README.md

Python Traffic Counter

The purpose of this project is to detect and track vehicles on a video stream and count those going through a defined line.

It uses:

• YOLO to detect objects on each of the video frames.

• SORT to track those objects over different frames.

Once the objects are detected and tracked over different frames a simple mathematical calculation is applied to count the intersections between the vehicles previous and current frame positions with a defined line.

The code on this prototype uses the code structure developed by Adrian Rosebrock for his article YOLO object detection with OpenCV.

Quick Start

1. Download the code to your computer.
2. Download yolov3.weights and place it in /yolo-coco.
3. Make sure you have Python 3.7.0 and OpenCV 3.4.2 installed.
4. Run:

$ python main.py --input input/highway.mp4 --output output/highway.avi --yolo yolo-coco

Citation

YOLO :

@article{redmon2016yolo9000,
  title={YOLO9000: Better, Faster, Stronger},
  author={Redmon, Joseph and Farhadi, Ali},
  journal={arXiv preprint arXiv:1612.08242},
  year={2016}
}

SORT :

@inproceedings{Bewley2016_sort,
  author={Bewley, Alex and Ge, Zongyuan and Ott, Lionel and Ramos, Fabio and Upcroft, Ben},
  booktitle={2016 IEEE International Conference on Image Processing (ICIP)},
  title={Simple online and realtime tracking},
  year={2016},
  pages={3464-3468},
  keywords={Benchmark testing;Complexity theory;Detectors;Kalman filters;Target tracking;Visualization;Computer Vision;Data Association;Detection;Multiple Object Tracking},
  doi={10.1109/ICIP.2016.7533003}
}