Skip to content
/ UNET Public

Reproducing one of the most cited (100k) deep learning architecture UNET using latest PyTorch 2.6. It is used in state-of-the-art generative models such as stable diffusion.

Notifications You must be signed in to change notification settings

akbaig/UNET

Repository files navigation

Reproducing one of the most cited (100k) deep learning architecture UNET using latest PyTorch 2.6. It is used in state-of-the-art generative models such as stable diffusion.

UNET Results

Installation

Python 3.9.21 is required

Install dependencies: pip install -r requirements.txt

Credits:

Reproduced by: Ahmad Kamal

Original Paper:

@misc{ronneberger2015unetconvolutionalnetworksbiomedical,
      title={U-Net: Convolutional Networks for Biomedical Image Segmentation}, 
      author={Olaf Ronneberger and Philipp Fischer and Thomas Brox},
      year={2015},
      eprint={1505.04597},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1505.04597}, 
}

About

Reproducing one of the most cited (100k) deep learning architecture UNET using latest PyTorch 2.6. It is used in state-of-the-art generative models such as stable diffusion.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published