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Getting Started With AEA

Overview​

This section provides a step-by-step guide to run the Aria Everyday Activities (AEA) quickstart tutorial in a Jupyter notebook.

This notebook covers how to:

  • Access raw sensor data (VRS files)
  • Visualize Eye Gaze data
  • Visualize Speech data
  • Load concurrent sequences from multiple Project Aria glasses in a shared space location
  • Use Timecode to get synchronized data between two devices

Run Jupyter Notebook on Google Colab​

Use the following link to run the Python notebook in an installation free playground:

Running the Jupyter Notebook locally​

Step 0 : Check system requirements and download codebase​

Ensure your system is supported and then download projectaria_tools codebase from the github

Step 1 : Install Python​

If you have already installed projectaria-tools using Python Package Installation, you can skip to Step 4. The AEA Python code is part of the main projectaria-tools package.

Jupyter notebook error

If you have problems using Jupyter examples, please upgrade python3 to the latest 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 : Download the Sample Sequence​

Download the sample AEA sequence by following steps 0 to 4 in Dataset Download.

Step 5 : Run Tutorial​

From your projectaria_tools Python virtual environment, run:

cd $HOME/Documents/projectaria_sandbox

jupyter notebook projectaria_tools/projects/AriaEverydayActivities/examples/aea_quickstart_tutorial.ipynb

Troubleshooting​

Go to Data Utilities Troubleshooting if you experience issues implementing this guide.