{"id":15029738,"url":"https://github.com/jakeret/tf_unet","last_synced_at":"2025-05-15T13:06:50.725Z","repository":{"id":46655056,"uuid":"65535135","full_name":"jakeret/tf_unet","owner":"jakeret","description":"Generic U-Net Tensorflow implementation for image segmentation","archived":false,"fork":false,"pushed_at":"2020-05-05T09:29:55.000Z","size":4933,"stargazers_count":1904,"open_issues_count":90,"forks_count":747,"subscribers_count":65,"default_branch":"master","last_synced_at":"2025-04-15T02:08:57.430Z","etag":null,"topics":["deep-learning","image-segmentation","neural-network","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jakeret.png","metadata":{"files":{"readme":"README.rst","changelog":"HISTORY.rst","contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-08-12T08:02:22.000Z","updated_at":"2025-04-14T05:42:52.000Z","dependencies_parsed_at":"2022-08-22T06:00:30.770Z","dependency_job_id":null,"html_url":"https://github.com/jakeret/tf_unet","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jakeret%2Ftf_unet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jakeret%2Ftf_unet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jakeret%2Ftf_unet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jakeret%2Ftf_unet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jakeret","download_url":"https://codeload.github.com/jakeret/tf_unet/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254346624,"owners_count":22055808,"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","image-segmentation","neural-network","tensorflow"],"created_at":"2024-09-24T20:11:31.524Z","updated_at":"2025-05-15T13:06:45.684Z","avatar_url":"https://github.com/jakeret.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"=============================\nTensorflow Unet\n=============================\n\n.. image:: https://readthedocs.org/projects/tf-unet/badge/?version=latest\n\t:target: http://tf-unet.readthedocs.io/en/latest/?badge=latest\n\t:alt: Documentation Status\n\t\t\n.. image:: http://img.shields.io/badge/arXiv-1609.09077-orange.svg?style=flat\n        :target: http://arxiv.org/abs/1609.09077\n\n.. image:: https://img.shields.io/badge/ascl-1611.002-blue.svg?colorB=262255\n        :target: http://ascl.net/1611.002\n\n.. image:: https://mybinder.org/badge.svg\n        :target: https://mybinder.org/v2/gh/jakeret/tf_unet/master?filepath=demo%2Fdemo_toy_problem.ipynb\n\n\n.. warning::\n\n    This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://github.com/jakeret/unet\n\n\nThis is a generic **U-Net** implementation as proposed by `Ronneberger et al. \u003chttps://arxiv.org/pdf/1505.04597.pdf\u003e`_ developed with **Tensorflow**. The code has been developed and used for `Radio Frequency Interference mitigation using deep convolutional neural networks \u003chttp://arxiv.org/abs/1609.09077\u003e`_ .\n\nThe network can be trained to perform image segmentation on arbitrary imaging data. Checkout the `Usage \u003chttp://tf-unet.readthedocs.io/en/latest/usage.html\u003e`_ section or the included Jupyter notebooks for a `toy problem \u003chttps://github.com/jakeret/tf_unet/blob/master/demo/demo_toy_problem.ipynb\u003e`_ or the `Radio Frequency Interference mitigation \u003chttps://github.com/jakeret/tf_unet/blob/master/demo/demo_radio_data.ipynb\u003e`_ discussed in our paper.\n\nThe code is not tied to a specific segmentation such that it can be used in a toy problem to detect circles in a noisy image.\n\n.. image:: https://raw.githubusercontent.com/jakeret/tf_unet/master/docs/toy_problem.png\n   :alt: Segmentation of a toy problem.\n   :align: center\n\nTo more complex application such as the detection of radio frequency interference (RFI) in radio astronomy.\n\n.. image:: https://raw.githubusercontent.com/jakeret/tf_unet/master/docs/rfi.png\n   :alt: Segmentation of RFI in radio data.\n   :align: center\n\nOr to detect galaxies and star in wide field imaging data.\n\n.. image:: https://raw.githubusercontent.com/jakeret/tf_unet/master/docs/galaxies.png\n   :alt: Segmentation of a galaxies.\n   :align: center\n\n\nAs you use **tf_unet** for your exciting discoveries, please cite the paper that describes the package::\n\n\n\t@article{akeret2017radio,\n\t  title={Radio frequency interference mitigation using deep convolutional neural networks},\n\t  author={Akeret, Joel and Chang, Chihway and Lucchi, Aurelien and Refregier, Alexandre},\n\t  journal={Astronomy and Computing},\n\t  volume={18},\n\t  pages={35--39},\n\t  year={2017},\n\t  publisher={Elsevier}\n\t}\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjakeret%2Ftf_unet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjakeret%2Ftf_unet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjakeret%2Ftf_unet/lists"}