Repository of the paper "AnyUp: Universal Feature Upsampling".

Hiera: A fast, powerful, and simple hierarchical vision transformer.

Reference PyTorch implementation and models for DINOv3

Official code for "No time to train! Training-Free Reference-Based Instance Segmentation"

A tool for cell instance aware segmentation in densely packed 3D volumetric images

ilastik-shell, applets, and workflows to string them together.

Python project containing Ice remoting code for OMERO

Next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.

Implementation of next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.

Distributed segmentation for bio-image-analysis

Affinity based segmentation algorithms and tools

napari: a fast, interactive, multi-dimensional image viewer for python

An implementation of chunked, compressed, N-dimensional arrays for Python.

Repository of scripts to facilitate participation in CellMap's segmentation challenge. This includes downloading data, simple setups for training 2D and 3D models, workflows for prediction and post…

Transformer-based cell tracking for live-cell microscopy

QuPath extension for Segment Anything Model (SAM)

Browse your OMERO database from within napari.

Deep learning-based image analysis for cochleae imaged in light-sheet microscopy

A napari plugin for making image annotation using feature space of vision transformers and Random Forest classifier

A nifty library for graph based image segmentation.

Accurate and efficient spot detection for microscopy data

Collaborative image annotation and model training with human in the loop

Segment Anything for Histopathology

Parameter Efficient Fine-Tuning of Segment Anything Model

Segment Anything for Medical Imaging

Tool for robust segmentation of >100 important anatomical structures in CT and MR images

Reconstruction of synaptic structures in electron microscopy

Multi-Object Tracker using Integer Linear Equations

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…