Python API for working with WEBKNOSSOS datasets, annotations, and for WEBKNOSSOS server interaction.
Project description
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
wkCuberoperations 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
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