ome-zarr-converters-tools
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
- Abstraction layer for building OME-Zarr images and HCS plates from microscope metadata and image data
- Customizable pipeline for filtering, validating, registering, and tiling images
- Python API for building custom converters, with optional Fractal integration for parallel processing
- Flexible input: parse tiles from DataFrames or construct them programmatically
Architecture Diagram
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:
- HCS Plate Tutorial -- converting plate-based microscopy data
- Single Images Tutorial -- converting standalone images
- Advanced Tutorial -- programmatic tile construction with custom loaders
- Fractal Tasks Guide -- building parallel converters with the Fractal platform
- Pipeline Configuration -- filters, registration, tiling, and writer modes
- API Reference
1 maintainer
Release files for ome-zarr-converters-tools 1.0.2
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| ome_zarr_converters_tools-1.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 27.1 MB
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