Metadata-Version: 2.1
Name: unet-torch
Version: 0.0.1
Summary: unet - Pytorch
Home-page: https://github.com/kyegomez/SimpleUnet
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.6,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: torch
Project-URL: Repository, https://github.com/kyegomez/unet
Description-Content-Type: text/markdown

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# Unet
My implemenetation of a modular Unet from the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation"

[Paper Link](https://arxiv.org/abs/1505.04597)

# Appreciation
* Lucidrains
* Agorians



# Install
`pip install unet`

# License
MIT

# Citations
```bibtex
@misc{1505.04597,
Author = {Olaf Ronneberger and Philipp Fischer and Thomas Brox},
Title = {U-Net: Convolutional Networks for Biomedical Image Segmentation},
Year = {2015},
Eprint = {arXiv:1505.04597},
}
```
