Skip to content

This project uses the YOLO TensorRT library and the DeepSORT algorithm to monitor tunnel traffic. It identifies, counts, and tracks vehicles as they enter and exit the tunnel, providing real-time insights into traffic flow.

Notifications You must be signed in to change notification settings

Akaqox/tunnel-car-tracking

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Real Time Tunnel Car Tracking with DeepSORT and ByteTrack

This project uses the YOLO TensorRT library and the DeepSORT and ByteTrack algorithm to monitor tunnel traffic. While identifies, counts, and tracks vehicles as they enter and exit the tunnel, providing real-time insights into traffic flow.

Python Pytorch


💾 ABOUT

Will be added later


Project Structure

Will be added later

💻 TECHNOLOGIES

PythonOpenCVnVIDIANumPyPyTorchscikit-learnnVIDIAAnacondaLinux

INSTALLATION

git clone https://github.com/Akaqox/tunnel-car-tracking.git
cd tunnel-car-tracking
conda create --name track --file requirements.txt
conda activate track

🔎 SHOWCASE

Will be added



🔎 REFERENCES

TensorRT YOLO Inference taken code samples from: https://github.com/Linaom1214/TensorRT-For-YOLO-Series

ByteTrack taken code samples from: https://github.com/ifzhang/ByteTrack

deep_sort_realtime library is used



About

This project uses the YOLO TensorRT library and the DeepSORT algorithm to monitor tunnel traffic. It identifies, counts, and tracks vehicles as they enter and exit the tunnel, providing real-time insights into traffic flow.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages