做cs231n时候的作业上使用到的机器学习分类数据集。 国内下载速度巨慢，而且还需要使用linux系统才能运行那个脚本，因此直接贴在CSDN上。 The CIFAR-10 and CIFAR-100 are labeled subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The CIFAR-10 dataset The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain more images from one class than another. Between them, the training batches contain exactly 5000 images from each class.

cifar-10数据集,里面有5个data_batch和一个test_batch,共60000张。

cifar数据集，适合python开发，亲测，

cifar100 pyhon版本的数据集，文件夹里添加加一个load_data.py代码，用于演示如何提取所需100数据集文件,有兴趣的可以下载使用

CIFAR-10 60000张 32X32 彩色图像 10类，50000张训练，10000张测试，包含标签，直接使用 方便快捷下载

cifar10.mat，包含batches.meta.mat，data_batch_1~5.mat，基test_batch