animl-py

Includes a set of functions to classify subjects within camera trap field data and can handle both images and videos.
https://github.com/conservationtechlab/animl-py

Category: Biosphere
Sub Category: Terrestrial Wildlife

Last synced: about 16 hours ago
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Repository metadata

Animl comprises a variety of machine learning tools for analyzing ecological data. This Python package includes a set of functions to classify subjects within camera trap field data and can handle both images and videos.


Owner metadata


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Committers metadata

Last synced: 6 days ago

Total Commits: 738
Total Committers: 14
Avg Commits per committer: 52.714
Development Distribution Score (DDS): 0.205

Commits in past year: 355
Committers in past year: 6
Avg Commits per committer in past year: 59.167
Development Distribution Score (DDS) in past year: 0.155

Name Email Commits
Kyra Swanson t****n@g****m 587
mamani828 m****1@g****m 33
copilot-swe-agent[bot] 1****t 24
jcampbell350 j****0@g****u 17
srinidhi98 s****y@g****m 16
Mathias Tobler m****r@g****t 15
unduwapk u****e@u****u 13
Peter van Lunteren c****t@p****m 12
ayush2725 6****5 10
Raine Wen 5****2 4
Mani m****i@R****g 3
Wani Sachin Gopal s****8@g****m 2
Nikita Sharma s****6@c****u 1
Katie Garwood k****d@s****g 1

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Issue and Pull Request metadata

Last synced: 12 days ago

Total issues: 93
Total pull requests: 167
Average time to close issues: 4 months
Average time to close pull requests: 4 days
Total issue authors: 10
Total pull request authors: 13
Average comments per issue: 0.17
Average comments per pull request: 0.13
Merged pull request: 114
Bot issues: 0
Bot pull requests: 0

Past year issues: 49
Past year pull requests: 73
Past year average time to close issues: 29 days
Past year average time to close pull requests: 2 days
Past year issue authors: 8
Past year pull request authors: 7
Past year average comments per issue: 0.14
Past year average comments per pull request: 0.05
Past year merged pull request: 49
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/conservationtechlab/animl-py

Top Issue Authors

  • tkswanson (70)
  • matobler (7)
  • jcampbell350 (3)
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  • kgarwoodsdzwa (3)
  • srinidhi98 (2)
  • iingram (2)
  • cyang406 (1)
  • nikitasharma768 (1)
  • sriraksharao (1)

Top Pull Request Authors

  • tkswanson (118)
  • ayush2725 (19)
  • Copilot (7)
  • Raindrop182 (4)
  • mamani828 (4)
  • srinidhi98 (4)
  • jcampbell350 (3)
  • abishop1990 (2)
  • PetervanLunteren (2)
  • unduwapk (1)
  • Sachin-Wani (1)
  • nikitasharma768 (1)
  • matobler (1)

Top Issue Labels

  • enhancement (11)
  • documentation (4)
  • bug (4)
  • api change (4)

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Package metadata

pypi.org: animl

A Collection of ML Tools for Species Detection and Classification in Camera Trap Images and Videos.

  • Homepage: https://github.com/conservationtechlab/animl-py
  • Documentation: https://animl.readthedocs.io/
  • Licenses: mit
  • Latest release: 3.3.0 (published 15 days ago)
  • Last Synced: 2026-06-12T03:01:20.198Z (12 days ago)
  • Versions: 27
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 420 Last month
  • Rankings:
    • Dependent packages count: 10.118%
    • Downloads: 20.076%
    • Dependent repos count: 21.552%
    • Average: 22.644%
    • Forks count: 22.649%
    • Stargazers count: 38.827%
  • Maintainers (2)
pypi.org: animl-lite

Tools for classifying camera trap images

  • Homepage: https://github.com/conservationtechlab/animl-py
  • Documentation: https://animl-lite.readthedocs.io/
  • Licenses: mit
  • Latest release: 3.2.1 (published 4 months ago)
  • Last Synced: 2026-06-12T03:01:20.203Z (12 days ago)
  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 91 Last month
  • Rankings:
    • Dependent packages count: 8.303%
    • Average: 27.619%
    • Dependent repos count: 46.934%
  • Maintainers (1)

Dependencies

pyproject.toml pypi
  • numpy ==1.26.4
  • onnxruntime-gpu ==1.19.2
  • opencv-python ==4.10.0.84
  • pandas ==2.2.2
  • pillow ==10.4.0
  • scikit-learn ==1.5.2
  • timm ==1.0.9
  • tqdm >=4.66.5
  • ultralytics ==8.3.95
  • wget >=3.2

Score: 12.492198507714647