https://github.com/zaccharieramzi/tf-unet

An unofficial TensorFlow implementation of the U-net
https://github.com/zaccharieramzi/tf-unet

image-denoising image-segmentation tensorflow unet

Last synced: 3 months ago
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An unofficial TensorFlow implementation of the U-net

• Host: GitHub
• URL: https://github.com/zaccharieramzi/tf-unet
• Owner: zaccharieramzi
• Created: 2020-11-02T15:12:07.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-11-02T16:45:25.000Z (over 5 years ago)
• Last Synced: 2025-06-12T13:11:27.027Z (about 1 year ago)
• Topics: image-denoising, image-segmentation, tensorflow, unet
• Language: Python
• Homepage:
• Size: 5.86 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# TensorFlow implementation of the U-net

[![Build Status](https://travis-ci.com/zaccharieramzi/tf-unet.svg?branch=master)](https://travis-ci.com/zaccharieramzi/tf-unet)

The U-net is a network introduced by Olaf Ronneberger et al. in “U-Net: Convolutional Networks for Biomedical Image Segmentation”, MICCAI 2015.

If you use this network, please cite their work appropriately.

A change when compared to the initial architecture is that we use zero-padding to keep a constant image size.

There are lots of unofficial implementation of the U-net all over the web, here are some examples with comments:

- in [Keras](https://github.com/zhixuhao/unet/blob/master/model.py), however this model is not very modular.

- in [PyTorch](https://github.com/milesial/Pytorch-UNet/blob/master/unet/unet_model.py), again this model is not very modular off-the-shelf.

- in [TF v1.x](https://github.com/jakeret/tf_unet/blob/master/tf_unet/unet.py).

- in [TF v2.x](https://github.com/jakeret/unet/blob/master/src/unet/unet.py), by the same people as above.

- and [many more...](https://github.com/search?q=u-net)

The goal of this implementation in TensorFlow is to be easy to read and to adapt:

- all the code is in one file

- defaults are those from the paper (for gray image denoising)

- there is no other imports than from TensorFlow