doongli / pymagsac

MAGSAC: marginalizing sample consensus, python version

pymagsac

This repository contains an Python wrapper of MAGSAC. Daniel Barath, Jana Noskova and Jiri Matas; MAGSAC: Marginalizing sample consensus, CVPR 2019

https://github.com/danini/magsac -- main repo.

If you use the algorithm, please cite

@inproceedings{barath2019magsac,
	author = {Barath, Daniel and Matas, Jiri and Noskova, Jana},
	title = {MAGSAC: marginalizing sample consensus},
	booktitle = {Conference on Computer Vision and Pattern Recognition},
	year = {2019},
}

@inproceedings{barath2019magsacplusplus,
	author = {Barath, Daniel and Noskova, Jana and Ivashechkin, Maksym and Matas, Jiri},
	title = {MAGSAC++, a fast, reliable and accurate robust estimator},
	booktitle = {arXiv preprint:1912.05909},
	year = {2019},
}

If you use it for fundamental matrix estimation with DEGENSAC turned on, please cite

@inproceedings{Chum2005,
  author = {Chum, Ondrej and Werner, Tomas and Matas, Jiri},
  title = {Two-View Geometry Estimation Unaffected by a Dominant Plane},
  booktitle = {CVPR},
  year = {2005},
}

Performance

Magsac is the state of the art according to the recent study Yin et.al."Image Matching across Wide Baselines: From Paper to Practice", 2020.

Installation

To build and install python_cpp_example, clone or download this repository and then, from within the repository, run:

python3 ./setup.py install

or

pip3 install .

Example of usage

import pymagsac
H, mask = pymagsac.findHomography(src_pts, dst_pts, 3.0)
F, mask = pymagsac.findFundamentalMatrix(src_pts, dst_pts, 3.0)

See also this notebook

Requirements

• Python 3
• CMake 2.8.12 or higher
• OpenCV 3.4
• A modern compiler with C++14 support

Acknowledgements

This wrapper part is based on great Benjamin Jack python_cpp_example.