Skip to main content

Python package that simplifies using the BioCLIP foundation model.

Project description

pybioclip

PyPI - Version PyPI - Python Version


Command line tool and python package to simplify using BioCLIP, including for taxonomic or other label prediction on (and thus annotation or labeling of) images, as well as for generating semantic embeddings for images. No particular understanding of ML or computer vision is required to use it. It also implements a number of performance optimizations for batches of images or custom class lists, which should be particularly useful for integration into computational workflows.

Documentation

See the pybioclip documentation website for requirements, installation instructions, and tutorials.

License

pybioclip is distributed under the terms of the MIT license.

Citation

Our code (this repository):

@software{Bradley_pybioclip_2025,
author = {Bradley, John and Lapp, Hilmar and Campolongo, Elizabeth G.},
doi = {10.5281/zenodo.13151194},
month = feb,
title = {{pybioclip}},
version = {1.3.0},
year = {2025}
}

BioCLIP paper:

@inproceedings{stevens2024bioclip,
  title = {{B}io{CLIP}: A Vision Foundation Model for the Tree of Life}, 
  author = {Samuel Stevens and Jiaman Wu and Matthew J Thompson and Elizabeth G Campolongo and Chan Hee Song and David Edward Carlyn and Li Dong and Wasila M Dahdul and Charles Stewart and Tanya Berger-Wolf and Wei-Lun Chao and Yu Su},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024}
}

Also consider citing the BioCLIP code:

@software{bioclip2023code,
  author = {Samuel Stevens and Jiaman Wu and Matthew J. Thompson and Elizabeth G. Campolongo and Chan Hee Song and David Edward Carlyn},
  doi = {10.5281/zenodo.10895871},
  title = {BioCLIP},
  version = {v1.0.0},
  year = {2024}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pybioclip-1.3.0.tar.gz (2.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pybioclip-1.3.0-py3-none-any.whl (13.1 kB view details)

Uploaded Python 3

File details

Details for the file pybioclip-1.3.0.tar.gz.

File metadata

  • Download URL: pybioclip-1.3.0.tar.gz
  • Upload date:
  • Size: 2.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.8

File hashes

Hashes for pybioclip-1.3.0.tar.gz
Algorithm Hash digest
SHA256 acb0f5cde460a1eca6eb61084dce6c07479843c8b2f100df914eff5914a8548e
MD5 bc9f617bf6ab4eb2b3032c18e9fbcd02
BLAKE2b-256 106f7cf08e6e090eec518fd604389c43d1cab22e0c127117c10e30c5d2728beb

See more details on using hashes here.

File details

Details for the file pybioclip-1.3.0-py3-none-any.whl.

File metadata

  • Download URL: pybioclip-1.3.0-py3-none-any.whl
  • Upload date:
  • Size: 13.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.8

File hashes

Hashes for pybioclip-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fc07d2af6cda51a65a0eb949a3bd073f8b80d5c2c43c6c6163404ec0ef524cc6
MD5 102bd50f623d539fbb5fb6a05e0f3679
BLAKE2b-256 c40542c20120c6f09b7cde23085b14cdfd59475dbf20f563e8b70fd568b5d427

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page