Perceiving Humans in 3D
MonoLoco++ and MonStereo for 3D localization, orientation, bounding box dimensions and social distancing from monocular and / or stereo images. PyTorch Official Implementation.
- Perceiving Humans: from Monocular 3D Localization to Social Distancing (MonoLoco++)
README & Article
Installation steps are the same for both projects.
The installation has been tested on OSX and Linux operating systems, with Python 3.6 or Python 3.7.
Packages have been installed with pip and virtual environments.
For quick installation, do not clone this repository,
and make sure there is no folder named monstereo in your current directory.
A GPU is not required, yet highly recommended for real-time performances.
MonoLoco++ and MonStereo can be installed as a single package, by:
pip3 install monstereo
For development of the monstereo source code itself, you need to clone this repository and then:
pip3 install sdist cd monstereo python3 setup.py sdist bdist_wheel pip3 install -e .
All the commands are run through a main file called
main.py using subparsers.
To check all the commands for the parser and the subparsers (including openpifpaf ones) run:
python3 -m monstereo.run --help
python3 -m monstereo.run predict --help
python3 -m monstereo.run train --help
python3 -m monstereo.run eval --help
python3 -m monstereo.run prep --help
or check the file
Data ├── arrays ├── models ├── kitti ├── figures ├── logs
Run the following to create the folders:
mkdir data cd data mkdir arrays models kitti figures logs
Further instructions for prediction, preprocessing, training and evaluation can be found here: