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ngff-zarr
A lean and kind Open Microscopy Environment (OME) Next Generation File Format (NGFF) Zarr implementation.
Table of Contents
Installation
To install the command line interface (CLI):
pip install 'ngff-zarr[cli]'
Features
- Minimal dependencies
- Work with arbitrary Zarr store types
- Lazy, parallel, and web ready -- no local filesystem required
- Process extremely large datasets
- Multiple downscaling methods
- Supports Python>=3.7
- Implements version 0.4 of the OME-Zarr NGFF specification
Usage
Convert an image file
Convert any scientific image file format supported by either itk, tifffile, or imageio.
Example:
ngff-zarr -i ./MR-head.nrrd -o ./MR-head.zarr
Convert an image volume slice series
Note the quotes:
ngff-zarr -i "series/*.tif" -o ome-ngff.zarr
Print information about generated multiscales
To print information about the input, omit the output argument.
ngff-zarr -i ./MR-head.nrrd
Specify output chunks
ngff-zarr -c 64 -i ./MR-head.nrrd
Specify metadata
ngff-zarr --dims "z" "y" "x" --scale x 1.4 y 1.4 z 2.5 --translation x 6.24 y 360.0 z 332.5 --name LIDC2 -i "series/*.tif"
Limit memory consumption
Limit memory consumption by passing a rough memory limit in human-readable units, e.g. 8GB with the --memory-target option.
ngff-zarr --memory-target 50M -i ./LIDCFull.vtk -o ./LIDCFull.zarr
More options
ngff-zarr --help
See also
License
ngff-zarr is distributed under the terms of the MIT license.
Development
Contributions are welcome and appreciated.
To run the unit tests:
pip install -e ".[test,dask-image,itk,cli]"
pytest
Updating test data
- Generate new test data tarball
cd test/data
tar cvf ../data.tar baseline input
gzip -9 ../data.tar
-
Upload the data to web3.storage
-
Upload the
test_data_ipfs_cid(from web3.storage web UI) andtest_data_sha256(sh256sum ../data.tar.gz) variables in test/_data.py.
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