Merge branch 'dev' into bug/lps_orientation_transform

Author: ericspod

.coderabbit.yaml

@@ -0,0 +1,53 @@
+# yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json
+
+# This file configures CodeRabbit with the various options described in https://docs.coderabbit.ai/configure-coderabbit.
+# CodeRabbit also has a set of commands here: https://docs.coderabbit.ai/guides/commands/
+
+language: "en-US"
+early_access: false
+tone_instructions: "Be terse and to the point in all statements and commentary."
+reviews:
+  # chill is less verbose, assertive is more verbose with more nitpick feedback
+  profile: chill
+  high_level_summary: false
+  high_level_summary_placeholder: "@coderabbitai summary"
+  sequence_diagrams: false
+  auto_apply_labels: false
+  suggested_reviewers: false
+  changed_files_summary: false
+  suggested_labels: false
+  abort_on_close: true
+  poem: false
+  path_instructions:
+    - path: '**/*.md'
+      instructions: Remember that documentation must be updated with the latest information.
+    - path: '**/*.rst'
+      instructions: Remember that documentation must be updated with the latest information.
+    - path: '**/*.py'
+      instructions: >-
+        Review the Python code for quality and correctness. Ensure variable names adhere to PEP8 style guides, are
+        sensible and informative in regards to their function, though permitting simple names for loop and comprehension
+        variables. Ensure routine names are meaningful in regards to their function and use verbs, adjectives, and
+        nouns in a semantically appropriate way. Docstrings should be present for all definition which describe each
+        variable, return value, and raised exception in the appropriate section of the Google-style of docstrings.
+        Examine code for logical error or inconsistencies, and suggest what may be changed to addressed these. Suggest
+        any enhancements for code improving efficiency, maintainability, comprehensibility, and correctness. Ensure new
+        or modified definitions will be covered by existing or new unit tests.
+
+  auto_review:
+    # Automatic Review | Automatic code review
+    enabled: true
+    # Review draft PRs/MRs.
+    drafts: false
+    # ignore PRs with these in the title, these sorts of PRs should be drafts anyway
+    ignore_title_keywords:
+    - "WIP"
+    - "DO NOT MERGE"
+
+# opt out for now until it's clear this isn't too much info and is useful
+knowledge_base:
+  opt_out: true
+
+# chat is allowed
+chat:
+  auto_reply: true

.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/pythonapp-min.yml

@@ -124,7 +124,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        pytorch-version: ['2.4.1', '2.5.1', '2.6.0']  # FIXME: add 'latest' back once PyTorch 2.7 issues are resolved
+        pytorch-version: ['2.4.1', '2.5.1', '2.6.0', '2.7.1']
     timeout-minutes: 40
     steps:
     - uses: actions/checkout@v4
@@ -151,11 +151,7 @@ jobs:
     - name: Install the dependencies
       run: |
         # min. requirements
-        if [ ${{ matrix.pytorch-version }} == "latest" ]; then
-          python -m pip install torch
-        else
-          python -m pip install torch==${{ matrix.pytorch-version }}
-        fi
+        python -m pip install torch==${{ matrix.pytorch-version }}
         python -m pip install -r requirements-min.txt
         python -m pip list
         BUILD_MONAI=0 python setup.py develop  # no compile of extensions

.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

README.md

@@ -6,6 +6,7 @@
 
 ![Supported Python versions](https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/python.svg)
 [![License](https://img.shields.io/badge/license-Apache%202.0-green.svg)](https://opensource.org/licenses/Apache-2.0)
+[![auto-commit-msg](https://img.shields.io/badge/dynamic/json?label=citations&query=%24.citationCount&url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2FDOI%3A10.48550%2FarXiv.2211.02701%3Ffields%3DcitationCount)](https://arxiv.org/abs/2211.02701)
 [![PyPI version](https://badge.fury.io/py/monai.svg)](https://badge.fury.io/py/monai)
 [![docker](https://img.shields.io/badge/docker-pull-green.svg?logo=docker&logoColor=white)](https://hub.docker.com/r/projectmonai/monai)
 [![conda](https://img.shields.io/conda/vn/conda-forge/monai?color=green)](https://anaconda.org/conda-forge/monai)
@@ -54,7 +55,7 @@ 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).
 
@@ -75,7 +76,7 @@ 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

@@ -1,5 +1,5 @@
--f https://download.pytorch.org/whl/cpu/torch-2.3.0%2Bcpu-cp39-cp39-linux_x86_64.whl
-torch>=2.4.1, <2.7.0
+-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
 itk>=5.2

docs/requirements.txt

@@ -123,8 +123,7 @@ MONAI implements reference networks with the aim of both flexibility and code re
 
 Network layers and blocks are in general implemented to be compatible with spatial 1D, 2D and 3D inputs.
 Users can easily integrate the layers, blocks and networks as part of their customised pipelines.
-Various utilities are provided to leverage the existing model weights, e.g., finetuning [from MMAR](https://github.com/Project-MONAI/tutorials/blob/main/modules/transfer_mmar.ipynb)
-or [from a bundle in MONAI model-zoo](https://github.com/Project-MONAI/tutorials/tree/main/model_zoo).
+Various utilities are provided to leverage the existing model weights, e.g. [from a bundle in MONAI model-zoo](https://github.com/Project-MONAI/tutorials/tree/main/model_zoo).
 
 ### C++/CUDA optimized modules
 
@@ -231,8 +230,8 @@ A typical process of `decollate batch` is illustrated as follows (with a `batch_
 
 Except for the pytorch-ignite based `monai.engines`, most of the MONAI modules could be used independently or combined
 with other software packages. For example, MONAI can be easily integrated into popular frameworks such as
-PyTorch-Lightning and Catalyst. [[Lightning segmentation](https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/spleen_segmentation_3d_lightning.ipynb),
-[Catalyst segmentation](https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/unet_segmentation_3d_catalyst.ipynb)]
+[PyTorch-Lightning](https://github.com/Project-MONAI/tutorials/blob/main/3d_segmentation/spleen_segmentation_3d_lightning.ipynb)
+and [MLflow](https://github.com/Project-MONAI/tutorials/blob/main/experiment_management/spleen_segmentation_mlflow.ipynb).
 
 ## Bundle
 
@@ -264,7 +263,7 @@ A typical bundle example can include:
      ┗━ *license.txt
 ```
 Details about the bundle config definition and syntax & examples are at [config syntax](https://docs.monai.io/en/latest/config_syntax.html).
-A step-by-step [get started](https://github.com/Project-MONAI/tutorials/blob/main/bundle/get_started.md) tutorial notebook can help users quickly set up a bundle. [[bundle examples](https://github.com/Project-MONAI/tutorials/tree/main/bundle), [model-zoo](https://github.com/Project-MONAI/model-zoo)]
+A step-by-step [get started](https://github.com/Project-MONAI/tutorials/blob/main/bundle/README.md) tutorial notebook can help users quickly set up a bundle. [[bundle examples](https://github.com/Project-MONAI/tutorials/tree/main/bundle), [model-zoo](https://github.com/Project-MONAI/model-zoo)]
 
 ## Federated Learning