/smg-pyopencv

Primary LanguageC++OtherNOASSERTION

smg-pyopencv

This Python package provides Python bindings for OpenCV images.

It is a submodule of smglib, the open-source Python framework associated with our drone research in the Cyber-Physical Systems group at the University of Oxford.

Installation (as part of smglib)

Note: Please read the top-level README for smglib before following these instructions.

  1. Download and extract a pre-built copy of OpenCV (if you have not already done so), and set (at a system level, not within the terminal) the SMGLIB_OPENCV_DIR environment variable to the sub-directory within it that contains OpenCVConfig.cmake, e.g.

    C:/Users/<your user>/Downloads/opencv-3.4.15/build

  2. Open the terminal, and change to the <root>/smg-pyopencv directory.

  3. Check out the master branch.

  4. Activate the Conda environment, e.g. conda activate smglib.

  5. Run pip install -e . at the terminal.

Publications

If you build on this framework for your research, please cite the following paper:

@inproceedings{Golodetz2022TR,
author = {Stuart Golodetz and Madhu Vankadari* and Aluna Everitt* and Sangyun Shin* and Andrew Markham and Niki Trigoni},
title = {{Real-Time Hybrid Mapping of Populated Indoor Scenes using a Low-Cost Monocular UAV}},
booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
month = {October},
year = {2022}
}

Acknowledgements

This work was supported by Amazon Web Services via the Oxford-Singapore Human-Machine Collaboration Programme, and by UKRI as part of the ACE-OPS grant. We would also like to thank Graham Taylor for the use of the Wytham Flight Lab, Philip Torr for the use of an Asus ZenFone AR, and Tommaso Cavallari for implementing TangoCapture.