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Official implementation for CVPR2023 Paper "Re-IQA : Unsupervised Learning for Image Quality Assessment in the Wild"

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Thanks for sharing your very interesting work! I have encountered an installation issue from requirements.txt: ``` ERROR: No matching distribution found for sklearn==1.1.3 ``` Changing sklearn==1.1.3 to scikit-learn==1.1.3, solved it....

Hi, thanks for your sharing of the code. I found the test_options.py in the current code, but I cannot find a test code with a trained model (only training code...

The process of determining "different-quality" after completing the swap between chunkc1 and chunkc2 is not very clear.

Is there any parameter setting information about the training of the regressors? I didn't get that good performance using a single-layer MLP regression score

Hi thank you for your work. I wonder if there is a model to get the final scores instead of the features? Thank you!