A Python‑based vehicle perception and mechatronics project that uses YOLO‑based object detection for real‑time vehicle detection. The repository includes various scripts for experimentation and building an intelligent system for robotics/vehicle analysis.
This project integrates computer vision with mechatronics principles to detect and process vehicle information from video or images using Python. The core object detection is implemented using YOLO (You Only Look Once) models, enabling fast and accurate recognition of vehicles such as cars, bikes, and trucks.
If you’re integrating this into a robotic system or autonomous agent, these scripts form the vision foundation for perception tasks (detection, tracking, classification).
✔ Real‑time vehicle detection using YOLO models
✔ Multiple Python scripts for different experiment setups
✔ Lightweight project structure ideal for mechatronics and robotics integration
✔ Works with pre‑trained YOLO weights or custom datasets (optional)
| File / Folder | Description |
|---|---|
yolo.py |
Main YOLO detection logic (uses a YOLO model) |
startpy.py |
Entry point script (example runner) |
corr.py |
Correlation or data processing utility |
span.py |
Additional helper module |
done.py, old.py, improved1.py |
Example/legacy scripts |
requirements.txt |
Python dependencies |
yolov8n.pt |
Pre‑trained YOLOv8‑n weights used for detection |
You need Python 3.7+ installed. Then install dependencies:
git clone https://github.com/Swizknife/MechatronicsVehicle.git
cd MechatronicsVehicle
pip install -r requirements.txt