https://github.com/jakeret/unet

Generic U-Net Tensorflow 2 implementation for semantic segmentation
https://github.com/jakeret/unet

deep-learning keras-tensorflow semantic-segmentation tensorflow

Last synced: 5 days ago
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Generic U-Net Tensorflow 2 implementation for semantic segmentation

• Host: GitHub
• URL: https://github.com/jakeret/unet
• Owner: jakeret
• License: gpl-3.0
• Created: 2020-04-08T13:33:05.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-12-26T21:38:41.000Z (about 2 years ago)
• Last Synced: 2024-12-24T23:06:05.640Z (12 days ago)
• Topics: deep-learning, keras-tensorflow, semantic-segmentation, tensorflow
• Language: Jupyter Notebook
• Homepage: https://u-net.readthedocs.io/en/latest/?badge=latest
• Size: 6.73 MB
• Stars: 254
• Watchers: 5
• Forks: 88
• Open Issues: 15
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGELOG.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE.txt

Awesome Lists containing this project

README

        
=============================

Tensorflow Unet

=============================

.. image:: https://readthedocs.org/projects/u-net/badge/?version=latest

        :target: https://u-net.readthedocs.io/en/latest/?badge=latest

        :alt: Documentation Status

.. image:: https://travis-ci.com/jakeret/unet.svg?branch=master

    :target: https://travis-ci.com/jakeret/unet

.. image:: http://img.shields.io/badge/arXiv-1609.09077-orange.svg?style=flat

        :target: http://arxiv.org/abs/1609.09077

.. image:: https://camo.githubusercontent.com/c8e5db7a5d15b0e7c13480a0ed81db1ae2128b80/68747470733a2f2f62696e6465722e70616e67656f2e696f2f62616467655f6c6f676f2e737667

        :target: https://mybinder.org/v2/gh/jakeret/unet/master?filepath=notebooks%2Fcicles.ipynb

.. image:: https://camo.githubusercontent.com/52feade06f2fecbf006889a904d221e6a730c194/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667

        :target: https://colab.research.google.com/drive/1laPoOaGcqEBB3jTvb-pGnmDU21zwtgJB

This is a generic **U-Net** implementation as proposed by `Ronneberger et al. `_ developed with **Tensorflow 2**. This project is a reimplementation of the original `tf_unet `_.

Originally, the code was developed and used for `Radio Frequency Interference mitigation using deep convolutional neural networks `_ .

The network can be trained to perform image segmentation on arbitrary imaging data. Checkout the `Usage `_ section, the included `Jupyter notebooks `_  or `on Google Colab `_ for a toy problem or the Oxford Pet Segmentation example available on `Google Colab `_.

The 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.

.. image:: https://raw.githubusercontent.com/jakeret/unet/master/docs/toy_problem.png

   :alt: Segmentation of a toy problem.

   :align: center

To more complex application such as the detection of radio frequency interference (RFI) in radio astronomy.

.. image:: https://raw.githubusercontent.com/jakeret/unet/master/docs/rfi.png

   :alt: Segmentation of RFI in radio data.

   :align: center

Or to detect galaxies and star in wide field imaging data.

.. image:: https://raw.githubusercontent.com/jakeret/unet/master/docs/galaxies.png

   :alt: Segmentation of a galaxies.

   :align: center

The architectural elements of a U-Net consist of a contracting and expanding path:

.. image:: https://raw.githubusercontent.com/jakeret/unet/master/docs/unet.png

   :alt: Unet architecture.

   :align: center

As you use **unet** for your exciting discoveries, please cite the paper that describes the package::

	@article{akeret2017radio,

	  title={Radio frequency interference mitigation using deep convolutional neural networks},

	  author={Akeret, Joel and Chang, Chihway and Lucchi, Aurelien and Refregier, Alexandre},

	  journal={Astronomy and Computing},

	  volume={18},

	  pages={35--39},

	  year={2017},

	  publisher={Elsevier}

	}