AIS-4SD

AIS-4SD (AI Summit - 4 Stable Diffusion models) is a collection of 4.000 images, generated using a set of Stability AI text-to-image diffusion models

Context

This dataset was developed during the development of a collaborative project between PEReN and VIGINUM for the AI Summit held in Paris in February 2025. This open-source project aims at assessing generated images detectors performances and their robustness to different models and transformations. The code is free and open source, and contributions to connect additional detectors are also welcome.

Official repository: https://code.peren.gouv.fr/open-source/ai-action-summit/generated-image-detection.

Dataset summary

This dataset can be used to assess detection models performances, and in particular their robustness to successive updates of the generation model. 

Dataset description

1.000 generated images with four different versions of stability AI text-to-image diffusion model.

For each models, we generated:

• 500 portraits (👨) using SFHQ-T2I "random" prompts for faces (see Github repo, and dataset on Kaggle),
• 500 more general content images (🖼️) using captions of Google's Conceptual Captions dataset.

Reproducibility

The scripts used to generated these images can be found on our open-source repository (see this specific file). After setting-up our project, you can run:

$ poetry run python scripts/generate_images.py

With minor updates to these scripts you can enrich this dataset with your specific needs.

Dataset structure

One zip file with the following structure, each directory containing the associated 500 images:

AIS-4SD/
├── generation_metadata.csv
├── StableDiffusion-2.1-faces-20250203-1448
├── StableDiffusion-2.1-other-20250203-1548
├── StableDiffusion-3.5-faces-20250203-1012
├── StableDiffusion-3.5-other-20250203-1603
├── StableDiffusion-3-faces-20250203-1545
├── StableDiffusion-3-other-20250203-1433
├── StableDiffusion-XL-faces-20250203-0924
└── StableDiffusion-XL-other-20250203-1727

The metadata for generated images (see generation_metadata.csv) are:

• model: model used for generation,
• prompt: prompt used for generation (ie Conceptual Captions caption or sfhqt2i prompt, with some minor prompt engineering),
• guidance_scale: guidance scale of diffusion process,
• num_inference_steps: number of inference steps of diffusion process,
• generated_img_relative_path: relative path to image in zip structure.

Project status

Project is under ongoing development. A preliminary blog post can be found here: https://www.peren.gouv.fr/en/perenlab/2025-02-11_ai_summit/.