Datasets:
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README.md
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This dataset can be used to assess detection models performances, and in particular their robustness to successive updates of the generation model.
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### Dataset description
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1.000 generated images with four different versions of stability AI text-to-image diffusion model.
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For each models, we generated:
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- 500 portraits (👨) using SFHQ-T2I "random" prompts for faces (see Github repo, and dataset on Kaggle),
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- 500 more general content images (🖼️) using captions of Google's Conceptual Captions dataset.
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| Model | Number of images |
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|:-----------------------------------------------:|:----------------:|
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| stabilityai/stable-diffusion-xl-base-1.0 | 500 👨 + 500 🖼️ |
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| stabilityai/stable-diffusion-2-1 | 500 👨 + 500 🖼️ |
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| stabilityai/stable-diffusion-3-medium-diffusers | 500 👨 + 500 🖼️ |
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| stabilityai/stable-diffusion-3.5-large | 500 👨 + 500 🖼️ |
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### Reproducibility
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└── StableDiffusion-XL-other-20250203-1727
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```
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The metadata for generated images
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- `model`: model used for generation,
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- `prompt`: prompt used for generation (ie Conceptual Captions caption or sfhqt2i prompt, with some minor prompt engineering),
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- `guidance_scale`: guidance scale of diffusion process,
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- `num_inference_steps`: number of inference steps of diffusion process
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- `generated_img_relative_path`: relative path to image in zip structure.
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## Project status
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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/.
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This dataset can be used to assess detection models performances, and in particular their robustness to successive updates of the generation model.
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YOu can also find this dataset on [Zenodo](https://zenodo.org/records/15131117)
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### Dataset description
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1.000 generated images with four different versions of stability AI text-to-image diffusion model.
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For each models, we generated:
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- 500 portraits (👨) using SFHQ-T2I "random" prompts for faces (see [Github repo](https://github.com/SelfishGene/SFHQ-T2I-dataset), and [dataset on Kaggle](https://www.kaggle.com/datasets/selfishgene/sfhq-t2i-synthetic-faces-from-text-2-image-models)),
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- 500 more general content images (🖼️) using captions of Google's [Conceptual Captions](https://ai.google.com/research/ConceptualCaptions) dataset.
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| Model | Number of images |
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|:-----------------------------------------------:|:----------------:|
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| [stabilityai/stable-diffusion-xl-base-1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) | 500 👨 + 500 🖼️ |
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| [stabilityai/stable-diffusion-2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1) | 500 👨 + 500 🖼️ |
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| [stabilityai/stable-diffusion-3-medium-diffusers](https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers) | 500 👨 + 500 🖼️ |
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| [stabilityai/stable-diffusion-3.5-large](https://huggingface.co/stabilityai/stable-diffusion-3.5-large) | 500 👨 + 500 🖼️ |
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### Reproducibility
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└── StableDiffusion-XL-other-20250203-1727
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```
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The metadata for generated images are:
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- `model`: model used for generation,
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- `prompt`: prompt used for generation (ie Conceptual Captions caption or sfhqt2i prompt, with some minor prompt engineering),
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- `guidance_scale`: guidance scale of diffusion process,
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- `num_inference_steps`: number of inference steps of diffusion process.
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## Project status
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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/](https://www.peren.gouv.fr/en/perenlab/2025-02-11_ai_summit/).
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