timlawrenz/prx-tg-training-data
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Tim Lawrenz PRO
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Introducing Stratum-FFHQ: A Multi-Modal Enriched Face Dataset liked a dataset 1 day ago
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Introducing Stratum-FFHQ: A Multi-Modal Enriched Face Dataset
High-quality datasets are the lifeblood of modern generative AI, but raw pixels alone are no longer enough. To train advanced diffusion models, ControlNets, and multi-modal systems, you need rich, aligned contextual data for every single image.
Today, we are excited to release Stratum-FFHQ—an enriched, dataset-agnostic pipeline transformation of the renowned Flickr-Faces-HQ (FFHQ) dataset.
Instead of just providing high-resolution RGB images, Stratum-FFHQ delivers a complete multi-modal artifact payload for every image, including dense captions, DINOv3 semantic embeddings, T5 text encodings, and Sapiens-derived spatial maps (depth, normals, and segmentation).
https://huggingface.co/datasets/timlawrenz/stratum-ffhqOrganizations
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Introducing Stratum-FFHQ: A Multi-Modal Enriched Face Dataset
High-quality datasets are the lifeblood of modern generative AI, but raw pixels alone are no longer enough. To train advanced diffusion models, ControlNets, and multi-modal systems, you need rich, aligned contextual data for every single image.
Today, we are excited to release Stratum-FFHQ—an enriched, dataset-agnostic pipeline transformation of the renowned Flickr-Faces-HQ (FFHQ) dataset.
Instead of just providing high-resolution RGB images, Stratum-FFHQ delivers a complete multi-modal artifact payload for every image, including dense captions, DINOv3 semantic embeddings, T5 text encodings, and Sapiens-derived spatial maps (depth, normals, and segmentation).
timlawrenz/stratum-ffhq
High-quality datasets are the lifeblood of modern generative AI, but raw pixels alone are no longer enough. To train advanced diffusion models, ControlNets, and multi-modal systems, you need rich, aligned contextual data for every single image.
Today, we are excited to release Stratum-FFHQ—an enriched, dataset-agnostic pipeline transformation of the renowned Flickr-Faces-HQ (FFHQ) dataset.
Instead of just providing high-resolution RGB images, Stratum-FFHQ delivers a complete multi-modal artifact payload for every image, including dense captions, DINOv3 semantic embeddings, T5 text encodings, and Sapiens-derived spatial maps (depth, normals, and segmentation).
timlawrenz/stratum-ffhq
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