I'm excited to an open-source vision system I've been building for humanoid robots. It runs entirely on NVIDIA Jetson Orin Nano with full ROS2 integration.
The Problem
Every day, millions of robots are deployed to help humans. But most of them are blind. Or dependent on cloud services that fail. Or so expensive only big companies can afford them.
I wanted to change that.
What OpenEyes Does
The robot looks at a room and understands:
- "There's a cup on the table, 40cm away"
- "A person is standing to my left"
- "They're waving at me - that's a greeting"
- "The person is sitting down - they might need help"
- Object Detection (YOLO11n)
- Depth Estimation (MiDaS)
- Face Detection (MediaPipe)
- Gesture Recognition (MediaPipe Hands)
- Pose Estimation (MediaPipe Pose)
- Object Tracking
- Person Following (show open palm to become owner)
Performance
- All models: 10-15 FPS
- Minimal: 25-30 FPS
- Optimized (INT8): 30-40 FPS
Philosophy
- Edge First - All processing on the robot
- Privacy First - No data leaves the device
- Real-time - 30 FPS target
- Open - Built by community, for community
Quick Start
git clone https://github.com/mandarwagh9/openeyes.git
cd openeyes
pip install -r requirements.txt
python src/main.py --debug
python src/main.py --follow (Person following!)
python src/main.py --ros2 (ROS2 integration)
The Journey
Started with a simple question: Why can't robots see like we do?
Been iterating for months fixing issues like:
- MediaPipe detection at high resolution
- Person following using bbox height ratio
- Gesture-based owner selection
Would love feedback from the community!
GitHub: github.com/mandarwagh9/openeyes
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