IDD-YOLOv5: A Lightweight Insulator Defect Real-time Detection Algorithm

Introduction

This is our PyTorch implementation of the paper "IDD-YOLOv5: A Lightweight Insulator Defect Real-time Detection Algorithm" published in 2024 IEEE International Conference on Mechatronics and Automation (ICMA).

Quick Start Examples

Install

First, clone the project and configure the environment. Python>=3.7.0, PyTorch>=1.7.

git clone https://github.com/LuYang-2023/ICMA2024.git  # clone
cd ICMA2024
pip install -r requirements.txt  # install

Train

python train.py --cfg models/IDD-yolov5.yaml --data data/insulator_detection.yaml

Test

python val.py --data data/mydata.yaml --weights best.pt --task test

Citation

If you use this code or article in your research, please cite it using the following BibTeX entry:

@INPROCEEDINGS{10632897,
  author={Lu, Yang and Li, Dahua and Gao, Qiang and Yu, Xiao and Li, Xuan and Bai, Zhongli},
  booktitle={2024 IEEE International Conference on Mechatronics and Automation (ICMA)}, 
  title={IDD-YOLOv5: A Lightweight Insulator Defect Real-time Detection Algorithm}, 
  year={2024},
  volume={},
  number={},
  pages={491-495},
  keywords={YOLO;Adaptation models;Accuracy;Power transmission lines;Insulators;Real-time systems;Neck;Defect detection;Insulator;Lightweight;Deep learning;YOLOv5},
  doi={10.1109/ICMA61710.2024.10632897}}

Author's Contact

Email：yj20220275@stud.tjut.edu.cn