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README.md
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<img src="docs/monoloco.gif" alt="gif" />
This library is based on three research projects:
This library is based on three research projects for monocular/stereo 3D human localization, orientation and social distancing.
> __MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization__<br />
> _[L. Bertoni](https://scholar.google.com/citations?user=f-4YHeMAAAAJ&hl=en), [S. Kreiss](https://www.svenkreiss.com),
[T. Mordan](https://people.epfl.ch/taylor.mordan/?lang=en), [A. Alahi](https://scholar.google.com/citations?user=UIhXQ64AAAAJ&hl=en)_, ICRA21 --> [Article](https://arxiv.org/abs/2008.10913),[Video](#Todo)
<img src="docs/000840_multi.jpg" width="550"/>
<img src="docs/000840_multi.jpg" width="600"/>
---
@ -18,20 +18,25 @@ This library is based on three research projects:
> _[L. Bertoni](https://scholar.google.com/citations?user=f-4YHeMAAAAJ&hl=en), [S. Kreiss](https://www.svenkreiss.com),
[A. Alahi](https://scholar.google.com/citations?user=UIhXQ64AAAAJ&hl=en)_, T-ITS 2021 --> [Article](https://arxiv.org/abs/2009.00984), [Video](https://www.youtube.com/watch?v=r32UxHFAJ2M)
<img src="docs/social_distancing.jpg" width="550"/>
<img src="docs/social_distancing.jpg" width="600"/>
---
> __MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation__<br />
> _[L. Bertoni](https://scholar.google.com/citations?user=f-4YHeMAAAAJ&hl=en), [S. Kreiss](https://www.svenkreiss.com), [A.Alahi](https://scholar.google.com/citations?user=UIhXQ64AAAAJ&hl=en)_, ICCV 2019 --> [Article](https://arxiv.org/abs/1906.06059), [Video](https://www.youtube.com/watch?v=ii0fqerQrec)
<img src="docs/surf.jpg.combined.png" width="550"/>
<img src="docs/surf.jpg.combined.png" width="600"/>
## License
All projects are built upon [Openpifpaf](https://github.com/vita-epfl/openpifpaf) for the 2D keypoints and share the AGPL Licence.
This software is also available for commercial licensing via the EPFL Technology Transfer
Office (https://tto.epfl.ch/, info.tto@epfl.ch).
# Quick setup
A GPU is not required, yet highly recommended for real-time performances.
The installation has been tested on OSX and Linux operating systems, with Python 3.6, 3.7, 3.8.
Packages have been installed with pip and virtual environments.
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or check the file `monoloco/run.py`
# Predictions
# TODO from here
For a quick setup download a pifpaf and MonoLoco++ / MonStereo models from
[here](https://drive.google.com/drive/folders/1jZToVMBEZQMdLB5BAIq2CdCLP5kzNo9t?usp=sharing) and save them into `data/models`.