Traffic Signals Detector using YOLOv8

Published: 19 September 2024| Version 3 | DOI: 10.17632/g6mnc24f5b.3
Contributors:
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Description

This repository presents the obtained products from the research article "Commissioning of the NVIDIA Jetson AGX Orin module for a traffic signals detector based on YOLO"; this article, among other things, presents a real-time Traffic Signals Detector model trained on the NVIDIA Jetson AGX Orin module using CUDA cores. The proposed TSD is based on a pre-trained YOLOv8m model. Some detections and metrics of the TSD are shown to evaluate its performance.

Files

Steps to reproduce

1) Unzip the compressed file. 2) Read Readme.txt file. ***Note: The obtained TSD model can be found in the "\runs\detect\train13\weights\" directory as "best.pt". 3) If it is only desired to evaluate the model, the "TSD_testing.7z" file may be unzipped in order to run the "TSD_testing.py" script.

Institutions

Tecnologico Nacional de Mexico, Instituto Tecnologico de la Laguna

Categories

Computer Vision, Object Detection, Convolutional Neural Network, Deep Neural Network, Computer Vision Algorithms, Deep Transfer Learning, Transfer Learning

Funding

Tecnológico Nacional de México

Consejo Nacional de Humanidades, Ciencias y Tecnologías

Licence