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<img src="docs/monoloco.gif" alt="gif" /> <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 /> > __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), > _[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) [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"/>
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> _[L. Bertoni](https://scholar.google.com/citations?user=f-4YHeMAAAAJ&hl=en), [S. Kreiss](https://www.svenkreiss.com), > _[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) [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"/>
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> __MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation__<br /> > __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) > _[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. 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 # Quick setup
A GPU is not required, yet highly recommended for real-time performances. 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. 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. Packages have been installed with pip and virtual environments.
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or check the file `monoloco/run.py` or check the file `monoloco/run.py`
# Predictions # Predictions
# TODO from here
For a quick setup download a pifpaf and MonoLoco++ / MonStereo models from 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`. [here](https://drive.google.com/drive/folders/1jZToVMBEZQMdLB5BAIq2CdCLP5kzNo9t?usp=sharing) and save them into `data/models`.