WEBKNOSSOS CLI¶

Python CLI for creating and working with WEBKNOSSOS WKW or Zarr datasets. WKW is a container format for efficiently storing large, scale 3D image data as found in (electron) microscopy. Zarr is a community-driven, cloud-native data format for n-dimensional datasets.

Installation¶

To install and run the WEBKNOSSOS CLI the webknossos package is required. Please refer to the Installation Guide for detailed instructions.

Features¶

The WEBKNOSSOS CLI offers many useful commands to work with WEBKNOSSOS datasets:

webknossos compress: Compress a WEBKNOSSOS dataset
webknossos convert: Convert an image stack (e.g., tiff, jpg, png, bmp, dm3, dm4) to a WEBKNOSSOS dataset
webknossos convert-knossos: Converts a KNOSSOS dataset to a WEBKNOSSOS dataset
webknossos convert-raw: Converts a RAW image file to a WEBKNOSSOS dataset
webknossos convert-zarr: Converts a Zarr dataset to a WEBKNOSSOS dataset
webknossos copy-dataset: Makes a copy of a WEBKNOSSOS dataset
webknossos download: Download a dataset from a WEBKNOSSOS server
webknossos downsample: Downsample a WEBKNOSSOS dataset
webknossos merge-fallback: Merge a volume layer of a WEBKNOSSOS dataset with an annotation
webknossos upload: Upload a local WEBKNOSSOS dataset to a remote location
webknossos upsample: Upsample a WEBKNOSSOS dataset
webknossos export-as-tiff: Export a part of a WEBKNOSSOS dataset as a TIFF sequence

Environment Variables¶

To get access to services that require authentication, you can set the environment variables:

WK_TOKEN
WK_URL
AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
S3_ENDPOINT_URL
HTTP_BASIC_USER
HTTP_BASIC_PASSWORD

Parallelization¶

Most tasks can be configured to be executed in a parallelized manner. Via --distribution-strategy you can pass multiprocessing, slurm or kubernetes. The first can be further configured with --jobs and the latter via --job-resources '{"mem": "10M"}'. For a more detailed overview take a look at our distribution strategies page.

License¶

AGPLv3 Copyright scalable minds