---
license: mit
task_categories:
- image-feature-extraction
tags:
- anime
- pretrain
- ssl
- self-supervised
pretty_name: AnimePics
size_categories:
- 100M<n<1B
---

# AnimePics

This dataset is a pure image dataset in WebDataset format, designed for pre-training anime-style models. 
It can also be used to evaluate the effect of additional pre-training on backbones trained primarily on real-world images when applied to datasets of a completely different nature. 
The dataset is designed to be continuously updated, leveraging the features of WebDataset.

## Dataset Details

### Dataset Description

The `animepics` dataset is a large-scale, image-only dataset intended for unsupervised pre-training of models for anime-style image generation and analysis. 
All images are provided in the WebDataset format, allowing for efficient, sequential access to the data, 
which is particularly well-suited for large-scale training on cloud infrastructure.


- **Curated by:** `zenless-lab`
- **License:** `MIT`

### Dataset Sources [optional]

- **Repository:** [zenless-lab/animepics](https://huggingface.co/datasets/zenless-lab/animepics)
<!-- - **Paper [optional]:** [More Information Needed] -->
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## Uses

### Direct Use

This dataset is intended for pre-training computer vision models, particularly those that will be used for tasks involving anime-style images. 
It can also be used to research the effects of transfer learning from a distinctly different domain (anime) to models pre-trained on real-world images.

### Out-of-Scope Use

This dataset is not intended for any use that would violate the original licenses of the source datasets. 
The images are provided **AS-IS**, and may contain biases or content that is not suitable for all audiences.

## Dataset Structure

The dataset is structured in the WebDataset format. Each `.tar` file contains a collection of `.webp` images, with a maximum size of 1GB per `.tar` file. 
The key for each image (which also serves as its filename) is a UUID4(e.g. *bf8f5936-6b93-489f-9e07-01bbb7df8db7*), 
ensuring that there are no filename conflicts when new images are added. 
This structure allows for the dataset to be continuously and sustainably updated.

## Dataset Creation

### Curation Rationale

The motivation behind creating this dataset was to provide a large-scale, easily accessible, and continuously updated resource for pre-training models on anime-style images. 

### Source Data

#### Data Collection and Processing

The images in this dataset are sourced from other open datasets with permissive licenses that are compatible with the `MIT` license, allowing for redistribution.

The current data source is:

*   [nyanko7/danbooru2023](https://huggingface.co/datasets/nyanko7/danbooru2023)

All images have been pre-processed for efficient training on cloud infrastructure.
Images with a short side larger than 1024 pixels have been resized to have a short side of 1024 pixels while maintaining their original aspect ratio. 
All images have been converted to the `.webp` format.

The dataset currently contains **5,954,808** images, with a total size of **640GB**.