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>=3.11

  • Reads OME-Zarr v0.1 to v0.6 into simple Python data classes with Dask arrays

  • Optional OME-Zarr data model validation during reading

  • Writes OME-Zarr v0.4 to v0.6

  • v0.6 adds RFC-5 coordinate systems and transformations

  • Sharded Zarr stores

  • Zarr I/O backed by zarrista / Rust zarrs (Python) or zarrita (TypeScript) – no zarr-python dependency; OME-Zarr 0.4 (Zarr v2) outputs stay readable by zarr-python 2 and 3, and 0.5+ (Zarr v3) by zarr-python 3

  • Anatomical orientation metadata (RFC-4)

  • Coordinate systems and transformations (RFC-5)

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

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

  • TIFF/OME-TIFF support with automatic metadata extraction and multi-series conversion

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

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

🔀 Migration Guides

📖 Reference