Update README.md

README.md

@@ -1,4 +1,16 @@
-# danbooru-artists-10k
+---
+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.
@@ -7,5 +19,4 @@ This dataset contains images from 10,000 artists collected from Danbooru. The im
 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`.
-
+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`.