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Python CLI for creating and working with WEBKNOSSOS WKW datasets. WKW is a container format for efficiently storing large, scale 3D image data as found in (electron) microscopy.


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 download: Download a dataset from a WEBKNOSSOS server as WKW format
  • 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

Supported input formats

  • Standard image formats, e.g. tiff, jpg, png, bmp
  • Proprietary image formats, e.g. dm3
  • Raw binary files


Python 3 with pip from PyPi

  • webknossos requires at least Python 3.8
pip install "webknossos[all]"

# to install auto completion as well use:
webknossos --install-completion


# Convert image stacks into wkw datasets
webknossos convert \
  --voxel-size 11.24,11.24,25 \
  --name great_dataset \
  data/source data/target

# Create downsampled magnifications
webknossos downsample data/target
webknossos downsample --layer-name color data/target

# Compress data in-place (mostly useful for segmentation)
webknossos compress data/target
webknossos compress data/target

# Convert Knossos cubes to wkw cubes
webknossos convert-knossos --layer-name color --voxel-size 11.24,11.24,25 data/source/mag1 data/target

# Convert RAW file to wkw file
webknossos convert-raw --layer-name color --voxel-size 10,10,30 --dtype uint8 --shape 2048,2048,1024 data/source/raw_file.raw data/target


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"}'. Use --help to get more information.


Make sure to install all the required dependencies using Poetry:

git clone

cd webknossos-libs
pip install -r requirements.txt

cd webknossos
poetry install --all-extras

Please, format, lint, typecheck and unit test your code changes before merging them.


Generate the API documentation

Run docs/ to open a server displaying the API docs. docs/ --persist persists the html to docs/api.


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