Datasets:

Modalities:
Image
ArXiv:
License:
FakeImageDataset / README.md
whlzy's picture
Update README.md
4a89f9b
|
raw
history blame
5.18 kB
---
license: apache-2.0
---
# Fake Image Dataset
Fake Image Dataset is now open-sourced at [huggingface (InfImagine Organization)](https://huggingface.co/datasets/InfImagine/FakeImageDataset/tree/main/ImageData/train). ↗ It consists of two folders, *ImageData* and *MetaData*. *ImageData* contains the compressed packages of the Fake Image Dataset, while *MetaData* contains the labeling information of the corresponding data indicating whether they are real or fake.
Sentry-Image is now open-sourced at [Sentry-Image (github repository)](https://github.com/Inf-imagine/Sentry) which provides the SOTA fake image detection models in [Sentry-Image Leaderboard](http://sentry.infimagine.com/) pretraining in [Fake Image Dataset](https://huggingface.co/datasets/InfImagine/FakeImageDataset/tree/main/ImageData/train) to detect whether the image provided is an AI-generated or real image.
## Why we need [Fake Image Dataset](https://huggingface.co/datasets/InfImagine/FakeImageDataset/tree/main/ImageData/train) and [Sentry-Image](http://sentry.infimagine.com/)?
* 🧐 Recent [study](https://arxiv.org/abs/2304.13023) have shown that humans struggle significantly to distinguish real photos from AI-generated ones, with a misclassification rate of **38.7%**.
* 🤗 To help people confirm whether the images they see are real images or AI-generated images, we launched the Sentry-Image project.
* 💻 Sentry-Image is an open source project which provides the SOTA fake image detection models in [Sentry-Image Leaderboard](http://sentry.infimagine.com/) to detect whether the image provided is an AI-generated or real image.
# Dataset card for Fake Image Dataset
## Dataset Description
* **Homepage:** [Sentry-Image](http://sentry.infimagine.com/)
* **Paper:** [https://arxiv.org/pdf/2304.13023.pdf](https://arxiv.org/pdf/2304.13023.pdf)
* **Point of Contact:** [contact@infimagine.com](mailto:contact@infimagine.com)
## How to Download
You can use following codes to download the dataset:
```shell
git lfs install
git clone https://huggingface.co/datasets/InfImagine/FakeImageDataset
```
You can use following codes to extract the files in each subfolder (take the *SDv15R-CC1M* subfolder in ImageData/train/SDv15R-CC1M as an example):
```shell
cat SDv15R-CC1M.tar.gz.* > SDv15R-CC1M.tar.gz
tar -xvf SDv15R-CC1M.tar.gz
```
## Dataset Summary
FakeImageDataset was created to serve as an large-scale dataset for the pretraining of detecting fake images.
It was built on StableDiffusion v1.5, IF and StyleGAN3.
## Supported Tasks and Leaderboards
FakeImageDataset is intended to be primarly used as a pretraining dataset for detecting fake images.
## Sub Dataset
### Fake2M Dataset
| Dataset | SD-V1.5Real-dpms-25 | IF-V1.0-dpms++-25 | StyleGAN3 |
| ----------- | :-----------: | :-----------: | :-----------: |
| Generator | Diffusion | Diffusion | GAN |
| Numbers | 1M | 1M | 87K |
| Resolution | 512 | 256 | (>=512) |
| Caption | CC3M-Train | CC3M-Train | - |
| ImageData Path | ImageData/train/SDv15R-CC1M | ImageData/train/IF-CC1M | ImageData/train/stylegan3-80K |
| MetaData Path | MetaData/train/SDv15R-CC1M.csv | MetaData/train/IF-CC1M.csv | MetaData/train/stylegan3-80K.csv |
# News
* [2023/07] We open source the [Sentry-Image repository](https://github.com/Inf-imagine/Sentry) and [Sentry-Image Demo & Leaderboard](http://sentry.infimagine.com/).
* [2023/07] We open source the [Sentry-Image dataset](https://huggingface.co/datasets/InfImagine/FakeImageDataset).
Stay tuned for this project! Feel free to contact [contact@infimagine.com](contact@infimagine.com)! 😆
# License
This project is open-sourced under the [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0). These weights and datasets are fully open for academic research and can be used for commercial purposes with official written permission. If you find our open-source models and datasets useful for your business, we welcome your donation to support the development of the next-generation Sentry-Image model. Please contact [contact@infimagine.com](contact@infimagine.com) for commercial licensing and donation inquiries.
# Citation
The code and model in this repository is mostly developed for or derived from the paper below. Please cite it if you find the repository helpful.
```
@misc{sentry-image-leaderboard,
title = {Sentry-Image Leaderboard},
author = {Zeyu Lu, Di Huang, Chunli Zhang, Chengyue Wu, Xihui Liu, Lei Bai, Wanli Ouyang},
year = {2023},
publisher = {InfImagine, Shanghai AI Laboratory},
howpublished = "\url{https://github.com/Inf-imagine/Sentry}"
},
@misc{lu2023seeing,
title = {Seeing is not always believing: Benchmarking Human and Model Perception of AI-Generated Images},
author = {Zeyu Lu, Di Huang, Lei Bai, Jingjing Qu, Chengyue Wu, Xihui Liu, Wanli Ouyang},
year = {2023},
eprint = {2304.13023},
archivePrefix = {arXiv},
primaryClass = {cs.AI}
}
```