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Simplify camera trap image analysis with ML species recognition models based around the MegaDetector model

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arky/EcoAssist

 
 

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status Project Status: Active The project has reached a stable, usable state and is being actively developed. GitHub GitHub last commit


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

@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

@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}
}

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
# All users
─── 📁Program Files
    └── 📁EcoAssist_files

# Single user
─── 📁Users
    └── 📁<username>
        └── 📁EcoAssist_files
Location on macOS
─── 📁Applications
    └── 📁.EcoAssist_files
Location on Linux
─── 📁home
    └── 📁<username>
        └── 📁.EcoAssist_files

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Simplify camera trap image analysis with ML species recognition models based around the MegaDetector model

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  • Python 73.3%
  • Shell 13.9%
  • Batchfile 12.8%