https://github.com/PetervanLunteren/AddaxAI

Simplify camera trap image analysis with AI species recognition models based around the MegaDetector model
https://github.com/PetervanLunteren/AddaxAI

animals annotation-tool cameratraps classifier-model conservation deploy ecology linux machine-learning macos megadetector object-detection python windows yolov5

Last synced: about 10 hours ago
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Simplify camera trap image analysis with AI species recognition models based around the MegaDetector model

• Host: GitHub
• URL: https://github.com/PetervanLunteren/AddaxAI
• Owner: PetervanLunteren
• License: mit
• Created: 2022-01-29T13:43:22.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2025-04-13T23:01:51.000Z (8 days ago)
• Last Synced: 2025-04-14T14:01:45.218Z (7 days ago)
• Topics: animals, annotation-tool, cameratraps, classifier-model, conservation, deploy, ecology, linux, machine-learning, macos, megadetector, object-detection, python, windows, yolov5
• Language: Python
• Homepage: https://addaxdatascience.com/addaxai/
• Size: 123 MB
• Stars: 131
• Watchers: 11
• Forks: 19
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: citation.cff
  • Zenodo: .zenodo.json

Awesome Lists containing this project

• open-sustainable-technology - EcoAssist - An open-source application designed to streamline the work of ecologists dealing with camera trap images. (Biosphere / Terrestrial Wildlife)
• awesome-yolo-object-detection - PetervanLunteren/EcoAssist - code platform to train and deploy YOLOv5 object detection models. (Object Detection Applications)
• awesome-yolo-object-detection - PetervanLunteren/EcoAssist - code platform to train and deploy YOLOv5 object detection models. (Applications)

README

        



  





[![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/AddaxAI)

![GitHub last commit](https://img.shields.io/github/last-commit/PetervanLunteren/AddaxAI)



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[![](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/addaxai/






AddaxAI 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.



  

  

   

   



## Project name change

To avoid any legal concerns, we have renamed our project from EcoAssist to AddaxAI. The project itself remains the same—only the name has changed. 



  



## Cite AddaxAI in your research

If you used AddaxAI in your research, please include the following citation, along with the models used to analyze your data.

[Link to paper](https://joss.theoj.org/papers/10.21105/joss.05581)

```BibTeX

@article{van Lunteren2023,

  title = {AddaxAI: A no-code platform to train and deploy custom YOLOv5 object detection models},

  author = {Peter van Lunteren},

  journal = {Journal of Open Source Software},

  doi = {10.21105/joss.05581},

  url = {https://doi.org/10.21105/joss.05581},

  year = {2023},

  publisher = {The Open Journal},

  volume = {8},

  number = {88},

  pages = {5581}

}

```

## 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](https://github.com/PetervanLunteren/AddaxAI/blob/main/AddaxAI_GUI.py#L8). Is there something you would be interested in? [Get in touch](mailto:[email protected]) and I will guide you in the right direction. Thanks!