FSLeyes
FSLeyes is the FSL image viewer.
Installation
FSLeyes is a GUI application written in Python, and built on wxPython. FSLeyes requires OpenGL for visualisation.
In the majority of cases, you should be able to follow the installation instructions outlined at the FSLeyes home page:
Dependencies
All of the dependencies of FSLeyes are listed in pyproject.toml.
Being an OpenGL application, FSLeyes can only be used on computers with graphics hardware (or a software GL renderer) that supports one of the following versions:
OpenGL 3.3
OpenGL 2.1, with the following extensions:
EXT_framebuffer_object
ARB_instanced_arrays
ARB_draw_instanced
OpenGL 1.4, with the following extensions:
ARB_vertex_program
ARB_fragment_program
EXT_framebuffer_object
GL_ARB_texture_non_power_of_two
Documentation
The FSLeyes user and API documentation are hosted at:
The FSLeyes user and API documentation is written in ReStructuredText, and can be built using sphinx:
pip install -e ".[doc]" sphinx-build userdoc userdoc/html sphinx-build apidoc apidoc/html
The documentation will be generated and saved in userdoc/html/ and apidoc/html/.
Credits
Some of the FSLeyes icons are derived from the Freeline icon set, by Enes Dal, available at https://www.iconfinder.com/Enesdal, and released under the Creative Commons (Attribution 3.0 Unported) license.
The volumetric spline interpolation routine uses code from:
Daniel Ruijters and Philippe Thévenaz, GPU Prefilter for Accurate Cubic B-Spline Interpolation, The Computer Journal, vol. 55, no. 1, pp. 15-20, January 2012. http://dannyruijters.nl/docs/cudaPrefilter3.pdf
The GLSL parser is based on code by Nicolas P . Rougier, available at https://github.com/rougier/glsl-parser, and released under the BSD license.
DICOM to NIFTI conversion is performed with Chris Rorden’s dcm2niix (https://github.com/rordenlab/dcm2niix).
The brain_colours colour maps were produced and provided by Cyril Pernet (https://doi.org/10.1111/ejn.14430).
The data files used in the FSLeyes tractogram unit tests are from the DIPY example data sets (dipy.data.fetch_stanford_hardi).
1 maintainer
Metadata
1 maintainer
Release files for fsleyes 1.20.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fsleyes-1.20.2.tar.gz | 39.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fsleyes-1.20.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 79.8 MB
Release files / fsleyes-1.20.2.tar.gz
| Download URL | fsleyes-1.20.2.tar.gz |
|---|---|
| Size | 39.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/7.0.0 CPython/3.12.13
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Release files / fsleyes-1.20.2-py3-none-any.whl
| Download URL | fsleyes-1.20.2-py3-none-any.whl |
|---|---|
| Size | 40.4 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.13
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