Imageomics/bioclip-2
Repository for the BioCLIP 2 model project. [NeurIPS'25 Spotlight] BioCLIP 2 is a biological foundation model trained on TreeOfLife-200M. Despite the narrow training objective, BioCLIP 2 yields extraordinary accuracy when applied to various biological visual tasks such as habitat classification and trait prediction.
This project helps biologists, ecologists, and conservationists automatically analyze images of living organisms. By taking an image of a plant or animal, it can identify the species, classify its habitat, or predict its traits. This is useful for researchers who need to process large volumes of biological imagery for various tasks, from biodiversity monitoring to ecological studies.
Use this if you need highly accurate, automated classification and analysis of biological images, especially for species identification or trait prediction across diverse biological visual tasks.
Not ideal if your image analysis needs are outside of biological organisms or if you require image generation capabilities rather than classification and understanding.
Stars
55
Forks
9
Language
Python
License
—
Category
Last pushed
Mar 19, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/Imageomics/bioclip-2"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
PytorchConnectomics/pytorch_connectomics
PyTorch Connectomics: segmentation toolbox for EM connectomics
segments-ai/segments-ai
Segments.ai Python SDK
afermg/cp_measure
Morphological features from images and masks made easy.
oarriaga/paz
Hierarchical perception library in Python for pose estimation, object detection, instance...
JdeRobot/PerceptionMetrics
A toolkit designed to unify and streamline the evaluation of object detection and segmentation...