identification

Vehicle direction identification consists of three module detection , tracking and direction recognization

Vehicle direction identification consists of three module detection , tracking and direction recognization.

Algorithm used : Yolo algorithm for detection + SORT algorithm to track vehicles + vector based direction detection

Backend : opencv and python

Library required:

  • opencv = ‘4.5.4-dev’
  • scipy = ‘1.4.1’
  • filterpy
  • lap
  • scikit-image

IMPORTANT:

  • I hadn’t uploaded model weights and configuration files (which were used for object detection) here because those were already available in yolo_detection repo
  • download yolo tiny weights , config file and coco.names file from here : [https://github.com/hasit73/yolo_detection]
  • For detection i was using same code which was available in yolo_detection repo.

1) main.py

  • Loading model and user configurations
  • perform io interfacing tasks

2) yolo.py

  • use opencv modules to detect objects from user given media(photo/video)
  • detection take place inside this file

3) config.json