Computer Vision & Embedded · 2025
Electronics Component Detector
Custom YOLO model that recognises Arduino and IoT components in real time
A custom-trained YOLO model for real-time detection and classification of common electronic components used in Arduino and IoT projects, reaching 83.8% mAP@0.5.
Trained on a curated dataset of components found on a typical maker's bench, the model is suited to both learning and practical use.
What it does
- 83.8% mAP@0.5 on the curated dataset
- Real-time detection of common Arduino and IoT parts
- First custom YOLO model trained end to end
Built with
- Python
- YOLO
- Ultralytics
- OpenCV