v0.0.15: Housekeeping

This release is compatible with the PyTorch 2.2 release.

v0.0.14: Bugfixing

This release includes (besides bug fixes and dependency upgrades) a new SinglePredictor class to create predictions for a trained model in the main process without a consumer/producer architecture

Full Changelog: v0.0.13...v0.0.14

v0.0.13: PyTorch Conference poster release

This release features our PyTorch Conference poster Dealing with I/O bottlenecks in high-throughput model training including the code for the experiments.

Additionally, the code is now compatible with PyTorch 2.1.

v0.0.12: Context paper release

This release features the code and new models for our MICCAI2023 paper Semantic segmentation of surgical hyperspectral images under geometric domain shifts. See also the section in the README for more details.

v0.0.11: HeiPorSPECTRAL dataset release

Latest code to work with the recently released HeiPorSPECTRAL dataset.

Includes many internal updates, e.g PyTorch 2.0 is now supported.

v0.0.10: housekeeping

This release makes sure our code works with the latest lightning 2.0 release (pytorch 2.0 does not work yet).

v0.0.9: First release with pretrained models

This is the first release of our framework with the code from our paper “Robust deep learning-based semantic organ segmentation in hyperspectral images” including our pretrained networks.

Repository announcement

This is the announcement release for our code and pre-trained models which will be available soon.