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[doc] md fixes for readme + updated badges
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README.md

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CCTag library
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===================
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[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/3989/badge)](https://bestpractices.coreinfrastructure.org/projects/3989) [![Codacy Badge](https://app.codacy.com/project/badge/Grade/a99505cea4bd4cd195b9b65b6114ee90)](https://www.codacy.com/manual/alicevision/CCTag?utm_source=github.com&utm_medium=referral&utm_content=alicevision/CCTag&utm_campaign=Badge_Grade)
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# CCTag library
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[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/3989/badge)](https://bestpractices.coreinfrastructure.org/projects/3989)
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[![Codacy Badge](https://app.codacy.com/project/badge/Grade/5b8f7ee0d05b4c8fb5e6d6602e011217)](https://app.codacy.com/gh/alicevision/CCTag/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
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[![Continuous Integration](https://github.com/alicevision/CCTag/actions/workflows/continuous-integration.yml/badge.svg)](https://github.com/alicevision/CCTag/actions/workflows/continuous-integration.yml)
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Detection of CCTag markers made up of concentric circles. Implementations in both CPU and GPU.
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The library is the implementation of the paper:
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The library is the implementation of the paper:
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* Lilian Calvet, Pierre Gurdjos, Carsten Griwodz, Simone Gasparini. **Detection and Accurate Localization of Circular Fiducials Under Highly Challenging Conditions.** In: *Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR 2016)*, Las Vegas, E.-U., IEEE Computer Society, p. 562-570, June 2016. https://doi.org/10.1109/CVPR.2016.67
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* Lilian Calvet, Pierre Gurdjos, Carsten Griwodz, Simone Gasparini. **Detection and Accurate Localization of Circular Fiducials Under Highly Challenging Conditions.** In: *Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR 2016)*, Las Vegas, E.-U., IEEE Computer Society, p. 562-570, June 2016. <https://doi.org/10.1109/CVPR.2016.67>
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If you want to cite this work in your publication, please use the following
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If you want to cite this work in your publication, please use the following
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```latex
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@inproceedings{calvet2016Detection,
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}
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```
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Marker library
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---------
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## Marker library
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Markers to print are located [here](markersToPrint).
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Check your graphic card CUDA compatibility [here](https://github.com/tpruvot/ccminer/wiki/Compatibility).
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Building
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--------
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## Building
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See [INSTALL](INSTALL.md) text file.
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Continuous integration:
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| | windows | linux |
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|--------- |:-------: |:-----: |
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| master | [![Build status](https://ci.appveyor.com/api/projects/status/909b01qlixwslvmf?svg=true)](https://ci.appveyor.com/project/AliceVision/cctag) | ![Continuous Integration](https://github.com/alicevision/CCTag/workflows/Continuous%20Integration/badge.svg?branch=master) |
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| develop | [![Build status](https://ci.appveyor.com/api/projects/status/909b01qlixwslvmf/branch/develop?svg=true)](https://ci.appveyor.com/project/AliceVision/cctag/branch/develop) | ![Continuous Integration](https://github.com/alicevision/CCTag/workflows/Continuous%20Integration/badge.svg?branch=develop) |
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Running
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-------
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## Running
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Once compiled, you might want to run the CCTag detection on a sample image:
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```bash
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$ build/src/detection -n 3 -i sample/01.png
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build/src/detection -n 3 -i sample/01.png
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```
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For the library interface, see [ICCTag.hpp](src/cctag/ICCTag.hpp).
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Documentation
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-------------
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## Documentation
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The documentation can be found on the [Read the Docs page](https://cctag.readthedocs.io/en/latest/)
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License
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-------
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## License
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CCTag is licensed under [MPL v2 license](COPYING.md).
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Authors
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-------
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## Authors
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Lilian Calvet (CPU, [email protected])
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Carsten Griwodz (GPU, [email protected])
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Stian Vrba (CPU, [email protected])
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Cyril Pichard ([email protected])
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Simone Gasparini ([email protected])
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Lilian Calvet (CPU, <[email protected]>)
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Carsten Griwodz (GPU, <[email protected]>)
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Stian Vrba (CPU, <[email protected]>)
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Cyril Pichard (<[email protected]>)
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Simone Gasparini (<[email protected]>)
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Acknowledgments
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## Acknowledgments
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This has been developed in the context of the European project [POPART](https://alicevision.org/popart/) founded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 644874.
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