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Merge remote-tracking branch 'origin/dev' into mednext
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.github/workflows/pythonapp.yml

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- name: Install dependencies
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run: |
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find /opt/hostedtoolcache/* -maxdepth 0 ! -name 'Python' -exec rm -rf {} \;
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python -m pip install --user --upgrade pip setuptools wheel twine
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python -m pip install --user --upgrade pip setuptools wheel twine packaging
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# install the latest pytorch for testing
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# however, "pip install monai*.tar.gz" will build cpp/cuda with an isolated
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# fresh torch installation according to pyproject.toml

.github/workflows/release.yml

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python-version: ${{ matrix.python-version }}
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- name: Install setuptools
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run: |
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python -m pip install --user --upgrade setuptools wheel
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python -m pip install --user --upgrade setuptools wheel packaging
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- name: Build and test source archive and wheel file
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run: |
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find /opt/hostedtoolcache/* -maxdepth 0 ! -name 'Python' -exec rm -rf {} \;
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run: |
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find /opt/hostedtoolcache/* -maxdepth 0 ! -name 'Python' -exec rm -rf {} \;
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git describe
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python -m pip install --user --upgrade setuptools wheel
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python -m pip install --user --upgrade setuptools wheel packaging
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python setup.py build
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cat build/lib/monai/_version.py
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- name: Upload version

.github/workflows/weekly-preview.yml

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- cron: "0 2 * * 0" # 02:00 of every Sunday
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jobs:
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flake8-py3:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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opt: ["codeformat", "pytype", "mypy"]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python 3.9
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uses: actions/setup-python@v5
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with:
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python-version: '3.9'
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- name: cache weekly timestamp
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id: pip-cache
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run: |
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echo "datew=$(date '+%Y-%V')" >> $GITHUB_OUTPUT
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- name: cache for pip
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uses: actions/cache@v4
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id: cache
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with:
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path: ~/.cache/pip
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key: ${{ runner.os }}-pip-${{ steps.pip-cache.outputs.datew }}
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- name: Install dependencies
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run: |
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find /opt/hostedtoolcache/* -maxdepth 0 ! -name 'Python' -exec rm -rf {} \;
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python -m pip install --upgrade pip wheel
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python -m pip install -r requirements-dev.txt
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- name: Lint and type check
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run: |
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# clean up temporary files
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$(pwd)/runtests.sh --build --clean
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# Github actions have 2 cores, so parallelize pytype
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$(pwd)/runtests.sh --build --${{ matrix.opt }} -j 2
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packaging:
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if: github.repository == 'Project-MONAI/MONAI'
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runs-on: ubuntu-latest
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python-version: '3.9'
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- name: Install setuptools
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run: |
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python -m pip install --user --upgrade setuptools wheel
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python -m pip install --user --upgrade setuptools wheel packaging
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- name: Build distribution
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run: |
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export HEAD_COMMIT_ID=$(git rev-parse HEAD)

README.md

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[![postmerge](https://img.shields.io/github/checks-status/project-monai/monai/dev?label=postmerge)](https://github.com/Project-MONAI/MONAI/actions?query=branch%3Adev)
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[![Documentation Status](https://readthedocs.org/projects/monai/badge/?version=latest)](https://docs.monai.io/en/latest/)
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[![codecov](https://codecov.io/gh/Project-MONAI/MONAI/branch/dev/graph/badge.svg?token=6FTC7U1JJ4)](https://codecov.io/gh/Project-MONAI/MONAI)
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[![monai Downloads Last Month](https://assets.piptrends.com/get-last-month-downloads-badge/monai.svg 'monai Downloads Last Month by pip Trends')](https://piptrends.com/package/monai)
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MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE) framework for deep learning in healthcare imaging, part of [PyTorch Ecosystem](https://pytorch.org/ecosystem/).
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Its ambitions are:

docs/requirements.txt

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zarr
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huggingface_hub
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pyamg>=5.0.0
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packaging

docs/source/apps.rst

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~~~~~~~~~~~~~
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.. autofunction:: monai.apps.reconstruction.complex_utils.complex_conj
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`Vista3d`
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---------
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.. automodule:: monai.apps.vista3d.inferer
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.. autofunction:: point_based_window_inferer
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.. automodule:: monai.apps.vista3d.transforms
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.. autoclass:: VistaPreTransformd
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:members:
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.. autoclass:: VistaPostTransformd
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:members:
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.. autoclass:: Relabeld
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:members:
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.. automodule:: monai.apps.vista3d.sampler
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.. autofunction:: sample_prompt_pairs
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`Auto3DSeg`
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.. automodule:: monai.apps.auto3dseg
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.. autoclass:: monai.apps.nnunet.nnUNetV2Runner
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:members:
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`Generative AI`
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---------------
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`MAISI Utilities`
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~~~~~~~~~~~~~~~~~
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.. automodule:: monai.apps.generation.maisi.utils.morphological_ops
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:members:

docs/source/installation.md

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- The options are
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```
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[nibabel, skimage, scipy, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, cucim, openslide, pandas, einops, transformers, mlflow, clearml, matplotlib, tensorboardX, tifffile, imagecodecs, pyyaml, fire, jsonschema, ninja, pynrrd, pydicom, h5py, nni, optuna, onnx, onnxruntime, zarr, lpips, pynvml, huggingface_hub]
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[nibabel, skimage, scipy, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, cucim, openslide, pandas, einops, transformers, mlflow, clearml, matplotlib, tensorboardX, tifffile, imagecodecs, pyyaml, fire, jsonschema, ninja, pynrrd, pydicom, h5py, nni, optuna, onnx, onnxruntime, zarr, lpips, pynvml, huggingface_hub, segment-anything]
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```
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which correspond to `nibabel`, `scikit-image`,`scipy`, `pillow`, `tensorboard`,
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`gdown`, `pytorch-ignite`, `torchvision`, `itk`, `tqdm`, `lmdb`, `psutil`, `cucim`, `openslide-python`, `pandas`, `einops`, `transformers`, `mlflow`, `clearml`, `matplotlib`, `tensorboardX`, `tifffile`, `imagecodecs`, `pyyaml`, `fire`, `jsonschema`, `ninja`, `pynrrd`, `pydicom`, `h5py`, `nni`, `optuna`, `onnx`, `onnxruntime`, `zarr`, `lpips`, `nvidia-ml-py`, `huggingface_hub` and `pyamg` respectively.
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`gdown`, `pytorch-ignite`, `torchvision`, `itk`, `tqdm`, `lmdb`, `psutil`, `cucim`, `openslide-python`, `pandas`, `einops`, `transformers`, `mlflow`, `clearml`, `matplotlib`, `tensorboardX`, `tifffile`, `imagecodecs`, `pyyaml`, `fire`, `jsonschema`, `ninja`, `pynrrd`, `pydicom`, `h5py`, `nni`, `optuna`, `onnx`, `onnxruntime`, `zarr`, `lpips`, `nvidia-ml-py`, `huggingface_hub`, `pyamg` and `segment-anything` respectively.
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- `pip install 'monai[all]'` installs all the optional dependencies.

docs/source/networks.rst

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.. autoclass:: SegResNetDS
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`SegResNetDS2`
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~~~~~~~~~~~~~~
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.. autoclass:: SegResNetDS2
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:members:
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`SegResNetVAE`
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~~~~~~~~~~~~~~
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.. autoclass:: SegResNetVAE
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.. autoclass:: UNETR
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`VISTA3D`
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~~~~~~~~~
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.. autoclass:: VISTA3D
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:members:
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`SwinUNETR`
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.. autoclass:: SwinUNETR

docs/source/transforms.rst

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.. automodule:: monai.transforms.utils_pytorch_numpy_unification
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.. automodule:: monai.transforms.utils_morphological_ops
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:members:
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By Categories
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-------------
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.. toctree::

environment-dev.yml

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- nvidia
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- conda-forge
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dependencies:
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- numpy>=1.20
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- numpy>=1.24,<2.0
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- pytorch>=1.9
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- torchvision
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- pytorch-cuda=11.6
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- pytorch-cuda>=11.6
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- pip
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- pip:
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- -r requirements-dev.txt

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