Dataset
Danbooru2026 is a large-scale anime illustration dataset containing over 10 million community-annotated images. It is intended for research and development in anime-style image generation, image classification, multimodal learning, and related tasks.
Danbooru is a long-running image board known for its extensive tagging system and community-maintained metadata.
Key Specifications:
This dataset builds upon danbooru2023 and expands the collection by more than 4.5 million images.
Danbooru2026 contains images only. Non-image files, animations, videos, audio files, archives, documents, and other unsupported media are excluded.
All included images are:
For an image with width (W) and height (H), resizing is applied only when:
W × H > 4096 × 4096
The dataset is designed to be straightforward to use, avoiding obscure storage formats while supporting efficient downloading, local access, research, and torrent seeding.
Images are stored as WebP files and distributed across 1,000 zero-padded buckets named 0000 through 0999. The bucket for each image is determined by the Danbooru post ID modulo 1,000.
For example:
BUCKET=$(printf "%04d" $((ID % 1000)))
The corresponding image path is:
original/$BUCKET/$ID.webp
An image with post ID 210001 is therefore stored at:
original/0001/210001.webp
/
└── danbooru2026/
├── README.md
├── metadata/
│ ├── posts.parquet
│ └── ...
└── original/
├── 0000/ -> data-0000.tar
├── 0001/ -> data-0001.tar
│ ├── 10001.webp
│ ├── 210001.webp
│ └── ...
└── ... (up to 0999)
The processed dataset does not preserve the original source file formats. Every successfully decoded item is provided as a WebP image with a maximum resolution of 4 megapixels.
Files that cannot be safely decoded as images are excluded from the processed image collection. This includes corrupted files, incorrectly labeled non-image files, unsupported media, and other invalid source data.