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Author:
None
License:
BSD 3-Clause License
Copyright (c) 2026, MSU Graphics & Media Lab
Redistribution and use in source and binary forms, with or without
modification, are permitt...
Summary:
A toolkit for extracting IQA features, training regressors, and analyzing super-resolution image quality against human scores.
Latest version:
0.1.7
Required dependencies:
huggingface-hub
|
matplotlib
|
numpy
|
pandas
|
pillow
|
scikit-learn
|
scipy
|
tqdm
Optional dependencies:
build
|
catboost
|
check-manifest
|
icecream
|
ipykernel
|
jupyter
|
lightgbm
|
pyiqa
|
pytest
|
ruff
|
shap
|
timm
|
torch
|
torchvision
|
transformers
|
twine
|
xgboost
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