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GPTTrace image v2 training data

Training data for GPTTrace's AI-generated image detectors. Everything here comes from permissively licensed sources or was generated by us from CC0 photos. Each part keeps its source licence; check the source before reuse.

All files are parquet shards with these columns: id, src, gen, kind, label, w, h, jpeg, image. The image column holds the original bytes.

Folder / prefix Content Source Licence
vae/vae-* Real photos round-tripped through open autoencoders. Six VAEs: SD, SDXL, FLUX.1-style, FLUX.2, Qwen-Image, Sana. Also includes partial "local" edits. The JPEG settings match each real twin. bitmind/megalith-small photos (CC0); our generation CC0
ext/dragon-* 25 diffusion models lesc-unifi/dragon CC BY-SA 4.0
ext/elsa-* SD-family elsaEU/ELSA1M_track1 CC BY 4.0
ext/oip-* FLUX-dev, SD3.5 Large data-is-better-together/open-image-preferences-v1 Apache-2.0
ext/nano-* Gemini 2.5 Flash Image bitmind/nano-banana MIT
ext/gpt4o-* GPT-4o image FreedomIntelligence/ShareGPT-4o-Image Apache-2.0
ext/ddb-* SD 1.x poloclub/diffusiondb CC0
ext/rapid-* Generators from 2023 to 2026, sampled evenly per model Rapidata/text-to-image-human-preference-6M CC BY 4.0
t2i/* Z-Image-Turbo, FLUX.2-klein, Sana generations our generation (Apache-2.0 models) CC0

Attribution: thanks to the creators of the datasets above. Rapidata data © Rapidata, CC BY 4.0. DRAGON © the DRAGON authors, CC BY-SA 4.0. ELSA © the ELSA project, CC BY 4.0.

No benchmark or evaluation data is included. Benchmark images and near-duplicates of them are excluded from training (see dedupe/).

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