ITK-SNAP Deep Learning Segmentation (DLS) Plugins
This package contains Python scripts that enable deep learning segmentation models to be run from ITK-SNAP. The documentation is here:
For developers
- Contributing Guidelines — how to report bugs and submit pull requests.
- Developer Guide — architecture, the REST API, and how to add a model.
- ITK-SNAP Governance — how the project is run and who maintains it.
- ITK-SNAP Code of Conduct — expectations for participation.
Metadata
Release files for itksnap-dls 0.1.6
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| itksnap_dls-0.1.6.tar.gz | 23.2 kB | With provenance | Details for itksnap_dls-0.1.6.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| itksnap_dls-0.1.6-py3-none-any.whl | Python 3 | none | any | Details for itksnap_dls-0.1.6-py3-none-any.whl |
Total release size: 47.1 kB
Release files / itksnap_dls-0.1.6.tar.gz
| Download URL | itksnap_dls-0.1.6.tar.gz |
|---|---|
| Size | 23.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.13.16
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Transparency logRelease files / itksnap_dls-0.1.6-py3-none-any.whl
| Download URL | itksnap_dls-0.1.6-py3-none-any.whl |
|---|---|
| Size | 23.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
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Provenance
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Transparency logSecurity for itksnap-dls 0.1.6
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Full provenance
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Attestation for itksnap_dls-0.1.6.tar.gz
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Signed by GitHub Actions, verified by PyPI on Oct 23, 2026.
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