This system integrates advanced AI capabilities, including a machine learning algorithm running on-device, to allow users to control their computer cursor through hand and gesture tracking, leveraging Google's MediaPipe and the OAK-D Lite camera's processing.
- Control the cursor with hand gestures.
- Different gestures for moving, clicking, and scrolling.
- Efficient processing on OAK-D Lite's onboard chip.
- Intuitive, natural human-computer interaction.
To install the necessary dependencies, ensure you have Python 3 and pip installed on your system. Then run the following commands:
python3 -m pip install -U pip
python3 -m pip install --extra-index-url https://artifacts.luxonis.com/artifactory/luxonis-python-snapshot-local/ depthai
pip install -r requirements.txt
Make sure your OAK-D Lite camera is connected to your computer before proceeding.
The system recognizes specific hand poses to control the cursor:
- Move: FIVE pose (open hand, move around freely)
- Click: FIST pose (close fist)
- Scroll: PEACE pose (index and middle finger together, move up and down)
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To run the application, use the following command:
python3 mouse_controller.py
The system will start in headless mode by default, with no display output.
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To enable a real-time rendering of the hand tracking, use the
-r
flag:python3 mouse_controller.py -r
This will open a new window showing the live hand tracking process.
Ensure your hand is in the view of the OAK-D Lite camera, and the system will track your hand movements, interpreting them to control the cursor accordingly.
This project was inspired by the depthai_hand_tracker repository, and I acknowledge the groundbreaking work they have shared with the community and do not claim any rights for their work. Contributions to enhance functionality or performance are warmly welcomed. Feel free to submit issues or pull requests.
This system is a demonstration of AI and computer vision capabilities with the OAK-D Lite camera. It is not intended for critical use cases. Use at your own discretion and risk.