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CAREamics

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CAREamics is a PyTorch library aimed at simplifying the use of Noise2Void and its many variants and cousins (CARE, Noise2Noise, N2V2, P(P)N2V, HDN, muSplit etc.).

Why CAREamics?

Noise2Void is a widely used denoising algorithm, and is readily available from the n2v python package. However, n2v is based on TensorFlow and Keras and we found it increasingly hard to maintain. In addition, more recent methods (PPN2V, DivNoising, HDN) are all implemented in PyTorch, but are lacking the extra features that would make them usable by the community.

The aim of CAREamics is to provide a PyTorch library reuniting all the latest methods in one package, while providing a simple and consistent API. The library relies on PyTorch Lightning as a back-end. In addition, we will provide extensive documentation and tutorials on how to best apply these methods in a scientific context.

Installation and use

Check out the documentation for installation instructions and guides!

careamics's Projects

careamics icon careamics

A deep-learning library for N2V and friends

careamics-portfolio icon careamics-portfolio

A helper package to download example datasets used in various publications by the Jug lab, including data featured in N2V, P(P)N2V, DivNoising, HDN, EmbedSeg, etc.

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