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