ngio 0.5.10

Next Generation file format IO

ngio - Next Generation file format IO

ngio is a Python library designed to simplify bioimage analysis workflows, offering an intuitive interface for working with OME-Zarr files.

What is ngio?

ngio is built for the OME-Zarr file format, a modern, cloud-optimized format for biological imaging data. OME-Zarr stores large, multi-dimensional microscopy images and metadata in an efficient and scalable way.

ngio's mission is to streamline working with OME-Zarr files by providing a simple, object-based API for opening, exploring, and manipulating OME-Zarr images and high-content screening (HCS) plates. It also offers comprehensive support for labels, tables and regions of interest (ROIs), making it easy to extract and analyze specific regions in your data.

Key Features

🔍 Simple Object-Based API

• Easily open, explore, and manipulate OME-Zarr images and HCS plates
• Create and derive new images and labels with minimal boilerplate code

📊 Rich Tables and Regions of Interest (ROI) Support

• Tight integration with tabular data
• Extract and analyze specific regions of interest
• Store measurements and other metadata in the OME-Zarr container
• Extensible & modular allowing users to define custom table schemas and on disk serialization

🔄 Scalable Data Processing

• Powerful iterators for building scalable and generalizable image processing pipelines
• Extensible mapping mechanism for custom parallelization strategies

Installation

You can install ngio via pip:

pip install ngio

To get started check out the Quickstart Guide.

Supported OME-Zarr versions

ngio supports OME-Zarr v0.4/v0.5. Support for version 0.6 and higher is planned for future releases.

Development Status

ngio is under active development and is not yet stable. The API is subject to change, and bugs and breaking changes are expected. We follow Semantic Versioning. Which means for 0.x releases potentially breaking changes can be introduced in minor releases.

Available Features

• ✅ OME-Zarr metadata handling and validation
• ✅ Image and label access across pyramid levels
• ✅ ROI and table support
• ✅ Image processing iterators
• ✅ Streaming from remote sources
• ✅ Documentation and examples

Upcoming Features

• Enhanced performance optimizations (parallel iterators, optimized io strategies)

Contributors

ngio is developed at the BioVisionCenter, University of Zurich, by @lorenzocerrone and @jluethi.

License

ngio is released under the BSD-3-Clause License. See LICENSE for details.