pip install vuer
⬝
visit https://docs.vuer.ai for documentation
Vuer is a light-weight visualization toolkit for interacting with dynamic 3D and robotics data. It is VR and AR ready, and can be run on mobile devices.
Our features include:
- light-weight and performant
- VR and AR ready
- Hackable and extensible
- Open source, licensed under MIT
You can install vuer
with pip
:
pip install -U 'vuer[all]'
Here is an example that loads a URDF file and displays it in the browser. For a more comprehensive list of examples, please refer to the examples page.
from vuer import Vuer, VuerSession
from vuer.schemas import DefaultScene, Urdf
app = Vuer()
@app.spawn(start=True)
async def main(session: VuerSession):
app.set @ DefaultScene(
Urdf("assets/urdf/robotiq.urdf"),
)
while True:
await session.sleep(0.1)
To get a quick overview of what you can do with vuer
, check out the following:
- take a look at the example gallery here
- or try to take a look at this demo with a Unitree Go1 robot in front of a flight of stairs here
For a comprehensive list of visualization components, please refer to the API documentation on Components.
For a comprehensive list of data types, please refer to the API documentation on Data Types.
Now, to run the examples, first download the example datasets.
Each subdirectory in the assets
directory contains a Makefile
. Run the make
command in each subdirectory to download the datasets. For
example:
cd assets/static_3d
make
Then run the examples
cd vuer/examples/vuer
python 01_trimesh.py
Documentation is a crucial part of the vuer
ecosystem. To contribute to documentation and usage examples, simply:
pip install -e '.[all]'
make docs
This should fire up an http server at the port 8888
, and you can view the documentation at http://localhost:8888
.
@software{vuer,
author = {Ge Yang},
title = {{VUER}: A 3D Visualization and Data Collection Environment for Robot Learning},
version = {},
publisher = {GitHub},
url = {https://github.com/vuer-ai/vuer},
year = {2024}
}
Vuer is built by researchers at MIT and UCSD in fields including robotics, computer vision, and computer graphics.