---
license: mit
task_categories:
- image-classification
size_categories:
- 10K<n<100K
---

# Dataset Card for CIFAKE_autotrain_compatible

## Dataset Description

- **Homepage:** [Kaggle data card](https://www.kaggle.com/datasets/birdy654/cifake-real-and-ai-generated-synthetic-images?resource=download)
- **Paper:** Krizhevsky, A., & Hinton, G. (2009). Learning multiple layers of features from tiny images.

### Dataset Summary

This is a copy of the CIFAKE dataset created by Dr Jordan J. Bird and Professor Ahmad Lotfi. See more information on the original data card on [Kaggle](https://www.kaggle.com/datasets/birdy654/cifake-real-and-ai-generated-synthetic-images?resource=download).

The real images used are from CIFAR-10. The fake images were created by the authors using Stable Diffusion v1.4.

This dataset removes the train/test structures in the original dataset to allow compatibility with HuggingFace's AutoTrain. It removes the test split images from the original dataset in both categories. All training images remain.

## Dataset Structure

### Data Fields

Contains 100k total images per splits below.

### Data Splits
Real: 50k real images

Fake: 50k AI generated images

## Additional Information

### Dataset Curators
Dr Jordan J. Bird

Professor Ahmad Lotfi

### Licensing Information

This dataset is published under the [same MIT license as CIFAR-10](https://github.com/wichtounet/cifar-10/blob/master/LICENSE):

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

### Citation Information

If you use this dataset, you must cite the following sources:

[Krizhevsky, A., & Hinton, G. (2009). Learning multiple layers of features from tiny images.](https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdfl)

[Bird, J.J., Lotfi, A. (2023). CIFAKE: Image Classification and Explainable Identification of AI-Generated Synthetic Images. arXiv preprint arXiv:2303.14126.](https://arxiv.org/abs/2303.14126)

Real images are from Krizhevsky & Hinton (2009), fake images are from Bird & Lotfi (2023). The Bird & Lotfi study is a preprint currently available on ArXiv and this description will be updated when the paper is published.