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---
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license: mit
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---
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---
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license: mit
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task_categories:
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- image-classification
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- image-to-image
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- text-to-image
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language:
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- en
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- ja
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pretty_name: danbooru2023
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size_categories:
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- 1M<n<10M
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---
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# Yandere2023: A Large-Scale Crowdsourced and Tagged Anime Illustration Dataset
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<!-- Provide a quick summary of the dataset. -->
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Yandere2023 is a large-scale anime image dataset with over 5 million images contributed and annotated in detail by an enthusiast community. Image tags cover aspects like characters, scenes, copyrights, artists, etc with an average of 30 tags per image.
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Yandere is a veteran anime image board with high-quality images and extensive tag metadata. The dataset can be used to train image classification, multi-label tagging, character detection, generative models, and other computer vision tasks.
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- **Shared by:** Nyanko Devs
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- **Language(s):** English, Japanese
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- **License:** MIT
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## Uses
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## Format
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The goal of the dataset is to be as easy as possible to use immediately, avoiding obscure file formats, while allowing simultaneous research & seeding of the torrent, with easy updates.
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Images are provided in the full original form (be that JPG, PNG, GIF or otherwise) for reference/archival purposes, and bucketed into 1000 subdirectories 0000β0999 (0-padded), which is the Danbooru ID modulo 1000 (ie. all images in 0999/ have an ID ending in β999β); IDs can be turned into paths by dividing & padding (eg. in Bash, BUCKET=$(printf "%04d" $(( ID % 1000 )) )) and then the file is at {original,512px}/$BUCKET/$ID.$EXT.
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The reason for the bucketing is that a single directory would cause pathological filesystem performance, and modulo ID is a simple hash which spreads images evenly without requiring additional future directories to be made or a filesystem IO to check where the file is. The ID is not zero-padded and files end in the relevant extension, hence the file layout looks like this:
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```bash
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$ tree / | less
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/
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βββ yandere2023 -> /mnt/diffusionstorage/workspace/yandere/
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β βββ metadata
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β βββ readme.md
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β βββ original
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β β βββ 0000 -> data-0000.tar
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β β βββ 0001 -> data-0001.tar
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β β β βββ 10001.jpg
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β β β βββ 210001.png
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β β β βββ 3120001.webp
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β β β βββ 6513001.jpg
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```
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Currently represented file extensions are: avi/bmp/gif/html/jpeg/jpg/mp3/mp4/mpg/pdf/png/rar/swf/webm/wmv/zip.
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Raw original files are treacherous. Be careful if working with the original dataset. There are many odd files: truncated, non-sRGB colorspace, wrong file extensions (eg. some PNGs have .jpg extensions like original/0146/1525146.jpg or original/0558/1422558.jpg), etc.
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