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CDTNCA

Repository for our ICIP 2021 paper, titled Cyclic Diffeomorphic Transformer Nets for Contour Alignment co-authored by: Ilya Kaufman, Ron Shapira Weber and Oren Freifeld. CDTNCA alignmnet.

Model Architecture

CDTNCA architecture.

libcpab

licpab [2] is a python package supporting the CPAB transformations [1] in Numpy, Tensorflow and Pytorch. Our code uses a modified version of libcpab which allows for circular warps. Warp with different constraints.

Author of this software

Ilya Kafuman (email: [email protected])

Requirements

  • Standard Python(>=3.6) packages: numpy, matplotlib, tqdm
  • PyTorch >= 1.4
  • For Nvidia GPU iimplementation: CUDA==11.0 + appropriate cuDNN as well. You can follow the instructions here.

Installation

The code uses Python 3.6 and it was tested on Pytorch 1.9.0

Install pip and virtualenv

sudo apt-get install python-pip python-virtualenv

Clone the git project:

$ git clone [email protected]:BGU-CS-VIL/CDTNCA.git

Set up virtual environment:

$ mkdir <your_home_dir>/.virtualenvs
$ virtualenv -p python3 <your_home_dir>/.virtualenvs/CDTNCA

Activate virtual environment:

$ cd CDTNCA
$ source <your_home_dir>/.virtualenvs/CDTNCA/bin/activate

The requirements can be installed using:

pip install -r requirements.txt

Usage

Alignment of a subset of shapes generated from the 2D Shape Structure dataset [3]. For the entire archive, please visit: http://2dshapesstructure.github.io/

python alignment.py [args]
  • tess_size: list, with the number of cells in each dimension
  • zero_boundary: bool, determines if the velocity at the boundary is zero
  • circularity: bool, allows for circular warps

References

[1] @article{freifeld2017transformations,
  title={Transformations Based on Continuous Piecewise-Affine Velocity Fields},
  author={Freifeld, Oren and Hauberg, Soren and Batmanghelich, Kayhan and Fisher, John W},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2017},
  publisher={IEEE}
}

[2] @misc{detlefsen2018,
  author = {Detlefsen, Nicki S.},
  title = {libcpab},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/SkafteNicki/libcpab}},
}
[3] @article{Carlier:CG:20162:2DShapes,
  title={The 2d shape structure dataset: A user annotated open access database},
  author={Carlier, Axel and Leonard, Kathryn and Hahmann, Stefanie and Morin, Geraldine and Collins, Misha},
  journal={Computers \& Graphics},
  volume={58},
  pages={23--30},
  year={2016},
  publisher={Elsevier}
}

License

This software is released under the MIT License (included with the software). Note, however, that if you are using this code (and/or the results of running it) to support any form of publication (e.g., a book, a journal paper, a conference paper, a patent application, etc.) then we request you will cite our paper:

@INPROCEEDINGS{kaufman2021contouralign,
  author={Kaufman, Ilya and Weber, Ron Shapira and Freifeld, Oren},
  booktitle={2021 IEEE International Conference on Image Processing (ICIP)}, 
  title={Cyclic Diffeomorphic Transformer Nets For Contour Alignment}, 
  year={2021},
  pages={349-353}
}

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