In this post, I’m presenting an example of Hand Tracking and Gesture Recognition using MediaPipe Python and Rerun SDK.
If you’re interested in delving deeper and expanding your understanding, I will guide you on how to install MediaPipe Python and Rerun SDK to track a hand, recognise different gestures and visualise the data.
Therefore, you’ll learn:
- How to install MediaPipe Python and Rerun
- How to use MediaPipe Gesture Recognition for Hand Tracking and Gesture Recognition
- How to visualise the results of the hand-tracking and gesture recognition in the Rerun Viewer
If you’re just eager to give the example a try, simply use the provided code:
# Clone the rerun GitHub repository to your local machine.
git clone https://github.com/rerun-io/rerun# Navigate to the rerun repository directory.
cd rerun
# Install the required Python packages specified in the requirements file
pip install -r examples/python/gesture_detection/requirements.txt
# Run the main Python script for the example
python examples/python/gesture_detection/main.py
# Run the main Python script for a specific image
python examples/python/gesture_detection/main.py --image path/to/your/image.jpg
# Run the main Python script for a specific video
python examples/python/gesture_detection/main.py --video path/to/your/video.mp4
# Run the main Python script with camera stream
python examples/python/gesture_detection/main.py --camera
Before we proceed, let’s give credit to the technology that makes this possible. The hand tracking and gesture recognition technology aims to give the ability of the devices to interpret hand movements and gestures as commands or inputs. At the core of this technology, a pre-trained machine-learning model analyses the visual input and identifies hand landmarks and hand gestures. The real applications of such technology vary, as hand movements and gestures…