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Open Source Science

ecoassist-experiments

https://github.com/petervanlunteren/ecoassist-experiments

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 7 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: arxiv.org, joss.theoj.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: PetervanLunteren
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 126 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 166
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme Contributing Funding License Code of conduct Citation Zenodo

README.md

[![status](https://joss.theoj.org/papers/dabe3753aae2692d9908166a7ce80e6e/status.svg)](https://joss.theoj.org/papers/dabe3753aae2692d9908166a7ce80e6e) [![Project Status: Active The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active) ![GitHub](https://img.shields.io/github/license/PetervanLunteren/EcoAssist) ![GitHub last commit](https://img.shields.io/github/last-commit/PetervanLunteren/EcoAssist)
[![](https://img.shields.io/static/v1?label=Sponsor&message=%E2%9D%A4&logo=GitHub&color=%23fe8e86)](https://github.com/sponsors/PetervanLunteren)

Official website: https://addaxdatascience.com/ecoassist/

EcoAssist is an application designed to streamline the work of ecologists dealing with camera trap images. It’s an AI platform that allows you to analyse images with machine learning models for automatic detection, offering ecologists a way to save time and focus on conservation efforts.

Cite

Please use the following citations if you used EcoAssist in your research.

EcoAssist
[Link to paper](https://joss.theoj.org/papers/10.21105/joss.05581) ```BibTeX @article{van_Lunteren_EcoAssist_2023, author = {van Lunteren, Peter}, doi = {10.21105/joss.05581}, journal = {Journal of Open Source Software}, month = aug, number = {88}, pages = {5581}, title = {{EcoAssist: A no-code platform to train and deploy custom YOLOv5 object detection models}}, url = {https://joss.theoj.org/papers/10.21105/joss.05581}, volume = {8}, year = {2023} } ```
MegaDetector
[Link to paper](https://arxiv.org/abs/1907.06772) ```BibTeX @article{Beery_Efficient_2019, title = {Efficient Pipeline for Camera Trap Image Review}, author = {Beery, Sara and Morris, Dan and Yang, Siyu}, journal = {arXiv preprint arXiv:1907.06772}, year = {2019} } ```

Contribute

Interested in contributing to this project? There are always things to do. The list of to-do items, bug reports, and feature requests is always evolving. I try to keep a semi-structured list here. Is there something you would be interested in? Get in touch and I will guide you in the right direction. Thanks!

Uninstall

All files are located in one folder, called EcoAssist_files. You can uninstall EcoAssist by simply deleting this folder. Please be aware that it's hidden, so you'll probably have to adjust your settings before you can see it (find out how to: macOS, Windows, Linux). If you're planning on updating EcoAssist, there is no need to uninstall it first. It will do that automatically.

Location on Windows
```r # All users ─── 📁Program Files └── 📁EcoAssist_files # Single user ─── 📁Users └── 📁 └── 📁EcoAssist_files ```
Location on macOS
```r ─── 📁Applications └── 📁.EcoAssist_files ```
Location on Linux
```r ─── 📁home └── 📁 └── 📁.EcoAssist_files ```

Owner

  • Name: Peter van Lunteren
  • Login: PetervanLunteren
  • Kind: user
  • Location: Utrecht, NL

Wildlife ecologist and data scientist with a special interest in ML

Citation (citation.cff) 

cff-version: "1.2.0"
authors:
- family-names: Lunteren
  given-names: Peter
  name-particle: van
  orcid: "https://orcid.org/0000-0001-5488-4225"
doi: 10.5281/zenodo.7223363
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Lunteren
    given-names: Peter
    name-particle: van
    orcid: "https://orcid.org/0000-0001-5488-4225"
  date-published: 2023-08-04
  doi: 10.21105/joss.05581
  issn: 2475-9066
  issue: 88
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 5581
  title: "EcoAssist: A no-code platform to train and deploy custom
    YOLOv5 object detection models"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.05581"
  volume: 8
title: "EcoAssist: A no-code platform to train and deploy custom YOLOv5
  object detection models"

GitHub Events

Total
  • Release event: 151
  • Push event: 389
  • Create event: 154
Last Year
  • Release event: 151
  • Push event: 389
  • Create event: 154

Dependencies

.github/workflows/github-repo-stats.yml actions
  • jgehrcke/github-repo-stats RELEASE composite