Datasets:
tags:
- danbooru
- e621
- furry
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data/*.parquet
A highly condensed, diversity-maximized image dataset distilled from booru-style image boards. The original version used 2024 tag definition and is captioned with old outdated captioners.
RicemanT updated the tag definition to July/August 2026 and most importantly:
Tagged additional tags using the https://huggingface.co/animetimm/convnextv2_huge.dbv4-full model for Danbooru, and https://huggingface.co/RedRocket/Hydra for E621.
Recaptioned the whole thing with the current best vision captioner available Gemini 3.7 Flash while using Grok 4.6 and Qwen 3.8 27B as good backups for NSFW refusals.
Unlike the original dataset, the artist trigger tag format was changed from by artistname to Drawn by artistname. This is my personal preference for my own training projects, you can use scripts to change the prepend format to your liking.
The images can be obtained here RicemanT/booru-essence-2026-tars
This repo also contain the CSV files listing all characters and artists tag present within the dataset, and their count.
The cost of this whole operation on my own pocket was around 70 dollars, but actual usage if considering free vertex credits would be 400-450 dollars ;-;
Overview
A dataset of ~41,685 images, curated through a maximum variance selection strategy. Rather than collecting images in bulk, each image was chosen to contribute unique tag coverage — ensuring that all 74,000+ booru tags have at least one representative image in the dataset. The result is a dense, high-signal dataset where every sample carries informational weight.
Key Properties
| Property | Value | Value | Value |
|---|---|---|---|
| Total images | ~41,000 | ||
| Unique booru tags covered | 74,000+ | ||
| Captioned by | Gemini 3.7 Flash (~37,000 images) | Grok 4.6 (~4,000 images) | Qwen 3.8 27B FP8 (296 images) |
| Selection strategy | Maximum variance (diversity-maximized) |
Curation Methodology
The dataset was built around a coverage-first principle:
- Every one of the 74K booru tags is represented by at least one image
- Images were selected to maximize diversity across the tag space, avoiding redundancy
- The goal was the smallest possible dataset that still spans the full breadth of booru tag semantics This makes Booru Essence well-suited for tasks where tag coverage and concept diversity matter more than raw volume.
Intended Use
- Research on furry & anime/illustration style recognition and diffusion training
- Tag classification and multi-label learning
- Concept coverage benchmarking
- Low-resource or compute-efficient training scenarios
License
This dataset is released under CC BY-NC-SA 4.0.
But how do you licence a computer-generated dataset?