somePath/mnist_test' #需要修改的路径  

if not os.path.exists(datas_root):  
    os.mkdir(datas_root)  

for i in range(10):  
    file_name = datas_root + os.sep + str(i)  
    if not os.path.exists(file_name):  
        os.mkdir(file_name)  

for ii in range(numLabels):  
    img = Image.fromarray(datas[ii, 0, 0:28, 0:28])  
    label = labels[ii]  
    file_name = datas_root + os.sep + str(label) + os.sep + \  
        'mnist_test_' + str(ii) + '.png'  
    img.save(file_name)