Releases: MGAMZ/ITKIT
Release candidate 3 of v4
This is a develop release of v4.
The stable v4 will be released after the paper is drafted.
What's Changed
- [feat] itk_combine to combine multiple label sources by @MGAMZ in #61
- [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in #62
- Support Runtime Override
InferenceConfigby @MGAMZ in #63 - SegFormer3D now supports any stages by @MGAMZ in #65
- Add 3D Slicer extension for ITKIT inference by @Copilot in #64
- Align GUI tabs with backend CLI parameters by @Copilot in #66
- Add itk_slicer CLI entry point for SlicerITKIT server by @Copilot in #67
- Example, Log and Doc refine by @MGAMZ in #68
- Potential fix for code scanning alert no. 1: Workflow does not contain permissions by @MGAMZ in #69
- Release Docker Images by @MGAMZ in #70
Full Changelog: v4.0.0rc2...v4.0.0rc3
Release Candidate 2 of v4
This is a develop release of v4.
The stable v4 will be released after the paper is drafted.
What's Changed
- Prepare Release V4 by @MGAMZ in #49
- Compatible with mmengine loop arg by @MGAMZ in #50
- Fix metadata loss when processing modules skip existing files by @Copilot in #51
- Improve readthedoc layout structure by @MGAMZ in #52
- Introduce codecov into GitHub Action by @MGAMZ in #53
- Refactor test files structure and improve codecov by @MGAMZ in #54
- Introduce pre-commit ci APP by @MGAMZ in #55
- Support ONNX backend for
itkit.mm.inferenceby @MGAMZ in #56 - [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in #57
- Better
InferenceConfigand onnx infer backend by @MGAMZ in #58 - Support MSD dataset by @MGAMZ in #59
- yank back version by @MGAMZ in #60
New Contributors
- @pre-commit-ci[bot] made their first contribution in #57
Full Changelog: v4.0.0rc1...v4.0.0rc2
Release Candidate of v4
ITKIT is experimencing BC before formally published. So v3.6 will not be published as a stable release.
We are entering v4 epoch and resume from v3.6.0rc0.
What's Changed
Full Changelog: v3.6.0rc0...v4.0.0rc1
Release Candidate of v3.6
What's Changed
- Purge
SegFormer3Dimplementation and fixitk_patchtests by @MGAMZ in #30 - [Feature] itk_evaluate, itk_convert, torchio and more by @MGAMZ in #36
- Introduce MONAI-Based Train-Time Patching by @MGAMZ in #37
- Add IO shape validation tests for neural network models by @Copilot in #38
- Add comprehensive unit tests for itkit.io module by @Copilot in #40
- Add dataset mode to itk_orient for automatic image/label processing by @Copilot in #41
- Official example test on SegFormer3D, MONAI, TorchIO by @MGAMZ in #42
- Fix Inconsistent logic between TorchIO and ITKIT data backend by @MGAMZ in #43
- Compensate the missing commits in #43 by @MGAMZ in #44
Full Changelog: v3.5.3...v3.6.0rc0
Release v3.5.3
What's Changed
- Lint
itkit.mmfolder and deploypyrightintopre-commitby @MGAMZ in #25 - Lint more modules by @MGAMZ in #26
- Fix InferenceConfig not effecting during inference by @MGAMZ in #27
- Consistently orient to
LPIduringitk_patchby @MGAMZ in #28 - Fix IoUMetric bug by @MGAMZ in #29
Full Changelog: v3.5.0...v3.5.3
Release v3.5
Highlights
- Introducing pre-commit into this repo.
- Quality improvements by:
pyupgrade,ruff,isort. - Python static check by:
pyright,mypy. - Accelerated
PatchDatasetindexing during the initialization of training.
PRs
- Add ITKIT LOGO by @MGAMZ in #21
- Introduce auto lint and static check by @MGAMZ in #22
- Accelerate Indexing of PatchDataset by @MGAMZ in #23
Full Changelog: v3.4.0...v3.5.0
Release v3.4
Full Changelog: v3.3.0...v3.4.0
Highlights
- In this version, I refactor
itk_processingmodules to provide better maintainability and code structure. - CICD has also undergone improvements, resulting in higher module stability for this library.
- The
mmenginebased sliding-window inference efficiency has been improved via introducing a patch cache which can accelerateDevice2Hosttransfer.
New Features
- Support Totalsegmentator to CTSpine1K label extraction
- Support Totalsegmentator patched dataset
- An evaluation script for 3D medical volumes with segmentation tasks.
Enhancements
- GitHub Action environments upgrade:
- actions/checkout
- actions/setup-python
- Push will only trigger CI check with
python=3.13. - Disable
pin_memoryformgam_model_Seg3Dinference cachepred,count_matto save peak RAM occupation. - Introduce pinned patch cache on host to accelerate
Device2Hosttransfer, this can make sliding-window inference much faster. - Refactor
itk_processmodules to provide better readability and maintainance experiments. - Add pytest units for
itk_processmodules. - Auto publish to TestPyPI when doing a pre-release.
- Other general lint fixes.
Bug Fixes
itk_processmodule produces incorrect meta json file containing only one series.itk_resamplenormalize files' suffix differently in two input modes.
Repo Clean
- Remove unused packages, including
precrop_npz,standard_dataset,Sup_2D. - Remove
stretchprocessing module, it's one of my previous standalone work. - Remove unused
sitk_iofunctions. - Remove
inferencerof2Dmode,ONNXmode. - Now using
pyrightto check this repo, there're still many errors require fixing. - Remove
statistics,search_tool,SlideAvg,ckptclean,OpticalVisualization,ConfigQuickModify,CalcLabelDifferenceas they are strongly relied on specific dataset or task storage structure. - Remove
ResampleMhascript asitk_resampleis a better one with CLI.
Related PRs
Release Candidate 3 of v3.4
Bump v3.4.0rc3 by @MGAMZ in #19
Modification
- Delete unused srcs, test units, package imports
- Introduce evaluator util.
- Remove deprecated codes in
Inferencer. - Private methods are behind the public methods from now on, which will act as a coding guideline.
- Bug Fixes
Full Changelog: v3.4.0rc2...v3.4.0rc3
Release Candidate 2 of v3.4
What's Changed between rc1 and rc2
I'm trying to integrate the linter as pre-commit or CI. But no one satisfies me.
- Fix several lint suggestions. There're too many lint errors, it's hard to solve them in short time, so leaving them ready to be solved.
pyrighthas been selected to perform static type check. - Fix the incorrect arg passing in
SingleResampleProcessor. - Add
patch_sizeassertion check to avoid generating patches with wrong sizes. They can cause problems during deep learning training phase in which is quite complicated to locate the root of this issue. - Decouple the
IoU_metriclogic frommmsegtoITKIT, which perform evaluation on Host. - Change optional dependency.
- All
pre_cropscripts are removed as the newitk_patchis recommended. - Improve several test unit design.
Full Changelog: v3.4.0rc1...v3.4.0rc2
Release Candidate 1 of v3.4
What's Changed
Full Changelog: v3.4.0rc0...v3.4.0rc1