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Ethanliang99
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Model Details
Model Provider
Ethanliang99
Model Tree
Qwen/Qwen2.5-VL-7B-Instruct
Input Modalities
Output Modalities
Supported Functionality
Use the companion Zoom-IQA evaluator, which implements the prompts, crop routing, parsing, and evaluation metrics used by the model. In its Transformers environment, run:
bash
zoomiqa-score \--model-path /path/to/Zoom-IQA-7B \--image /path/to/your_image.jpg \--device 0
For benchmark evaluation, use zoomiqa-eval; a separate
zoomiqa-eval-vllm entrypoint is available for faster inference. See the code
repository for installation, annotation format, Python usage, and complete
command-line options.
The bundled generation_config.json is checkpoint metadata. The official
evaluator supplies its protocol settings explicitly.
Outputs are sampled and may occasionally be malformed. Results can change with different prompts, decoding settings, preprocessing, or runtime versions. The model is intended for image-quality research, not high-stakes decisions.
Released under the Apache License 2.0. Benchmark images and GR-IQA source images retain their original licenses.
bibtex
@article{liang2026zoomiqa,title={Zoom-IQA: Image Quality Assessment with Reliable Region-Aware Reasoning},author={Liang, Guoqiang and Wang, Jianyi and Wu, Zhonghua and Zhou, Shangchen and Loy, Chen Change},journal={arXiv preprint arXiv:2601.02918},year={2026}}