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lint/anybooru

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Hugging Face2023-03-03 更新2024-03-04 收录
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https://hf-mirror.com/datasets/lint/anybooru
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资源简介:
--- license: openrail --- # Anybooru ## Synthetic Anime Image Dataset Synthetic anime image dataset generated using Andite's Anything-v4.5 checkpoint with Danbooru2021 tags collected in https://gwern.net/danbooru2021. See https://github.com/1lint/anybooru for details and code to generate your own variant of the dataset. I have also uploaded the extracted Danbooru2021 tags to https://huggingface.co/datasets/lint/danbooru_tags, this dataset was generated with a small subset of the tags in `2021_0_pruned.parquet`. Each string of tags was used to generate 4 different images with different seeds. This serves a similar purpose as random resize crop and image flip transformations to train the model to focus on general concepts encoded in the tags, rather than memorizing specific images. ## Quick Start ``` from datasets import load_dataset dataset = load_dataset('lint/anybooru') sample = dataset['train'][0] image = sample['image'] tags = image.info['tags'] print(tags) ``` ## Samples Each row of samples share the same generation prompt (string of tags). ![](./anybooru_grid.png) ## Citations ``` @misc{danbooru2021, author = {Anonymous and Danbooru community and Gwern Branwen}, title = {Danbooru2021: A Large-Scale Crowdsourced and Tagged Anime Illustration Dataset}, howpublished = {\url{https://gwern.net/danbooru2021}}, url = {https://gwern.net/danbooru2021}, type = {dataset}, year = {2022}, month = {January}, timestamp = {2022-01-21}, note = {Accessed: 03/01/2023} } ```
提供机构:
lint
原始信息汇总

Anybooru 合成动漫图像数据集概述

数据集描述

数据集特性

  • 图像生成:每个标签字符串生成4张不同种子下的图像。
  • 训练目的:通过不同图像训练模型关注标签中的通用概念,而非特定图像。

使用方法

  • 加载数据集:使用datasets库加载数据集。
  • 示例代码: python from datasets import load_dataset dataset = load_dataset(lint/anybooru) sample = dataset[train][0] image = sample[image] tags = image.info[tags] print(tags)

样本展示

  • 样本结构:每行样本共享相同的生成提示(标签字符串)。
  • 样本图像:展示于./anybooru_grid.png

引用信息

  • 引用格式

    @misc{danbooru2021, author = {Anonymous and Danbooru community and Gwern Branwen}, title = {Danbooru2021: A Large-Scale Crowdsourced and Tagged Anime Illustration Dataset}, howpublished = {url{https://gwern.net/danbooru2021}}, url = {https://gwern.net/danbooru2021}, type = {dataset}, year = {2022}, month = {January}, timestamp = {2022-01-21}, note = {Accessed: 03/01/2023} }

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