---
license: cc-by-nc-sa-4.0
---

# Model Description
This repo contains model weights used in [IQA-PyTorch](https://github.com/chaofengc/IQA-PyTorch), a collection of Image Quality Assessment algorithms implemented in PyTorch.

## Overview
The weights provided here support various IQA models and metrics, enabling assessment of both full-reference and no-reference image quality evaluation tasks.

## Model Weights
The weights included in this repository come from two sources:
1. Models trained and validated by our team
2. Official weights collected from original model repositories

## Usage
Please refer to the [IQA-PyTorch](https://github.com/chaofengc/IQA-PyTorch) documentation for detailed instructions on how to use these weights with the corresponding models.

## Disclaimer
- Part of the weights are trained by us, while others are collected from official repositories
- While we strive for accuracy, performance is not guaranteed to exactly match original paper results
- Users should verify model performance for their specific use cases
- Please respect the original licenses and cite the appropriate papers when using these weights

## Citation
If you use these weights in your research, please cite our repository and the original papers for the respective models.
```
@misc{pyiqa,
  title={{IQA-PyTorch}: PyTorch Toolbox for Image Quality Assessment},
  author={Chaofeng Chen and Jiadi Mo},
  year={2022},
  howpublished = "[Online]. Available: \url{https://github.com/chaofengc/IQA-PyTorch}"
}
```