Merge branch 'dev' into torch27

Signed-off-by: Eric Kerfoot <eric.kerfoot@kcl.ac.uk>

Author: ericspod

.github/CODEOWNERS

@@ -0,0 +1,17 @@
+/monai/ @KumoLiu @ericspod @Nic-Ma
+/docs/ @KumoLiu @ericspod @Nic-Ma
+/tests/ @KumoLiu @ericspod @Nic-Ma
+/.github/ @KumoLiu
+/monai/networks/schedulers/ @virginiafdez
+/monai/inferers/inferer.py @virginiafdez
+/monai/losses/adversarial_loss.py @virginiafdez
+/monai/losses/perceptual.py @virginiafdez
+/monai/networks/blocks/spade_norm.py @virginiafdez
+/monai/networks/nets/autoencoderkl.py @virginiafdez
+/monai/networks/nets/controlnet.py @virginiafdez
+/monai/networks/nets/diffusion_model_unet.py @virginiafdez
+/monai/networks/nets/patchgan_discriminator.py @virginiafdez
+/monai/networks/nets/spade_autoencoderkl.py @virginiafdez
+/monai/networks/nets/spade_diffusion_model_unet.py @virginiafdez
+/monai/networks/nets/spade_network.py @virginiafdez
+/monai/networks/nets/vqvae.py @virginiafdez

.github/codecov.yml

@@ -24,8 +24,13 @@ coverage:
         flags: null
         paths: null
 
-# Disable comments on PR
-comment: false
+comment: # enable code coverage comment on PR
+  layout: "diff, flags, files"
+  behavior: default
+  require_changes: false
+  require_base: false
+  require_head: true
+  hide_project_coverage: true
 
 ignore:
   - "versioneer.py"

.github/workflows/conda.yml

@@ -21,6 +21,7 @@ jobs:
         os: [ubuntu-latest]
         python-version: ["3.9", "3.10"]
     runs-on: ${{ matrix.os }}
+    timeout-minutes: 46 # equal to max + 3*std over the last 600 successful runs
     env:
       QUICKTEST: True
     steps:

.github/workflows/weekly-preview.yml

@@ -66,7 +66,7 @@ jobs:
         export YEAR_WEEK=$(date +'%y%U')
         echo "Year week for tag is ${YEAR_WEEK}"
         if ! [[ $YEAR_WEEK =~ ^[0-9]{4}$ ]] ; then echo "Wrong 'year week' format.  Should be 4 digits."; exit 1 ; fi
-        git tag "1.5.dev${YEAR_WEEK}"
+        git tag "1.6.dev${YEAR_WEEK}"
         git log -1
         git tag --list
         python setup.py sdist bdist_wheel

CHANGELOG.md

@@ -5,6 +5,103 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [Unreleased]
 
+## [1.5.0] - 2025-06-13
+
+## What's Changed
+### Added
+* Add platform-specific constraints to setup.cfg (#8260)
+* Add PythonicWorkflow (#8151)
+* Add SM architecture version check (#8199)
+* Add MedNext implementation (#8004)
+* Added a top button to CONSTRIBUTING.md (#8163)
+* Adding CODEOWNERS (#8457)
+* Restormer Implementation (#8312)
+* Add rectified flow noise scheduler for accelerated diffusion model (#8374)
+* Add prediction type for rflow scheduler (#8386)
+* Add Average Precision to metrics (#8089)
+* Implementation of a Masked Autoencoder for representation learning (#8152)
+* Implement TorchIO transforms wrapper analogous to TorchVision transfo… (#7579)
+* 8328 nnunet bundle integration (#8329)
+* Adding Support Policy + Doc Updates (#8458)
+* Classifier free guidance (#8460)
+
+### Fixed
+* Fix Ruff Numpy2 deprecation rules (#8179)
+* Fix `torch.load()` frequently warning in PersistentDataset and GDSDataset (#8177)
+* Fix the logging of a nested dictionary metric in MLflow (#8169)
+* Fix ImageFilter to allow Gaussian filter without filter_size (#8189)
+* Fix fold_constants, test_handler switched to onnx (#8211)
+* Fix TypeError in meshgrid (#8252)
+* Fix PatchMerging duplicate merging (#8285)
+* Fix test load image issue (#8297)
+* Fix bundle download error from ngc source (#8307)
+* Fix deprecated usage in zarr (#8313, #8477)
+* Fix DataFrame subsets indexing in CSVDataset() (#8351)
+* Fix `packaging` imports in version comparison logic (#8347)
+* Fix CommonKeys docstring (#8342)
+* Fix: correctly apply fftshift to real-valued data inputs (#8407)
+* Fix OptionalImportError: required package `openslide` is not installed (#8419)
+* Fix cosine noise scheduler (#8427)
+* Fix AutoencoderKL docstrings. (#8445)
+* Inverse Threading Fix (#8418)
+* Fix normalize intensity (#8286)
+* Fix path at test onnx trt export (#8361)
+* Fix broken urls (#8481, #8483)
+
+### Changed
+* [DOC] Update README.md (#8157)
+* Streamlined Rearrange in SpatialAttentionBlock (#8130)
+* Optimize VISTA3D (#8123)
+* Skip torch trt convert test with torch newer than or equal to 2.5.0 (#8165)
+* Enable redirection of all loggers by configuring a FileHandler within the bundle (#8142)
+* Apply pyupgrade fixes for Python 3.9+ syntax (#8150)
+* Update base image to 2410 (#8164)
+* TRT support for MAISI (#8153)
+* 8134 Add unit test for responsive inference (#8146)
+* SwinUNETR refactor to accept additional parameters (#8212)
+* Allow an arbitrary mask to be used in the self attention (#8235)
+* Bump codecov/codecov-action from 4 to 5 (#8245)
+* Docs: update brats classes description (#8246)
+* Change default value of `patch_norm` to False in `SwinUNETR` (#8249)
+* Modify Dice, Jaccard and Tversky losses (#8138)
+* Modify Workflow to Allow IterableDataset Inputs (#8263)
+* Enhance download_and_extract (#8216)
+* Relax gpu load check (#8282, #8275)
+* Using LocalStore in Zarr v3 (#8299)
+* Enable gpu load nifti (#8188)
+* update pydicom reader to enable gpu load (#8283)
+* Zarr compression tests only with versions before 3.0 (#8319)
+* Changing utils.py to test_utils.py (#8335)
+* Refactor testd (#8231)
+* Recursive Item Mapping for Nested Lists in Compose  (#8187)
+* Bump min torch to 1.13.1 to mitigate CVE-2022-45907 unsafe usage of eval (#8296)
+* Inferer modification - save_intermediates clashes with latent shape adjustment in latent diffusion inferers (#8343)
+* Solves path problem in test_bundle_trt_export.py (#8357)
+* Modify ControlNet inferer so that it takes in context when the diffus… (#8360)
+* Update monaihosting download method (#8364)
+* Bump torch minimum to mitigate CVE-2024-31580 & CVE-2024-31583 and enable numpy 2 compatibility (#8368)
+* Auto3DSeg algo_template hash update (#8378)
+* Enable Pytorch 2.6 (#8309)
+* Auto3DSeg algo_template hash update (#8393, #8397)
+* Update Dice Metric Docs (#8388)
+* Auto3DSeg algo_template hash update (#8406)
+* Update bundle download API (#8403)
+* Add Skip test in TestTranschex (#8416)
+* Update get latest bundle version function (#8420)
+* Temporarily Restrict setuptools Version to 79.0.1 (#8441)
+* Update default overlap value in occlusion_sensitivity to 0.6 (#8446)
+* Enable code coverage comments on PRs in codecov configuration (#8402)
+* Migrate to modern Python Logger API (#8449)
+
+### Deprecated
+### Removed
+* Remove deprecated functionality for v1.5 (#8430)
+* Remove deprecated `return_state_dict ` in bundle `load` (#8454)
+* Remove deprecated `net_name` in test file (#8461)
+* Remove unused test cases in bundle load (#8463)
+* selfattention block: Remove the fc linear layer if it is not used (#8325)
+* Removed outdated `torch` version checks from transform functions (#8359)
+
 ## [1.4.0] - 2024-10-17
 ## What's Changed
 ### Added
@@ -1132,7 +1229,8 @@ the postprocessing steps should be used before calling the metrics methods
 
 [highlights]: https://github.com/Project-MONAI/MONAI/blob/master/docs/source/highlights.md
 
-[Unreleased]: https://github.com/Project-MONAI/MONAI/compare/1.4.0...HEAD
+[Unreleased]: https://github.com/Project-MONAI/MONAI/compare/1.5.0...HEAD
+[1.5.0]: https://github.com/Project-MONAI/MONAI/compare/1.4.0...1.5.0
 [1.4.0]: https://github.com/Project-MONAI/MONAI/compare/1.3.2...1.4.0
 [1.3.2]: https://github.com/Project-MONAI/MONAI/compare/1.3.1...1.3.2
 [1.3.1]: https://github.com/Project-MONAI/MONAI/compare/1.3.0...1.3.1

CITATION.cff

@@ -6,8 +6,8 @@ title: "MONAI: Medical Open Network for AI"
 abstract: "AI Toolkit for Healthcare Imaging"
 authors:
   - name: "MONAI Consortium"
-date-released: 2024-10-17
-version: "1.4.0"
+date-released: 2025-06-13
+version: "1.5.0"
 identifiers:
   - description: "This DOI represents all versions of MONAI, and will always resolve to the latest one."
     type: doi

CONTRIBUTING.md

@@ -105,9 +105,9 @@ MONAI tests are located under `tests/`.
 A bash script (`runtests.sh`) is provided to run all tests locally.
 Please run ``./runtests.sh -h`` to see all options.
 
-To run a particular test, for example `tests/test_dice_loss.py`:
+To run a particular test, for example `tests/losses/test_dice_loss.py`:
 ```
-python -m tests.test_dice_loss
+python -m tests.losses.test_dice_loss
 ```
 
 Before submitting a pull request, we recommend that all linting and unit tests

README.md

@@ -33,6 +33,15 @@ Its ambitions are as follows:
 - customizable design for varying user expertise;
 - multi-GPU multi-node data parallelism support.
 
+## Requirements
+
+MONAI works with the [currently supported versions of Python](https://devguide.python.org/versions), and depends directly on NumPy and PyTorch with many optional dependencies.
+
+* Major releases of MONAI will have dependency versions stated for them. The current state of the `dev` branch in this repository is the unreleased development version of MONAI which typically will support current versions of dependencies and include updates and bug fixes to do so.
+* PyTorch support covers [the current version](https://github.com/pytorch/pytorch/releases) plus three previous minor versions. If compatibility issues with a PyTorch version and other dependencies arise, support for a version may be delayed until a major release.
+* Our support policy for other dependencies adheres for the most part to [SPEC0](https://scientific-python.org/specs/spec-0000), where dependency versions are supported where possible for up to two years. Discovered vulnerabilities or defects may require certain versions to be explicitly not supported.
+* See the `requirements*.txt` files for dependency version information.
+
 ## Installation
 
 To install [the current release](https://pypi.org/project/monai/), you can simply run:
@@ -45,7 +54,7 @@ Please refer to [the installation guide](https://docs.monai.io/en/latest/install
 
 ## Getting Started
 
-[MedNIST demo](https://colab.research.google.com/drive/1wy8XUSnNWlhDNazFdvGBHLfdkGvOHBKe) and [MONAI for PyTorch Users](https://colab.research.google.com/drive/1boqy7ENpKrqaJoxFlbHIBnIODAs1Ih1T) are available on Colab.
+[MedNIST demo](https://colab.research.google.com/github/Project-MONAI/tutorials/blob/main/2d_classification/mednist_tutorial.ipynb) and [MONAI for PyTorch Users](https://colab.research.google.com/github/Project-MONAI/tutorials/blob/main/modules/developer_guide.ipynb) are available on Colab.
 
 Examples and notebook tutorials are located at [Project-MONAI/tutorials](https://github.com/Project-MONAI/tutorials).
 
@@ -66,7 +75,7 @@ For guidance on making a contribution to MONAI, see the [contributing guidelines
 
 ## Community
 
-Join the conversation on Twitter/X [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9).
+Join the conversation on Twitter/X [@ProjectMONAI](https://twitter.com/ProjectMONAI), [LinkedIn](https://www.linkedin.com/company/projectmonai), or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9).
 
 Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions).
 

docs/images/maisi_infer.png

@@ -1,4 +1,4 @@
--f https://download.pytorch.org/whl/cpu/torch-2.3.0%2Bcpu-cp39-cp39-linux_x86_64.whl
+-f https://download.pytorch.org/whl/cpu/torch-2.4.1%2Bcpu-cp39-cp39-linux_x86_64.whl
 torch>=2.4.1
 pytorch-ignite==0.4.11
 numpy>=1.20