ngff-zarr

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A lean and kind Open Microscopy Environment (OME) Next Generation File Format (NGFF) Zarr implementation, OME-Zarr.

✨ Features

  • Minimal dependencies

  • Work with arbitrary Zarr store types

  • Lazy, parallel, and web ready – no local filesystem required

  • Process extremely large datasets

  • Conversion of most bioimaging file formats

  • Multiple downscaling methods

  • Supports Python>=3.10

  • Reads OME-Zarr v0.1 to v0.5 into simple Python data classes with Dask arrays

  • Optional OME-Zarr data model validation during reading

  • Writes OME-Zarr v0.4 to v0.5

  • Sharded Zarr stores

  • Optional writing via zarr-python 2, zarr-python 3, tensorstore or zarrita (TypeScript)

  • Anatomical orientation metadata (RFC-4)

  • OME-Zarr Zip (.ozx) file support for single-file OME-Zarr datasets (RFC-9)

  • High Content Screening (HCS) support for plate and well data

  • Leica Image Format (LIF) support for Leica microscopy data

  • Model Context Protocol (MCP) server for AI agent integration

📖 Reference