This data set is the CIFAR-10 data set formatted for use with the NeuNetS tool. For images, NeuNetS requires that all of the images be in one file named "train.zip" and all the labels in a file named "labels.csv", with each line in labels.csv in the following format:
<file-name>,<class-name>

The zip file contains the following two files:

• train.zip
• labels.csv

The CIFAR-10 data set is a labeled subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton.

The CIFAR-10 data set is a .gz file which consists of 60000 32x32 colour images in 10 classes, with 6000 images per class.

The classes in the data set are: airplane, automobile, bird, cat, deer, dog, frog, horse, ship and truck.

For more details or for Matlab and binary versions of the data sets, see: https://www.cs.toronto.edu/%7Ekriz/cifar.html

Reference
This tech report (Chapter 3) describes the data set and the methodology followed when collecting it in much greater detail. Please cite this report when using this data set: Learning Multiple Layers of Features from Tiny Images, Alex Krizhevsky, 2009.