HQ-Edit-data-demo

# Dataset Card for HQ-EDIT

<!-- Provide a quick summary of the dataset. -->

HQ-Edit, a high-quality instruction-based image editing dataset with total 197,350 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline leveraging advanced foundation models, namely GPT-4V and DALL-E 3.
HQ-Edit’s high-resolution images, rich in detail and accompanied by comprehensive editing prompts, substantially enhance the capabilities of existing image editing models.

- **Homepage:** https://thefllood.github.io/HQEdit_web/
- **Repository:** https://github.com/UCSC-VLAA/HQ-Edit

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

"input" (str): description of input image.

"input_image" (image): the input image.

"edit" (str): edit instruction for transforming input images to output images.

"inverse_edit" (str): inverse-edit instructions for transforming output images back to input images.

"output" (str): description of output image.

"output_image" (image): the output image.

## Citation

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
If you find this dataset useful, please consider citing our paper:

```
@article{hui2024hq,
title = {HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing},
author = {Hui, Mude and Yang, Siwei and Zhao, Bingchen and Shi, Yichun and Wang, Heng and Wang, Peng and Zhou, Yuyin and Xie, Cihang},
journal = {arXiv preprint arXiv:2404.09990},
year = {2024}
}
```

# HQ-EDIT 数据集卡片

<!-- 提供数据集的简要概述。 -->

HQ-Edit是一个高质量的基于指令的图像编辑数据集，总计包含197,350条编辑样本。与此前依赖属性引导或人工反馈构建数据集的方法不同，我们设计了一套可扩展的数据收集流程，借助先进的基础模型（foundation models）GPT-4V与DALL-E 3完成数据采集。
HQ-Edit数据集包含高分辨率、细节丰富的图像，并配套有详尽的编辑指令，可显著提升现有图像编辑模型的性能。

- **项目主页：** https://thefllood.github.io/HQEdit_web/
- **代码仓库：** https://github.com/UCSC-VLAA/HQ-Edit

## 数据集结构

<!-- 本节将对数据集字段进行说明，并补充介绍数据集划分依据、样本间关联关系等数据集结构相关信息。 -->

`input` (str): 输入图像的描述文本。

`input_image` (image): 输入图像文件。

`edit` (str): 用于将输入图像转换为输出图像的编辑指令。

`inverse_edit` (str): 用于将输出图像还原为输入图像的反向编辑指令。

`output` (str): 输出图像的描述文本。

`output_image` (image): 输出图像文件。

## 引用说明

<!-- 若该数据集配有介绍论文或博客文章，请在此处提供其APA与Bibtex引用信息。 -->

若您认为本数据集对您的研究有所帮助，请引用我们的论文：

@article{hui2024hq,
title = {HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing},
author = {Hui, Mude and Yang, Siwei and Zhao, Bingchen and Shi, Yichun and Wang, Heng and Wang, Peng and Zhou, Yuyin and Xie, Cihang},
journal = {arXiv preprint arXiv:2404.09990},
year = {2024}
}