---
title: SEAGULL
emoji: 📊
colorFrom: blue
colorTo: yellow
sdk: gradio
sdk_version: 5.7.0
app_file: app.py
pinned: false
---

<img src="https://github.com/chencn2020/SEAGULL/raw/main/imgs/Logo/logo.png" alt="SEAGULL" style="height: auto; width: 100%;">

<div style="display: flex; justify-content: center; gap: 10px; flex-wrap: wrap; width: 100%;">
  <a href=""><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Spaces" style="max-width: 100%; height: auto;"></a>
  <a href="https://arxiv.org/abs/2411.10161"><img src="https://img.shields.io/badge/Arxiv-2411:10161-red" style="max-width: 100%; height: auto;"></a>
  <a href="https://hits.seeyoufarm.com"><img src="https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FZevin2023%2FSEAGULL-100w&count_bg=%2379C83D&title_bg=%23555555&icon=&icon_color=%23E7E7E7&title=Visitors&edge_flat=false" style="max-width: 100%; height: auto;"></a>
  <a href='https://github.com/chencn2020/SEAGULL/'><img src='https://img.shields.io/github/stars/chencn2020/Seagull.svg?style=social' style="max-width: 100%; height: auto;"></a>
</div>

## Acknowledgement 💌
<div id="Acknowledgement"></div>
- [Osprey](https://github.com/CircleRadon/Osprey) and [LLaVA-v1.5](https://github.com/haotian-liu/LLaVA): We build this repostory based on them.
- [RAISE](http://loki.disi.unitn.it/RAISE/): The Dist. images in SEAGULL-100w are constructed based on this dataset.
- [SAM](https://segment-anything.com/) and [SEEM](https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once): The mask-based ROIs are generated using these two awesome works. And SAM are used to get the segmentation result in the demo.
- [TOPIQ](https://github.com/chaofengc/IQA-PyTorch): The quality scores and importance scores for ROIs are generated using this great FR-IQA.


## Citation 🖊️
If our work is useful to your research, we will be grateful for you to cite our paper:
```
@misc{chen2024seagull,
      title={SEAGULL: No-reference Image Quality Assessment for Regions of Interest via Vision-Language Instruction Tuning}, 
      author={Zewen Chen and Juan Wang and Wen Wang and Sunhan Xu and Hang Xiong and Yun Zeng and Jian Guo and Shuxun Wang and Chunfeng Yuan and Bing Li and Weiming Hu},
      year={2024},
      eprint={2411.10161},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2411.10161}, 
}
```