webknossos 0.15.3

Description:

webknossos 0.15.3

WEBKNOSSOS Python Library





Python API for working with WEBKNOSSOS datasets, annotations, and for WEBKNOSSOS server interaction.
For the WEBKNOSSOS server, please refer to https://github.com/scalableminds/webknossos.
Features

easy-to-use dataset API for reading/writing/editing raw 2D/3D image data and volume annotations/segmentation in WEBKNOSSOS wrap (*.wkw) format

add/remove layers
update metadata (datasource-properties.json)
up/downsample layers
compress layers
add/remove magnifications
execute any of the wkCuber operations from your code


manipulation of WEBKNOSSOS skeleton annotations (*.nml) as Python objects

access to nodes, comments, trees, bounding boxes, metadata, etc.
create new skeleton annotation from Graph structures or Python objects


interaction, connection & scripting with your WEBKNOSSOS instance over the REST API

up- & downloading annotations and datasets



Please refer to the documentation for further instructions.
Installation
The webknossos package requires at least Python 3.8.
You can install it from pypi, e.g. via pip:
pip install webknossos

By default webknossos can only distribute any computations through multiprocessing or Slurm. For Kubernetes or Dask install these additional dependencies:
pip install cluster_tools[kubernetes]
pip install cluster_tools[dask]

Examples
See the examples folder or the the documentation.
The dependencies for the examples are not installed by default. Use poetry install --with examples to install them.
Contributions & Development
Please see the respective documentation page.
The development dependencies not installed by default. Use poetry install --with dev to install them.
License
AGPLv3
Copyright scalable minds
Test Data Credits
Excerpts for testing purposes have been sampled from:

Dow Jacobo Hossain Siletti Hudspeth (2018). Connectomics of the zebrafish's lateral-line neuromast reveals wiring and miswiring in a simple microcircuit. eLife. DOI:10.7554/eLife.33988
Zheng Lauritzen Perlman Robinson Nichols Milkie Torrens Price Fisher Sharifi Calle-Schuler Kmecova Ali Karsh Trautman Bogovic Hanslovsky Jefferis Kazhdan Khairy Saalfeld Fetter Bock (2018). A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster. Cell. DOI:10.1016/j.cell.2018.06.019. License: CC BY-NC 4.0
Bosch Ackels Pacureanu et al (2022). Functional and multiscale 3D structural investigation of brain tissue through correlative in vivo physiology, synchrotron microtomography and volume electron microscopy. Nature Communications. DOI:10.1038/s41467-022-30199-6
Hanke, M., Baumgartner, F. J., Ibe, P., Kaule, F. R., Pollmann, S., Speck, O., Zinke, W. & Stadler, J. (2014). A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Scientific Data, 1:140003. DOI:10.1038/sdata.2014.3
Sample OME-TIFF files (c) by the OME Consortium https://downloads.openmicroscopy.org/images/OME-TIFF/2016-06/bioformats-artificial/