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Implementation of next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.

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ome-zarr-py

Experimental support for multi-resolution images stored in Zarr filesets, according to the OME zarr spec.

Features

  • Use as a image reader plugin for napari. See napari-ome-zarr.
  • Simple command-line to read and download conforming Zarr filesets.
  • Helper methods for parsing related metadata.

Installation

Install the latest release of ome-zarr from PyPI:

pip install ome-zarr

Install developer mode to run from your current branch:

git clone [email protected]:ome/ome-zarr-py.git
cd ome-zarr-py
pip install -e .

Usage

Open Zarr filesets containing images with associated OME metadata. The examples below use the image at http://idr.openmicroscopy.org/webclient/?show=image-6001240.

All examples can be made more or less verbose by passing -v or -q one or more times:

# ome_zarr -vvv ...

info

Use the ome_zarr command to interrogate Zarr datasets:

# Remote data
$ ome_zarr info https://uk1s3.embassy.ebi.ac.uk/idr/zarr/v0.1/6001240.zarr/

# Local data (after downloading as below)
$ ome_zarr info 6001240.zarr/

download

To download all the resolutions and metadata for an image:

# creates local 6001240.zarr/
$ ome_zarr download https://uk1s3.embassy.ebi.ac.uk/idr/zarr/v0.1/6001240.zarr/

# Specify output directory
$ ome_zarr download https://uk1s3.embassy.ebi.ac.uk/idr/zarr/v0.1/6001240.zarr/ --output image_dir

csv to labels

The csv_to_labels command uses a CSV file to add key:value properties to labels under an OME-Zarr Image or Plate.

The OME-Zarr labels metadata must already contain a properties list of {key:value} objects, each with a unique key:ID. This key is omero:shapeId in the example below.

This ID can be used to identify a single row of the CSV table by specifying the name of a column with unique values, e.g. shape_id below. This row is used to add additional column_name:value data to the label properties.

You also need to specify which columns from the CSV to use, e.g. "area,X,Y,Width,Height". You can also specify the column types (as in https://github.com/ome/omero-metadata/) to specify the data-type for each column (string by default).

  • d: DoubleColumn, for floating point numbers
  • l: LongColumn, for integer numbers
  • s: StringColumn, for text
  • b: BoolColumn, for true/false

Use e.g. #d as a suffix in the column name to denote a float column, no spaces etc.: ` "area#d,label_text#s,Width#l,Height#l" `

For example, to take values from columns named area, label_text, Width and Height within a CSV file named labels_data.csv with an ID column named shape_id and add these values to label properties with an ID key of omero:shapeId in an Image or Plate named 123.zarr:

ome_zarr csv_to_labels labels_data.csv shape_id "area#d,label_text#s,Width#l,Height#l" 123.zarr omero:shapeId```

Release process

This repository uses bump2version to manage version numbers. To tag a release run:

$ bumpversion release

This will remove the .dev0 suffix from the current version, commit, and tag the release.

To switch back to a development version run:

$ bumpversion --no-tag [major|minor|patch]

specifying major, minor or patch depending on whether the development branch will be a major, minor or patch release. This will also add the .dev0 suffix.

Remember to git push all commits and tags.

License

Distributed under the terms of the BSD license, "ome-zarr-py" is free and open source software

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