---
license: cc-by-nc-sa-4.0
task_categories:
- zero-shot-image-classification
- image-classification
tags:
- art
- not-for-all-audiences
pretty_name: Danbooru Artists 10k
size_categories:
- 100K<n<1M
---
# Danbooru Artists 10k

## Dataset Summary
This dataset contains images from 10,000 artists collected from Danbooru. The images are primarily sourced from a mirror [here](https://huggingface.co/datasets/KBlueLeaf/danbooru2023-webp-4Mpixel). However, there are six images that are missing/broken in this mirror, which have been directly sourced from Danbooru. Each artist is represented by 30 images. This dataset is intended for use in metric learning or fine-grained classification tasks related to art styles. The artists are split into train, validation, and test sets at a ratio of 80%, 10%, and 10%, respectively. Similarly, each artist's 30 images are also split into train, validation, and test sets at the same ratio.

## Size
300,000 images (10,000 artists * 30 images/artist)

## Format
The images are stored as WebP files packaged in `a10k.zip`. The dataset splits are provided in `split.txt`. Each line of `split.txt` follows this format: `artist_split image_split artist_name file_path`.