Reverse Dependencies of ome-zarr

The following projects have a declared dependency on ome-zarr:

• acquire-imaging — no summary
• acquire-zarr — Performant streaming to Zarr storage, on filesystem or cloud
• aicsimageio — Image Reading, Metadata Conversion, and Image Writing for Microscopy Images in Pure Python
• aicsimageprocessing — A generalized scientific image processing module from the Allen Institute for Cell Science.
• aind-data-transfer — Services for compression and transfer of aind-data to the cloud
• aind-large-scale-prediction — Generated from aind-library-template
• apx-fractal-task-collection — A collection of custom fractal tasks.
• bellavista — Python package for interactive visualization of imaging-based spatial transcriptomics.
• bfio — Simple reading and writing classes for tiled tiffs using Bio-Formats.
• bia-explorer — no summary
• bioio — Image reading, metadata management, and image writing for Microscopy images in Python
• bioio-ome-zarr — A BioIO reader plugin for reading Zarr files in the OME format.
• brainglobe-stitch — A tool to stich large tiled datasets generated by the mesoSPIM.
• brainlit — Code to process and analyze brainlit data
• copick — Definitions for a collaborative cryoET annotation tool.
• cvpl-tools — A Python package for utilities and classes related to the file I/O, dataset record keeping and visualization for image processing and computer vision.
• cyto-dl — Collection of representation learning models, techniques, callbacks, utils, used to create latent variable models of cell shape, morphology and intracellular organization.
• czitools — Tools to simplify reading CZI (Carl Zeiss Image) meta and pixel data
• dexp — Light-sheet Dataset EXploration and Processing
• faim-ipa — Tools used at FMI-FAIM for Image Processing and Analysis.
• glue-genes — Multidimensional data visualization for genomics
• harpy-analysis — single-cell spatial proteomics analysis that makes you happy
• iohub — N-dimensional bioimaging data I/O with OME metadata in Python
• liom-toolkit — Package to support the research of LIOM.
• mcd2zarr — Command line tool to convert MCD files to Zarr
• mrc2omezarr — Command line tool to convert MRC-files to OME-Zarr.
• multiview-stitcher — Registration and fusion of large imaging datasets in 2D and 3D.
• mysquishy — Recompress zarr chunks in-place
• napari-activelearning — An active learning plugin for fine tuning of deep learning models.
• napari-chatgpt — A napari plugin to process and analyse images with chatGPT.
• napari-file-watcher — A napari plugin for file watching
• napari-ome-zarr — A reader for zarr backed OME-NGFF images.
• napari-ome-zarr-navigator — A plugin to browse OME-Zarr plates by conditions and load images, labels and features from ROIs
• napari-sentinel-to-zarr — Writer plugin for napari to save Sentinel tiffs into ome-zarr format
• nViz — A tool for creating and visualizing n-dimensional microscopy images.
• ome2glancer — A package that generates neuroglancer links for ome-zarr files.
• omero-cli-zarr — Plugin for exporting images in zarr format.
• openst — The computational pipeline for the Open-ST method.
• operetta-compose — Fractal tasks for the Opera/Operetta microscope and drug response profiling
• raw2tmap — Convert OME-Zarr files to TMAP format
• scportrait — Computational framework to generate single cell datasets from raw microscopy images.
• serotiny — A framework of tools to structure, configure and drive deep learning projects
• spatialdata — Spatial data format.
• stars-omics — A spatial transcriptomics analysis tool.
• tiledb-bioimg — Package supports all bio-imaging functionality provided by TileDB
• ufish — Deep learning based spot detection for FISH images.
• ultrack — Large-scale multi-hypotheses cell tracking
• vitessce — Jupyter widget facilitating interactive visualization of spatial single-cell data with Vitessce
• zarrnii — Package for working with OME-Zarr and NIFTI images in a unified manner, with a focus on spatial transformations