The Imageomics Institute GitHub organization hosts the development and distribution of a collection of open-source ML tools used to study the biological information encoded in images and videos integrated with structured biological knowledge. All Imageomics code, data, models, and demos hosted on GitHub or Hugging Face are searchable through the Imageomics Catalog:
What is the Imageomics Institute?
The Imageomics Institute is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under Award #2118240 (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning). It started in Oct 2021.
You can find a full mission, vision, and abstract under the Imageomics website's About page. In short, the vision of the Institute is to "establish a new scientific field called imageomics that harnesses revolutions in data science and computing, as well as the rapidly expanding collections of biological image data, in order to accelerate biological understanding of phenotypic traits extracted from images of organisms."
History leading to the Institute
History
The inception and research of the Imageomics Institute builds heavily on the "Biology-Guided Neural Networks for Discovering Phenotypic Traits" (BGNN) project, also funded by the US National Science Foundation. BGNN itself built in part on the Phenoscape project (funded by NSF multiple times), which started in 2007 and was incubated at the NSF-funded National Evolutionary Synthesis Center (NESCent).
Imageomics repositories held at predecessor organizations
Due to the history (see above) and highly collaborative and cross-disciplinary nature of the Institute, important software products and other code repositories are distributed over several organizations in GitHub, in addition to the ones found here. These early imageomics projects are listed and linked below under their organizations.
Disclaimer: Any opinions, findings and conclusions or recommendations expressed in the materials here are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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 ext…
Official repo for paper "Static Segmentation by Tracking: A Label-Efficient Approach to Fine-Grained Segmentation". Ideal for specimen image trait segmentation.
Python package to collect key info (Name, description, creation date, last updated date, contributors, etc.) from all repos in a GitHub or Hugging Face organization and save it to a color-coded Google Sheet file of choice.
Web-based tool for generating consistent CITATION.cff and .zenodo.json files from a single structured input form, reducing metadata inconsistencies across research releases.
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.
Catalog app for Imageomics code, data, models, and spaces hosted on GitHub and Hugging Face. Designed for improved discoverability of Imageomics products, the content is updated in real-time through calls to the GitHub and Hugging Face APIs. This repository also serves as a template for others looking to create a similar website.
This work presents a modular software pipeline and end-to-end workflow for video-based animal re-identification, which assigns consistent individual IDs by clustering multiview spatio-temporal tracks with minimal human intervention.
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