yolo_mark_utility

A utility for capturing training data for yolo models

https://github.com/weharris/yolo_mark_utility

Science Score: 57.0%

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CITATION.cff file
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Low similarity (4.5%) to scientific vocabulary

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Repository

A utility for capturing training data for yolo models

Basic Info

Host: GitHub
Owner: weharris
License: mit
Language: Python
Default Branch: main
Size: 15.6 KB

Statistics

Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 1

Created about 4 years ago · Last pushed 9 months ago

Metadata Files

Readme License Citation

Yolo Mark Utility

This repository is code for a lightweight data capture utility that provides a graphical user interface for drawing bounding boxes around objects in images for the creation of training datasets for deep learning applications. The basic program is based on the Yolo_mark repository. The program outputs data files in yolo format text files.

The program was developed at Harper Adams University by Matt Butler, George Wager, and Ed Harris.

Versions

desktopimagelabeller.py for labeling images that are stored locally on a PC
wirelessimagelabeller.py for labelling images that are recorded live with a webcam

Citation

Harris, W. Edwin et al. (2021), Data From: Investigating human repeatability of a computer vision based task to identify meristems on a potato plant (Solanum tuberosum)., Dryad, Dataset, https://doi.org/10.5061/dryad.2rbnzs7pz

Owner

Login: weharris
Kind: user
Location: American werewolf in Shropshire, UK

Twitter: EdHarris9000
Repositories: 1
Profile: https://github.com/weharris

Statistics and data science with a little bit of ecology, genetics and teaching.

Citation (CITATION.cff)

cff-version: 1.0.0
message: "If you use this software, please cite it as below."
title: "R Stats Bootcamp"
abstract: "A self-paced course for learning R programming, statistical analysis, and reproducible research practices. Designed for beginners with modules covering R scripting, RStudio interface, data analysis fundamentals, and reproducible research workflows using R and GitHub."
authors:
- family-names: "Harris"
  given-names: "W. E."
  orcid: "https://orcid.org/0000-0002-9038-8656"
- family-names: "Butler"
  given-names: "Matthew"
title: "Yolo Mark Utility"
version: 1.0.0
doi: 10.5281/zenodo.10853601
date-released: 2022-08-01
url: "https://github.com/yolo_mark_utility"
license: MIT
keywords:
  - yolo
  - computer Vision
  - deep learning
  - python
preferred-citation:
  type: software
  authors:
  - family-names: "Harris"
    given-names: "W. E."
    orcid: "https://orcid.org/0000-0002-9038-8656"
    affiliation: "Centre for Agricultural Data Science, Harper Adams University"
  - family-names: "Butler"
    given-names: "Matthew"
    affiliation: "Centre for Agricultural Data Science, Harper Adams University"
  title: "Yolo Mark Utility: Software to create training datasets for Yolo"
  year: 2023  # Update to your publication year
  url: "https://github.com/yolo_mark_utility"
  doi: "10.5281/zenodo.10853601"
  publisher: "Centre for Agricultural Data Science, Harper Adams University"
  notes: "Yolo Mark Utility, open software to aid creating yolo training data using a webcam"

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