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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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- zero-shot-image-classification |
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- text-to-image |
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language: |
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- en |
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tags: |
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- art |
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- anime |
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- not-for-all-audiences |
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size_categories: |
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- 1M<n<10M |
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--- |
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# Danbooru 2023 webp: A space-efficient version of Danbooru 2023 |
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This dataset is a resized/re-encoded version of [danbooru2023](https://huggingface.co/datasets/nyanko7/danbooru2023).<br> |
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Which removed the non-image/truncated files and resize all of them into smaller size. |
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This dataset already be updated to latest_id = 7,832,883. |
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Thx to DeepGHS! |
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**Notice**: content of updates folder and deepghs/danbooru_newest-webp-4Mpixel have been merged to 2000~2999.tar, You can ignore all the content in updates folder safely! |
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## Details |
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This dataset employs few method to reduce the size and improve the efficiency. |
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### Size and Format |
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This dataset resize all the image which have more than 2048x2048 pixel into near 2048x2048 pixels with bicubic algorithm.<br> |
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And remove all the image with longer edge larger than 16383 after resize.<br> |
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(one reason is beacuse webp doesn't allow that, another is that aspect ratio is too large/small.) |
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This dataset encode/save all the image with 90% quality webp with pillow library in Python. |
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Which is half size of the 100% quality lossy webp. |
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The total size of this dataset is around 1.3~1.4TB. Which is less than the 20% of original file size. |
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### Webdataset |
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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. |
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The `__key__` of each files is the id of it. You can use this id to query the [metadata database](https://huggingface.co/datasets/KBlueLeaf/danbooru2023-sqlite) easily. |
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