Click the video below to play a preview of our traffic detection system:
![Watch the video](/abidikshit/Yolov9-VancouverTrafficCongestion/raw/main/video/traffic.png)
Hey everyone! Exciting updates from our ongoing project tackling transit poverty through artificial intelligence. 🚗💻
We've implemented YOLO v9 (You Only Look Once) (released February 21st, 2024) to count incoming traffic for intersections in real-time. That's right; no more manual counting! 🙌
Currently, we're working on calculating vehicle speed and predicting approaching arrival times to optimize traffic signal timing. Think personalized green lights just for you! GREEN MEANS GO🚦
But wait, there's more! We're diving into reinforcement learning using V2X technology. What does that mean? Our system learns from the environment and makes decisions based on rewards – like giving priority to emergency vehicles or pedestrians. Mind blown yet? 🤯
And did we mention we're using YOLO object detection too? 🔍 It's like having our very own superhero watching over traffic flow. Safety and efficiency, anyone? 🛑️
The journey continues as we dive deeper into the realm of deep learning. Stay tuned for more exciting developments and join us in creating a smarter, safer future for all. 🌐✨
Special thanks to our dedicated contributors who have made significant contributions to this project:
- Murtaza Vora
- Gunjan Paladiya
- Milan Prajapati
- Chinthaka Dinesh
Run the yolov9c_vehicle_count_tracker.ipynb script in Jupyter Lab to get started and feel free to make adjustments based on your need.