ome-zarr-converters-tools

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A Python library that provides shared utilities for building OME-Zarr image converters. It handles tile management, image registration, filtering, validation, and writing OME-Zarr datasets.

Features

  1. Abstraction layer for building OME-Zarr images and HCS plates from microscope metadata and image data
  2. Customizable pipeline for filtering, validating, registering, and tiling images
  3. Python API for building custom converters, with optional Fractal integration for parallel processing
  4. Flexible input: parse tiles from DataFrames or construct them programmatically

Architecture Diagram

OME-Zarr Converters Tools Architecture

Getting Started

Install via pip:

pip install ome-zarr-converters-tools

For converting data stored on S3 (s3:// URLs), install the s3 extra:

pip install "ome-zarr-converters-tools[s3]"

Quickstart

Convert a tiles table (one row per tile: stage position, size, and image file) into a single OME-Zarr image:

import pandas as pd

from ome_zarr_converters_tools import (
    AcquisitionDetails,
    AutoTiling,
    ChannelInfo,
    ConverterOptions,
    OverwriteMode,
    StagePositionCorrections,
    WriterMode,
    build_default_registration_pipeline,
    single_images_from_dataframe,
    tiled_image_creation_pipeline,
    tiles_aggregation_pipeline,
)

acq = AcquisitionDetails(
    channels=[ChannelInfo(channel_label="DAPI")],
    xy_pixel_size=0.65,  # micrometers
    z_spacing=1.0,
)
tiles = single_images_from_dataframe(
    tiles_table=pd.read_csv("tiles.csv"), acquisition_details=acq
)
options = ConverterOptions()
tiled_image = tiles_aggregation_pipeline(
    tiles=tiles, converter_options=options, resource="/path/to/image/files"
)[0]
tiled_image_creation_pipeline(
    zarr_url="/path/to/output.zarr",
    tiled_image=tiled_image,
    registration_pipeline=build_default_registration_pipeline(
        StagePositionCorrections(), AutoTiling()
    ),
    converter_options=options,
    writer_mode=WriterMode.BY_FOV,
    overwrite_mode=OverwriteMode.NO_OVERWRITE,
    resource="/path/to/image/files",
)

See the tutorials for HCS plates, custom image loaders, and Fractal tasks.

Documentation

For detailed documentation, tutorials, and API reference, visit the official documentation.

The documentation includes:

Project links

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Credits

Author: Lorenzo Cerrone

GitHub Statistics

Data verified by PyPI on Aug 6, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

BSD License (BSD-3-Clause)

Requires

Python <3.15, >=3.11

Provides Extra

dev docs s3 test zarrs

Classifiers

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