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DanceCam

The public repository for DanceCam, showcasing some of the features of our atmospheric turbulence mitigation method.

The project website is available at https://dancecam.info.

The paper is available here.

Requirements (will be installed automatically by following the installation instructions)

  • Python 3.8+
  • PyTorch 1.10.0+
  • NumPy 1.21.2+
  • Astropy 4.0.1+
  • tqdm 4.62.3+
  • Blended Tiling 0.1.0+
  • SEWpy 0.1.0+

Installation

  1. Clone the repository:
git clone https://github.com/DanceCam/dancelibpublic.git
  1. Install:
cd dancelibpublic
pip install -e .

Usage

The demo folder contains a simple Jupyter notebook that shows how to use the library to perform inference on a video stream.

Citing DanceCam

To cite DanceCam, please use the following BibTeX entry:

@article{bialek2024dancecam,
  title = {DanceCam: atmospheric turbulence mitigation in wide-field astronomical images with short-exposure video streams},
  author = {Bialek, Spencer and Bertin, Emmanuel and Fabbro, S{\'e}bastien and Bouy, Herv{\'e} and Rivet, Jean-Pierre and Lai, Olivier and Cuillandre, Jean-Charles},
  journal = {Monthly Notices of the Royal Astronomical Society},
  pages = {stae1018},
  year = {2024},
  url = {https://academic.oup.com/mnras/advance-article/doi/10.1093/mnras/stae1018/7654005},
  publisher = {Oxford University Press},
}

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The public repository for DanceCam, showcasing some of the features of our atmospheric turbulence mitigation method.

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