YOLO-in-ROS2

Working Code to use yolo in the ros2 environment.

Ensure you have Darknet installed and the yolo cfg and weights file downloaded (This Repo utilises Yolo-v3)

Contains two Nodes:

People_detector

Code used to invoke YOLO within the ros2 environment to detect object, mainly people in this use case however, it works on all objects.

Webcam

Used to run the people detector algorithim using a regular webcam

Steps

1. Clone the repo within a ros2/src/ workspace and change the path directories for the weights and label files within peopleDetector.py
2. Build the workspace with colcon build
3. Source your workspace i.e export local_setup.bash
4. Run poeple_dector with ros2 run
5. Run webcam_py in a separate terminal
6. In another terminal, ros2 run rqt_image_view and select the output image topic to view live results.

Tested on:
Open-CV 4.7.0
Ubuntu 20.04
ROS2 Foxy

References

@article{yolov3,
title={YOLOv3: An Incremental Improvement},
author={Redmon, Joseph and Farhadi, Ali,
journal = {arXiv},
year={2018}
}