Measures and metrics for image2image tasks. PyTorch.
Collection of measures and metrics for automatic image quality assessment in various image-to-image tasks such as denoising, super-resolution, image generation etc. This easy to use yet flexible and extensive library is developed with focus on reliability and reproducibility of results. Use your favorite measures as losses for training neural networks with ready-to-use PyTorch modules.
Check out our GitHub repository for more information.
PyTorch Image Quality helps you to concentrate on your experiments without the boilerplate code. The library contains a set of measures and metrics that is constantly getting extended. For measures/metrics that can be used as loss functions, corresponding PyTorch modules are implemented.
$ pip install piq $ conda install piq -c photosynthesis-team -c conda-forge -c pytorch
See the open issues for a list of proposed features and known issues.
We appreciate all contributions. If you plan to:
Please see the contribution guide for more information.