Zamba
A Python package for identifying hundreds of kinds of animals, training custom models, and estimating distance from camera trap videos and images.
https://github.com/drivendataorg/zamba
Category: Biosphere
Sub Category: Terrestrial Wildlife
Keywords
animals camera-traps chimps cli conservation deep-learning ecology gpu images jungle machine-learning neural-network python pytorch pytorch-lightning video-processing videos
Last synced: about 19 hours ago
JSON representation
Repository metadata
A Python package for identifying hundreds of kinds of animals, training custom models, and estimating distance from camera trap videos and images
- Host: GitHub
- URL: https://github.com/drivendataorg/zamba
- Owner: drivendataorg
- License: mit
- Created: 2018-03-06T23:18:46.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2026-02-16T06:50:22.000Z (2 months ago)
- Last Synced: 2026-02-16T09:33:49.413Z (2 months ago)
- Topics: animals, camera-traps, chimps, cli, conservation, deep-learning, ecology, gpu, images, jungle, machine-learning, neural-network, python, pytorch, pytorch-lightning, video-processing, videos
- Language: Python
- Homepage: https://zamba.drivendata.org/docs/stable/
- Size: 83.4 MB
- Stars: 148
- Watchers: 15
- Forks: 35
- Open Issues: 63
- Releases: 0
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Metadata Files:
- Readme: README.md
- Changelog: HISTORY.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 35 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 4
- Total maintainers: 1
pypi.org: zamba
Zamba is a tool to identify the species seen in camera trap videos from sites in central Africa.
- Homepage: http://zamba.drivendata.org
- Documentation: http://zamba.drivendata.org/docs/
- Licenses: MIT License
- Latest release: 0.1.6 (published almost 8 years ago)
- Last Synced: 2026-03-27T07:52:26.270Z (about 1 month ago)
- Versions: 4
- Dependent Packages: 0
- Dependent Repositories: 1
- Downloads: 35 Last month
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Rankings:
- Dependent packages count: 7.373%
- Stargazers count: 7.995%
- Forks count: 9.37%
- Dependent repos count: 22.233%
- Average: 23.571%
- Downloads: 70.883%
- Maintainers (1)
Score: 8.962776046120291