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license: cc-by-nc-sa-4.0 |
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--- |
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# Model Description |
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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 |
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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 |
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The weights included in this repository come from two sources: |
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1. Models trained and validated by our team |
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2. Official weights collected from original model repositories |
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## Usage |
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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 |
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- Part of the weights are trained by us, while others are collected from official repositories |
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- While we strive for accuracy, performance is not guaranteed to exactly match original paper results |
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- Users should verify model performance for their specific use cases |
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- Please respect the original licenses and cite the appropriate papers when using these weights |
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## Citation |
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If you use these weights in your research, please cite our repository and the original papers for the respective models. |
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``` |
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@misc{pyiqa, |
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title={{IQA-PyTorch}: PyTorch Toolbox for Image Quality Assessment}, |
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author={Chaofeng Chen and Jiadi Mo}, |
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year={2022}, |
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howpublished = "[Online]. Available: \url{https://github.com/chaofengc/IQA-PyTorch}" |
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} |
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``` |
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