convnext-unet 0.0.4

Unet model with ConvNext as its encoder.

ConvNeXt-Unet

Unet model with ConvNext as its encoder.

:construction: Work in progress...

Roadmap

• Source Code
• Document
  ...

Install

python -m pip install convnext-unet

Usage

from convnext_unet import ConvNeXtUnet

model = ConvNeXtUnet(num_classes=1, encoder_name='convnext_tiny', activation='sigmoid', pretrained=False, in_22k=False)

num_calsses: number of output classes.
encoder_name: name of encoder in convnext_tiny, convnext_small, convnext_base, convnext_large, convnext_xlarge.
activation: activation function to call before output.
pretrained: Whether to load ImageNet pretrained model for encoder.
in_22k: Whether to load ImageNet-22k pretrained model for encoder.

Acknowledgement

This repository is built on top of Pytorch-UNet, ConvNeXt and segmentation_models.pytorch.

Copyright

This project is released under the GPL-3.0 license. Please see the LICENSE file for more information.
Copyright (c) 2022 Tianyi Wang.
All rights reserved.

This program incorporates a modified version of Other Program.
Copyright (c) 2022 Meta Platforms, Inc. and affiliates.
Copyright (c) 2022 milesial.
Copyright (c) 2022 Pavel Iakubovskii.

Reference

@Article{liu2022convnet,
  author  = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
  title   = {A ConvNet for the 2020s},
  journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year    = {2022},
}

@inproceedings{ronneberger2015u,
  title={U-net: Convolutional networks for biomedical image segmentation},
  author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={234--241},
  year={2015},
  organization={Springer}
}