road_sign_detection
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Scientific vocabulary similarity
Low similarity (1.9%) to scientific vocabulary
Last synced: 6 months ago
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JSON representation
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Repository
Basic Info
- Host: GitHub
- Owner: Ziyanlu16
- License: agpl-3.0
- Language: Python
- Default Branch: main
- Size: 196 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
Contributing
License
Citation
README.md
Road Sign Detection with YOLOv5
Welcome to the YOLOv5 GUI specially designed to detect road signs from Germany and the UK. The model has been meticulously trained on the GTSDB dataset to ensure high accuracy and reliability.
Video Tutorial
For a comprehensive explanation and hands-on guide on how to utilize this GUI effectively, check out the video tutorial I’ve prepared: - 🎥 Watch the tutorial
Dataset
- The model weights have been trained using the GTSDB dataset.
Enjoy exploring and using the GUI for road sign detection! 🚦
Owner
- Login: Ziyanlu16
- Kind: user
- Repositories: 1
- Profile: https://github.com/Ziyanlu16
Citation (CITATION.cff)
cff-version: 1.2.0
preferred-citation:
type: software
message: If you use YOLOv5, please cite it as below.
authors:
- family-names: Jocher
given-names: Glenn
orcid: "https://orcid.org/0000-0001-5950-6979"
title: "YOLOv5 by Ultralytics"
version: 7.0
doi: 10.5281/zenodo.3908559
date-released: 2020-5-29
license: AGPL-3.0
url: "https://github.com/ultralytics/yolov5"