https://github.com/CAREamics/careamics

A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.)
https://github.com/CAREamics/careamics

deep-learning denoising n2v python restoration

Last synced: 2 months ago
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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.)

• Host: GitHub
• URL: https://github.com/CAREamics/careamics
• Owner: CAREamics
• License: bsd-3-clause
• Created: 2023-02-27T10:22:28.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2025-02-10T15:24:59.000Z (2 months ago)
• Last Synced: 2025-02-10T15:33:37.165Z (2 months ago)
• Topics: deep-learning, denoising, n2v, python, restoration
• Language: Python
• Homepage: https://careamics.github.io/
• Size: 3.63 MB
• Stars: 49
• Watchers: 6
• Forks: 6
• Open Issues: 68
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

• awesome-scientific-image-analysis - CAREamics - Deep-learning based, self-supervised algorithms: Noise2Void, N2V2, etc. (🪄 Image denoising / Software tools)
• awesome-scientific-image-analysis - CAREamics

README

        


  

    

  



# CAREamics

[![License](https://img.shields.io/pypi/l/careamics.svg?color=green)](https://github.com/CAREamics/careamics/blob/main/LICENSE)

[![PyPI](https://img.shields.io/pypi/v/careamics.svg?color=green)](https://pypi.org/project/careamics)

[![Python Version](https://img.shields.io/pypi/pyversions/careamics.svg?color=green)](https://python.org)

[![CI](https://github.com/CAREamics/careamics/actions/workflows/ci.yml/badge.svg)](https://github.com/CAREamics/careamics/actions/workflows/ci.yml)

[![codecov](https://codecov.io/gh/CAREamics/careamics/branch/main/graph/badge.svg)](https://codecov.io/gh/CAREamics/careamics)

[![Image.sc](https://img.shields.io/badge/Got%20a%20question%3F-Image.sc-blue)](https://forum.image.sc/)

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](https://careamics.github.io/) for installation instructions and guides!