https://github.com/bencevans/megadetector-desktop

MegaDetector Desktop: Simple Interface for Detection of Humans, Animals and Vehicles in Camera Trap Imagery

https://github.com/bencevans/megadetector-desktop

Science Score: 10.0%

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

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    1 of 2 committers (50.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.6%) to scientific vocabulary

Keywords

camera-traps wildlife-conservation

Keywords from Contributors

cameratrap
Last synced: 6 months ago · JSON representation

Repository

MegaDetector Desktop: Simple Interface for Detection of Humans, Animals and Vehicles in Camera Trap Imagery

Basic Info
  • Host: GitHub
  • Owner: bencevans
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.79 MB
Statistics
  • Stars: 3
  • Watchers: 3
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Archived
Topics
camera-traps wildlife-conservation
Created almost 4 years ago · Last pushed about 3 years ago
Metadata Files
Readme Contributing

README.md

:warning: The MegaDetector Desktop Project has been superseded by the CamTrap Detector project. :warning:

MegaDetector Desktop

Warning: MegaDetector Desktop is currently considered alpha software. Expect bugs and crashes, and please report them on the GitHub repository. For a more stable CLI utility, see the Microsoft/CameraTraps MegaDetector Scripts.

MegaDetector Desktop Splash Image

Install

MegaDetector Desktop is currently available for Windows (x64) and MacOS (Intel). Latest versions can be found on the releases page.

Citation

If you use MegaDetector Desktop in your research, please cite the original MegaDetector work:

@article{beery2019efficient, 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} }

https://github.com/microsoft/CameraTraps/blob/main/megadetector.md#citing-megadetector

Furthermore, if you use MegaDetector Desktop in your research, please cite the MegaDetector Desktop project:

TODO

Development

Details on development and building can be found in CONTRIBUTING.md.

License

MIT

Owner

  • Name: Ben Evans
  • Login: bencevans
  • Kind: user
  • Location: London, UK
  • Company: Institute of Zoology, ZSL

GitHub Events

Total
Last Year

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 51
  • Total Committers: 2
  • Avg Commits per committer: 25.5
  • Development Distribution Score (DDS): 0.02
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Ben Evans b****n@b****o 50
Ben Evans B****s@b****k 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 8
  • Total pull requests: 10
  • Average time to close issues: 4 months
  • Average time to close pull requests: 6 days
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.38
  • Average comments per pull request: 0.0
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • bencevans (8)
Pull Request Authors
  • bencevans (10)
Top Labels
Issue Labels
good first issue (4) enhancement (4)
Pull Request Labels

Dependencies

.github/workflows/build-mac.yml actions
  • actions/checkout v3 composite
  • actions/upload-artifact v3 composite
  • conda-incubator/setup-miniconda v2 composite
.github/workflows/build-windows.yml actions
  • actions/checkout v3 composite
  • actions/upload-artifact v3 composite
  • conda-incubator/setup-miniconda v2 composite
environment.yml conda
  • pip
  • pyinstaller
  • python >=3.9
  • tensorflow