KBlueLeaf/danbooru2023-webp-4Mpixel

Danbooru 2023 webp: A space-efficient version of Danbooru 2023

This dataset is a resized/re-encoded version of danbooru2023.
Which removed the non-image/truncated files and resize all of them into smaller size.

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Details

This dataset employs few method to reduce the size and improve the efficiency.

Size and Format

This dataset resize all the image which have more than 2048x2048 pixel into near 2048x2048 pixels with bicubic algorithm.
And remove all the image with longer edge larger than 16383 after resize.
(one reason is beacuse webp doesn't allow that, another is that aspect ratio is too large/small.)

This dataset encode/save all the image with 90% quality webp with pillow library in Python. Which is half size of the 100% quality lossy webp.

The total size of this dataset is around 1.3~1.4TB. Which is less than the 20% of original file size.

Webdataset

This dataset use webdataset library to save all the tarfile, therefore, you can also use webdataset to load them easily. This is also a recommended way.

The __key__ of each files is the id of it. You can use this id to query the metadata database easily.

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Future work

I will open a repo on github for utilizing danbooru-webp and danbooru-sqlite datasets as a dataset exporter for fine-grained-image-task.
Since the original danbooru2023 actually doesn't have images published after 2023/11/20, and it may be updated in the future.
This dataset will be updated after original dataset is been updated. And maintain the same format.