Getting Started with Project Aria Data Utilities
In this guide, we introduce how to install the projectaria_tools
Python package and provide tutorials to go through the APIs to access and visualize Aria data.
You can run this tutorial via Google Colab or install projectaria_tools
locally and use Jupyter notebooks.
This page covers Project Aria Tools core tutorials:
- Dataprovider quickstart tutorial: using the Aria Data Provider to access sensor data from a VRS file. Content covered includes:
- Retrieve image data
- Summarize a VRS file using thumbnails
- Obtaining sensor calibrations
- Access project/unproject functionalities
- Undistorting an image
- Sophus Pybind Tutorial: access Sophus Library SO3, SE3, interpolate and iterativeMean features
- Machine Perception Services (MPS) quickstart tutorial: a guide to visualizing MPS (derived) data. Content covered includes visualizing:
You can also explore the open datasets through tutorials:
- Aria Digital Twin (ADT) Tutorials
- Go to Getting Started with ADT for the introductory tutorial
- Go to Advanced Tutorials for multi-person synchronization and converting depth maps + RGB images to colored pointclouds
- Aria Synthetic Synthetic Environments Tutorial
- Go to Getting Started with Synthetic Environments for this tutorial
Running Jupyter Notebooks on Google Colab
Use the following links to run the Python notebooks in an installation free playground:
- Dataprovider Quickstart Tutorial - core tutorial
- Machine Perception Services Tutorial - core tutorial
- Aria Digital Twin (ADT) - open data tutorial
- Project Aria TICSync Tutorial - Time synchronization between multiple devices tutorial, demo data provided
Running the Jupyter Notebooks locally
Step 0 : Check system requirements and download codebase
Go to the Download Codebase page to:
- Check your system is supported
- Download projectaria_tools codebase from the github
Step 1 : Install/Update Python 3
To use the Jupyter notebooks in this tutorial you'll need Python 3.9 or above (3.10 if you are on Apple Silicon). To ensure all utilities work effectively, we recommend keeping Python 3 up to date.
- Python 3 download page
- To check what what version of Python 3 you have use
python3 --version
Step 2 : Create a virtual environment
rm -rf $HOME/projectaria_tools_python_env
python3 -m venv $HOME/projectaria_tools_python_env
source $HOME/projectaria_tools_python_env/bin/activate
Step 3 : Install projectaria_tools from PyPI
python3 -m pip install --upgrade pip
python3 -m pip install projectaria-tools'[all]'
Step 4: Run Dataprovider quickstart tutorial
cd $HOME/Documents/projectaria_sandbox
jupyter notebook projectaria_tools/core/examples/dataprovider_quickstart_tutorial.ipynb
If you get a Jupyter notebook error please upgrade Python 3 to the latest version and recreate your virtual environment.
Step 5: Run Sophus Pybind Tutorial
cd $HOME/Documents/projectaria_sandbox
jupyter notebook projectaria_tools/core/examples/sophus_quickstart_tutorial.ipynb
Step 6: Run Machine Perception Services (MPS) quickstart tutorial
In the MPS tutorial, the notebook walks through how to visualize gaze, trajectory, and point cloud from MPS data.
cd $HOME/Documents/projectaria_sandbox
jupyter notebook projectaria_tools/core/examples/mps_quickstart_tutorial.ipynb
Troubleshooting
Check the Troubleshooting Guide if you encounter issues using this tutorial.
Other Useful Links
- Troubleshooting
- Installation guide
- Visualizers