用python将[CIFAR-10]数据集转换为图片格式_pytorch cifar10数据集保存为图片-优快云博客

本文介绍如何使用Python将CIFAR-10数据集转换为图片格式，包括从数据集中读取信息，转换像素数据，并保存为图片文件的过程。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

用python将[CIFAR-10]数据集转换为图片格式

cifar10数据集下载：http://www.cs.toronto.edu/~kriz/cifar.html

代码

import numpy as np
import pickle as pkl
import imageio
 
#将cifar10数据转化为图片+标签格式

#定义反序列函数
def unpickle(file):
    fo = open(file, 'rb')
    dict = pkl.load(fo,encoding='bytes') #以二进制的方式加载
    fo.close()
    return dict
 
#转换train数据集
for j in range(1, 6):
    dataName = "G:/dataset/cifar-10-batches-py/data_batch_" + str(j)
    Xtr = unpickle(dataName)
    print (dataName + " is loading...")
 
    for i in range(0, 10000):
        img = np.reshape(Xtr[b'data'][i], (3, 32, 32))
        img = img.transpose(1, 2, 0)
        picName = 'G:/dataset/cifar-10-batches-py/data_batch_/train/' + str(Xtr[b'labels'][i]) + '/' + str(i + (j - 1)*10000) + '.jpg'
        imageio.imwrite(picName, img)
    print(dataName + " loaded.")
 
print ("test_batch is loading...")
 
#转换test数据集
testXtr = unpickle("G:/dataset/cifar-10-batches-py/test_batch")
for i in range(0, 10000):
    img = np.reshape(testXtr[b'data'][i], (3, 32, 32))
    img = img.transpose(1, 2, 0)
    picName = 'G:/dataset/cifar-10-batches-py//data_batch_test/' + str(testXtr[b'labels'][i]) + '_' + str(i) + '.jpg'
    imageio.imwrite(picName, img)
print ("test_batch loaded.")