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A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.)

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CAREamics/careamics

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, while more recent methods denoising 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!

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A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.)

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