{"id":25237143,"url":"https://github.com/CAREamics/careamics","last_synced_at":"2025-10-26T12:30:36.685Z","repository":{"id":182008888,"uuid":"607105530","full_name":"CAREamics/careamics","owner":"CAREamics","description":"A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.)","archived":false,"fork":false,"pushed_at":"2025-02-10T15:24:59.000Z","size":3804,"stargazers_count":49,"open_issues_count":68,"forks_count":6,"subscribers_count":6,"default_branch":"main","last_synced_at":"2025-02-10T15:33:37.165Z","etag":null,"topics":["deep-learning","denoising","n2v","python","restoration"],"latest_commit_sha":null,"homepage":"https://careamics.github.io/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CAREamics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-02-27T10:22:28.000Z","updated_at":"2025-02-10T15:25:04.000Z","dependencies_parsed_at":"2024-05-14T15:00:22.244Z","dependency_job_id":"cb0141f9-25ab-4a55-b4c5-d3a06533e569","html_url":"https://github.com/CAREamics/careamics","commit_stats":null,"previous_names":["careamics/careamics-restoration","careamics/careamics"],"tags_count":19,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CAREamics%2Fcareamics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CAREamics%2Fcareamics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CAREamics%2Fcareamics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CAREamics%2Fcareamics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CAREamics","download_url":"https://codeload.github.com/CAREamics/careamics/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":238320442,"owners_count":19452553,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","denoising","n2v","python","restoration"],"created_at":"2025-02-11T15:33:30.473Z","updated_at":"2025-10-26T12:30:36.124Z","avatar_url":"https://github.com/CAREamics.png","language":"Python","funding_links":[],"categories":["🪄 Image denoising"],"sub_categories":["Software tools"],"readme":"\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://careamics.github.io/\"\u003e\n    \u003cimg src=\"https://raw.githubusercontent.com/CAREamics/.github/main/profile/images/banner_careamics.png\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n# CAREamics\n\n[![License](https://img.shields.io/pypi/l/careamics.svg?color=green)](https://github.com/CAREamics/careamics/blob/main/LICENSE)\n[![PyPI](https://img.shields.io/pypi/v/careamics.svg?color=green)](https://pypi.org/project/careamics)\n[![Python Version](https://img.shields.io/pypi/pyversions/careamics.svg?color=green)](https://python.org)\n[![CI](https://github.com/CAREamics/careamics/actions/workflows/ci.yml/badge.svg)](https://github.com/CAREamics/careamics/actions/workflows/ci.yml)\n[![codecov](https://codecov.io/gh/CAREamics/careamics/branch/main/graph/badge.svg)](https://codecov.io/gh/CAREamics/careamics)\n[![Image.sc](https://img.shields.io/badge/Got%20a%20question%3F-Image.sc-blue)](https://forum.image.sc/)\n\n\nCAREamics is a PyTorch library aimed at simplifying the use of Noise2Void and its many\nvariants and cousins (CARE, Noise2Noise, N2V2, P(P)N2V, HDN, muSplit etc.).\n\n## Why CAREamics?\n\nNoise2Void is a widely used denoising algorithm, and is readily available from the `n2v`\npython package. However, `n2v` is based on TensorFlow, while more recent methods \ndenoising methods (PPN2V, DivNoising, HDN) are all implemented in PyTorch, but are \nlacking the extra features that would make them usable by the community.\n\nThe aim of CAREamics is to provide a PyTorch library reuniting all the latest methods\nin one package, while providing a simple and consistent API. The library relies on \nPyTorch Lightning as a back-end. In addition, we will provide extensive documentation and \ntutorials on how to best apply these methods in a scientific context.\n\n## Installation and use\n\nCheck out the [documentation](https://careamics.github.io/) for installation instructions and guides!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCAREamics%2Fcareamics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FCAREamics%2Fcareamics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCAREamics%2Fcareamics/lists"}