3D Slicer医学图像全自动AI分割组合拳-MONAIAuto3DSeg扩展
1 官网下载最新3D Slicer image computing platform | 3D Slicer 版本5.7
2 安装torch依赖包：
2.1 进入安装目录C:\Users\wangzhenlin\AppData\Local\slicer.org\Slicer 5.7.0-2024-09-21\bin，安装下载好的whl文件，slicer对应的是python3.9版本。
2.2 参考python playsound插件下载 python插件库_kcoufee的技术博客_51CTO博客
在自己conda环境下安装好，之后copy到slicer的文件夹内 ：
slicer的 Lib/site-packages路径：C:\Users\wangzhenlin\AppData\Local\slicer.org\Slicer 5.7.0-2024-09-21\lib\Python\Lib\site-packages
conda的 Lib/site-packages路径：D:\ProgramData\Anaconda3\envs\slicer39\Lib\site-packages
3 最后slicer自动安装对应的包
4模型下载地址：C:\Users\wangzhenlin\.MONAIAuto3DSeg\models\abdominal-organs-3mm-v2.0.0
log记录：
>>>
Collecting monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3
Obtaining dependency information for monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3 from https://files.pythonhosted.org/packages/bc/74/42d4ab8ee0a32c23ac7d38912c0d9d7c30de6e36b601e68bd2538452309b/monai-1.3.2-py3-none-any.whl.metadata
Downloading monai-1.3.2-py3-none-any.whl.metadata (10 kB)
Requirement already satisfied: torch>=1.9 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (2.2.2+cu118)
Requirement already satisfied: numpy>=1.20 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (1.26.4)
Collecting tqdm>=4.47.0 (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for tqdm>=4.47.0 from https://files.pythonhosted.org/packages/48/5d/acf5905c36149bbaec41ccf7f2b68814647347b72075ac0b1fe3022fdc73/tqdm-4.66.5-py3-none-any.whl.metadata
Downloading tqdm-4.66.5-py3-none-any.whl.metadata (57 kB)
-------------------------------------- 57.6/57.6 kB 275.4 kB/s eta 0:00:00
Collecting pyyaml (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for pyyaml from https://files.pythonhosted.org/packages/19/87/5124b1c1f2412bb95c59ec481eaf936cd32f0fe2a7b16b97b81c4c017a6a/PyYAML-6.0.2-cp39-cp39-win_amd64.whl.metadata
Downloading PyYAML-6.0.2-cp39-cp39-win_amd64.whl.metadata (2.1 kB)
Collecting nibabel (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for nibabel from https://files.pythonhosted.org/packages/77/3f/ce43b8c2ccc4a7913a87c4d425aaf0080ea3abf947587e47dc2025981a17/nibabel-5.2.1-py3-none-any.whl.metadata
Downloading nibabel-5.2.1-py3-none-any.whl.metadata (8.8 kB)
Collecting itk>=5.2 (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk>=5.2 from https://files.pythonhosted.org/packages/84/83/f1936822cb496ceb0b83c896e9347c3fbc0d0feb36e7eb1bdf750dfba12c/itk-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Collecting fire (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Downloading fire-0.6.0.tar.gz (88 kB)
---------------------------------------- 88.4/88.4 kB 1.2 MB/s eta 0:00:00
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing metadata (pyproject.toml): started
Preparing metadata (pyproject.toml): finished with status 'done'
Collecting tensorboard (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for tensorboard from https://files.pythonhosted.org/packages/d4/41/dccba8c5f955bc35b6110ff78574e4e5c8226ad62f08e732096c3861309b/tensorboard-2.17.1-py3-none-any.whl.metadata
Downloading tensorboard-2.17.1-py3-none-any.whl.metadata (1.6 kB)
Collecting scikit-image>=0.14.2 (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for scikit-image>=0.14.2 from https://files.pythonhosted.org/packages/9d/63/233300aa76c65a442a301f9d2416a9b06c91631287bd6dd3d6b620040096/scikit_image-0.24.0-cp39-cp39-win_amd64.whl.metadata
Downloading scikit_image-0.24.0-cp39-cp39-win_amd64.whl.metadata (14 kB)
Collecting psutil (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for psutil from https://files.pythonhosted.org/packages/73/44/561092313ae925f3acfaace6f9ddc4f6a9c748704317bad9c8c8f8a36a79/psutil-6.0.0-cp37-abi3-win_amd64.whl.metadata
Downloading psutil-6.0.0-cp37-abi3-win_amd64.whl.metadata (22 kB)
Collecting pynrrd (from monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for pynrrd from https://files.pythonhosted.org/packages/ee/43/1be50fe04e6a5df8cfdafa62151035a9358a768e26a5b9f33fc417e10bc6/pynrrd-1.0.0-py2.py3-none-any.whl.metadata
Downloading pynrrd-1.0.0-py2.py3-none-any.whl.metadata (3.9 kB)
Collecting itk-core==5.4.0 (from itk>=5.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk-core==5.4.0 from https://files.pythonhosted.org/packages/6a/c0/dcba14bf17ac6a88475676fbfb6faa759616b61e7e7a071035336d4008ce/itk_core-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk_core-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Collecting itk-numerics==5.4.0 (from itk>=5.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk-numerics==5.4.0 from https://files.pythonhosted.org/packages/b0/14/0f14f4202418c47a76f47b1d3bbcbd191896261688a5d1e7f1fa08a74a47/itk_numerics-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk_numerics-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Collecting itk-io==5.4.0 (from itk>=5.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk-io==5.4.0 from https://files.pythonhosted.org/packages/14/53/5cbcd48a40309bbe0407e35ad90922ec94615129e3fabfb65b729b77d896/itk_io-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk_io-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Collecting itk-filtering==5.4.0 (from itk>=5.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk-filtering==5.4.0 from https://files.pythonhosted.org/packages/64/45/e603fc2f638e6b9988159c5feb148202062113fcb5eb8b37dfc0f805f463/itk_filtering-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk_filtering-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Collecting itk-registration==5.4.0 (from itk>=5.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk-registration==5.4.0 from https://files.pythonhosted.org/packages/89/38/38d5a441cf468c8625d5611100c2c2f8e0a0a8c41f5782f543d58774ad8d/itk_registration-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk_registration-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Collecting itk-segmentation==5.4.0 (from itk>=5.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for itk-segmentation==5.4.0 from https://files.pythonhosted.org/packages/43/40/eee28dc7b383be22b6bffb48c0e6dadb126bdf38b6310a9ca4d4acd3d4ab/itk_segmentation-5.4.0-cp39-cp39-win_amd64.whl.metadata
Downloading itk_segmentation-5.4.0-cp39-cp39-win_amd64.whl.metadata (22 kB)
Requirement already satisfied: scipy>=1.9 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (1.13.1)
Collecting networkx>=2.8 (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for networkx>=2.8 from https://files.pythonhosted.org/packages/d5/f0/8fbc882ca80cf077f1b246c0e3c3465f7f415439bdea6b899f6b19f61f70/networkx-3.2.1-py3-none-any.whl.metadata
Using cached networkx-3.2.1-py3-none-any.whl.metadata (5.2 kB)
Requirement already satisfied: pillow>=9.1 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (10.3.0)
Collecting imageio>=2.33 (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for imageio>=2.33 from https://files.pythonhosted.org/packages/1e/b7/02adac4e42a691008b5cfb31db98c190e1fc348d1521b9be4429f9454ed1/imageio-2.35.1-py3-none-any.whl.metadata
Downloading imageio-2.35.1-py3-none-any.whl.metadata (4.9 kB)
Collecting tifffile>=2022.8.12 (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for tifffile>=2022.8.12 from https://files.pythonhosted.org/packages/3a/4f/73714b1c1d339b1545cac28764e39f88c69468b5e10e51f327f9aa9d55b9/tifffile-2024.8.30-py3-none-any.whl.metadata
Downloading tifffile-2024.8.30-py3-none-any.whl.metadata (31 kB)
Requirement already satisfied: packaging>=21 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (24.0)
Collecting lazy-loader>=0.4 (from scikit-image>=0.14.2->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for lazy-loader>=0.4 from https://files.pythonhosted.org/packages/83/60/d497a310bde3f01cb805196ac61b7ad6dc5dcf8dce66634dc34364b20b4f/lazy_loader-0.4-py3-none-any.whl.metadata
Downloading lazy_loader-0.4-py3-none-any.whl.metadata (7.6 kB)
Collecting filelock (from torch>=1.9->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for filelock from https://files.pythonhosted.org/packages/b9/f8/feced7779d755758a52d1f6635d990b8d98dc0a29fa568bbe0625f18fdf3/filelock-3.16.1-py3-none-any.whl.metadata
Using cached filelock-3.16.1-py3-none-any.whl.metadata (2.9 kB)
Requirement already satisfied: typing-extensions>=4.8.0 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from torch>=1.9->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (4.12.1)
Collecting sympy (from torch>=1.9->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for sympy from https://files.pythonhosted.org/packages/99/ff/c87e0622b1dadea79d2fb0b25ade9ed98954c9033722eb707053d310d4f3/sympy-1.13.3-py3-none-any.whl.metadata
Using cached sympy-1.13.3-py3-none-any.whl.metadata (12 kB)
Collecting jinja2 (from torch>=1.9->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for jinja2 from https://files.pythonhosted.org/packages/31/80/3a54838c3fb461f6fec263ebf3a3a41771bd05190238de3486aae8540c36/jinja2-3.1.4-py3-none-any.whl.metadata
Using cached jinja2-3.1.4-py3-none-any.whl.metadata (2.6 kB)
Collecting fsspec (from torch>=1.9->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for fsspec from https://files.pythonhosted.org/packages/1d/a0/6aaea0c2fbea2f89bfd5db25fb1e3481896a423002ebe4e55288907a97a3/fsspec-2024.9.0-py3-none-any.whl.metadata
Using cached fsspec-2024.9.0-py3-none-any.whl.metadata (11 kB)
Collecting colorama (from tqdm>=4.47.0->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for colorama from https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl.metadata
Downloading colorama-0.4.6-py2.py3-none-any.whl.metadata (17 kB)
Requirement already satisfied: six in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from fire->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (1.16.0)
Collecting termcolor (from fire->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for termcolor from https://files.pythonhosted.org/packages/d9/5f/8c716e47b3a50cbd7c146f45881e11d9414def768b7cd9c5e6650ec2a80a/termcolor-2.4.0-py3-none-any.whl.metadata
Downloading termcolor-2.4.0-py3-none-any.whl.metadata (6.1 kB)
Collecting nptyping (from pynrrd->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for nptyping from https://files.pythonhosted.org/packages/b1/28/92edc05378175de13a3d4986cee7531853634a22b7e5e21a988fa84fde3f/nptyping-2.5.0-py3-none-any.whl.metadata
Downloading nptyping-2.5.0-py3-none-any.whl.metadata (7.6 kB)
Collecting absl-py>=0.4 (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for absl-py>=0.4 from https://files.pythonhosted.org/packages/a2/ad/e0d3c824784ff121c03cc031f944bc7e139a8f1870ffd2845cc2dd76f6c4/absl_py-2.1.0-py3-none-any.whl.metadata
Downloading absl_py-2.1.0-py3-none-any.whl.metadata (2.3 kB)
Collecting grpcio>=1.48.2 (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for grpcio>=1.48.2 from https://files.pythonhosted.org/packages/28/7c/a280d2f5f7afbb815602bbf030e4ae179506b973b8c88a58d44ceefe1d47/grpcio-1.66.1-cp39-cp39-win_amd64.whl.metadata
Downloading grpcio-1.66.1-cp39-cp39-win_amd64.whl.metadata (4.0 kB)
Collecting markdown>=2.6.8 (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for markdown>=2.6.8 from https://files.pythonhosted.org/packages/3f/08/83871f3c50fc983b88547c196d11cf8c3340e37c32d2e9d6152abe2c61f7/Markdown-3.7-py3-none-any.whl.metadata
Downloading Markdown-3.7-py3-none-any.whl.metadata (7.0 kB)
Collecting protobuf!=4.24.0,>=3.19.6 (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for protobuf!=4.24.0,>=3.19.6 from https://files.pythonhosted.org/packages/94/12/af94b0654fa6bde64272b2abab39b221544c32e9e911284745569f65e73a/protobuf-5.28.2-cp39-cp39-win_amd64.whl.metadata
Downloading protobuf-5.28.2-cp39-cp39-win_amd64.whl.metadata (592 bytes)
Requirement already satisfied: setuptools>=41.0.0 in c:\users\wangzhenlin\appdata\local\slicer.org\slicer 5.7.0-2024-09-21\lib\python\lib\site-packages (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3) (70.0.0)
Collecting tensorboard-data-server<0.8.0,>=0.7.0 (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for tensorboard-data-server<0.8.0,>=0.7.0 from https://files.pythonhosted.org/packages/7a/13/e503968fefabd4c6b2650af21e110aa8466fe21432cd7c43a84577a89438/tensorboard_data_server-0.7.2-py3-none-any.whl.metadata
Downloading tensorboard_data_server-0.7.2-py3-none-any.whl.metadata (1.1 kB)
Collecting werkzeug>=1.0.1 (from tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for werkzeug>=1.0.1 from https://files.pythonhosted.org/packages/4b/84/997bbf7c2bf2dc3f09565c6d0b4959fefe5355c18c4096cfd26d83e0785b/werkzeug-3.0.4-py3-none-any.whl.metadata
Downloading werkzeug-3.0.4-py3-none-any.whl.metadata (3.7 kB)
Collecting importlib-metadata>=4.4 (from markdown>=2.6.8->tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for importlib-metadata>=4.4 from https://files.pythonhosted.org/packages/a0/d9/a1e041c5e7caa9a05c925f4bdbdfb7f006d1f74996af53467bc394c97be7/importlib_metadata-8.5.0-py3-none-any.whl.metadata
Downloading importlib_metadata-8.5.0-py3-none-any.whl.metadata (4.8 kB)
Collecting MarkupSafe>=2.1.1 (from werkzeug>=1.0.1->tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for MarkupSafe>=2.1.1 from https://files.pythonhosted.org/packages/f6/f8/4da07de16f10551ca1f640c92b5f316f9394088b183c6a57183df6de5ae4/MarkupSafe-2.1.5-cp39-cp39-win_amd64.whl.metadata
Using cached MarkupSafe-2.1.5-cp39-cp39-win_amd64.whl.metadata (3.1 kB)
Collecting mpmath<1.4,>=1.1.0 (from sympy->torch>=1.9->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for mpmath<1.4,>=1.1.0 from https://files.pythonhosted.org/packages/43/e3/7d92a15f894aa0c9c4b49b8ee9ac9850d6e63b03c9c32c0367a13ae62209/mpmath-1.3.0-py3-none-any.whl.metadata
Using cached mpmath-1.3.0-py3-none-any.whl.metadata (8.6 kB)
Collecting zipp>=3.20 (from importlib-metadata>=4.4->markdown>=2.6.8->tensorboard->monai[fire,itk,nibabel,psutil,pynrrd,pyyaml,skimage,tensorboard,tqdm]>=1.3)
Obtaining dependency information for zipp>=3.20 from https://files.pythonhosted.org/packages/62/8b/5ba542fa83c90e09eac972fc9baca7a88e7e7ca4b221a89251954019308b/zipp-3.20.2-py3-none-any.whl.metadata
Downloading zipp-3.20.2-py3-none-any.whl.metadata (3.7 kB)
Downloading itk-5.4.0-cp39-cp39-win_amd64.whl (17 kB)
Downloading itk_core-5.4.0-cp39-cp39-win_amd64.whl (37.1 MB)
---------------------------------------- 37.1/37.1 MB 9.1 MB/s eta 0:00:00
Downloading itk_filtering-5.4.0-cp39-cp39-win_amd64.whl (23.8 MB)
---------------------------------------- 23.8/23.8 MB 12.6 MB/s eta 0:00:00
Downloading itk_io-5.4.0-cp39-cp39-win_amd64.whl (8.7 MB)
---------------------------------------- 8.7/8.7 MB 12.3 MB/s eta 0:00:00
Downloading itk_numerics-5.4.0-cp39-cp39-win_amd64.whl (19.9 MB)
---------------------------------------- 19.9/19.9 MB 11.9 MB/s eta 0:00:00
Downloading itk_registration-5.4.0-cp39-cp39-win_amd64.whl (9.5 MB)
---------------------------------------- 9.5/9.5 MB 11.6 MB/s eta 0:00:00
Downloading itk_segmentation-5.4.0-cp39-cp39-win_amd64.whl (5.0 MB)
---------------------------------------- 5.0/5.0 MB 10.0 MB/s eta 0:00:00
Downloading scikit_image-0.24.0-cp39-cp39-win_amd64.whl (12.9 MB)
---------------------------------------- 12.9/12.9 MB 9.6 MB/s eta 0:00:00
Downloading tqdm-4.66.5-py3-none-any.whl (78 kB)
---------------------------------------- 78.4/78.4 kB ? eta 0:00:00
Downloading monai-1.3.2-py3-none-any.whl (1.4 MB)
---------------------------------------- 1.4/1.4 MB 14.4 MB/s eta 0:00:00
Downloading nibabel-5.2.1-py3-none-any.whl (3.3 MB)
---------------------------------------- 3.3/3.3 MB 10.0 MB/s eta 0:00:00
Downloading psutil-6.0.0-cp37-abi3-win_amd64.whl (257 kB)
--------------------------------------- 257.4/257.4 kB 15.4 MB/s eta 0:00:00
Downloading pynrrd-1.0.0-py2.py3-none-any.whl (19 kB)
Downloading PyYAML-6.0.2-cp39-cp39-win_amd64.whl (162 kB)
--------------------------------------- 162.3/162.3 kB 10.1 MB/s eta 0:00:00
Downloading tensorboard-2.17.1-py3-none-any.whl (5.5 MB)
---------------------------------------- 5.5/5.5 MB 12.1 MB/s eta 0:00:00
Downloading absl_py-2.1.0-py3-none-any.whl (133 kB)
---------------------------------------- 133.7/133.7 kB 8.2 MB/s eta 0:00:00
Downloading grpcio-1.66.1-cp39-cp39-win_amd64.whl (4.3 MB)
---------------------------------------- 4.3/4.3 MB 16.1 MB/s eta 0:00:00
Downloading imageio-2.35.1-py3-none-any.whl (315 kB)
--------------------------------------- 315.4/315.4 kB 19.1 MB/s eta 0:00:00
Downloading lazy_loader-0.4-py3-none-any.whl (12 kB)
Downloading Markdown-3.7-py3-none-any.whl (106 kB)
---------------------------------------- 106.3/106.3 kB 6.0 MB/s eta 0:00:00
Using cached networkx-3.2.1-py3-none-any.whl (1.6 MB)
Downloading protobuf-5.28.2-cp39-cp39-win_amd64.whl (431 kB)
---------------------------------------- 431.6/431.6 kB 6.8 MB/s eta 0:00:00
Downloading tensorboard_data_server-0.7.2-py3-none-any.whl (2.4 kB)
Downloading tifffile-2024.8.30-py3-none-any.whl (227 kB)
---------------------------------------- 227.3/227.3 kB 7.0 MB/s eta 0:00:00
Downloading werkzeug-3.0.4-py3-none-any.whl (227 kB)
--------------------------------------- 227.6/227.6 kB 13.6 MB/s eta 0:00:00
Downloading colorama-0.4.6-py2.py3-none-any.whl (25 kB)
Using cached filelock-3.16.1-py3-none-any.whl (16 kB)
Using cached fsspec-2024.9.0-py3-none-any.whl (179 kB)
Using cached jinja2-3.1.4-py3-none-any.whl (133 kB)
Downloading nptyping-2.5.0-py3-none-any.whl (37 kB)
Using cached sympy-1.13.3-py3-none-any.whl (6.2 MB)
Downloading termcolor-2.4.0-py3-none-any.whl (7.7 kB)
Downloading importlib_metadata-8.5.0-py3-none-any.whl (26 kB)
Using cached MarkupSafe-2.1.5-cp39-cp39-win_amd64.whl (17 kB)
Using cached mpmath-1.3.0-py3-none-any.whl (536 kB)
Downloading zipp-3.20.2-py3-none-any.whl (9.2 kB)
Building wheels for collected packages: fire
Building wheel for fire (pyproject.toml): started
Building wheel for fire (pyproject.toml): finished with status 'done'
Created wheel for fire: filename=fire-0.6.0-py2.py3-none-any.whl size=117044 sha256=56c65e2b67ee319bb7643cfab4ee2b3313f097656f7ca21125f2c6b87247ce73
Stored in directory: c:\users\wangzhenlin\appdata\local\pip\cache\wheels\ec\ce\ba\9d5764d2266c500c18776c7d8f1e3c023075994cbc6dea47db
Successfully built fire
Installing collected packages: mpmath, zipp, tifffile, termcolor, tensorboard-data-server, sympy, pyyaml, psutil, protobuf, nptyping, nibabel, networkx, MarkupSafe, lazy-loader, itk-core, imageio, grpcio, fsspec, filelock, colorama, absl-py, werkzeug, tqdm, scikit-image, pynrrd, jinja2, itk-numerics, itk-io, importlib-metadata, fire, markdown, itk-filtering, tensorboard, monai, itk-segmentation, itk-registration, itk
Successfully installed MarkupSafe-2.1.5 absl-py-2.1.0 colorama-0.4.6 filelock-3.16.1 fire-0.6.0 fsspec-2024.9.0 grpcio-1.66.1 imageio-2.35.1 importlib-metadata-8.5.0 itk-5.4.0 itk-core-5.4.0 itk-filtering-5.4.0 itk-io-5.4.0 itk-numerics-5.4.0 itk-registration-5.4.0 itk-segmentation-5.4.0 jinja2-3.1.4 lazy-loader-0.4 markdown-3.7 monai-1.3.2 mpmath-1.3.0 networkx-3.2.1 nibabel-5.2.1 nptyping-2.5.0 protobuf-5.28.2 psutil-6.0.0 pynrrd-1.0.0 pyyaml-6.0.2 scikit-image-0.24.0 sympy-1.13.3 tensorboard-2.17.1 tensorboard-data-server-0.7.2 termcolor-2.4.0 tifffile-2024.8.30 tqdm-4.66.5 werkzeug-3.0.4 zipp-3.20.2
Initializing PyTorch...
Initializing MONAI...
Dependencies are set up successfully.
Downloading model 'abdominal-organs-3mm-v2.0.0' from https://github.com/lassoan/SlicerMONAIAuto3DSeg/releases/download/Models/abdominal-organs-3mm-v2.0.0.zip...
Downloading model: 0.1MB / 308.3MB (0.0%)
Downloading model: 3.2MB / 308.3MB (1.1%)
Downloading model: 6.4MB / 308.3MB (2.1%)
Downloading model: 9.5MB / 308.3MB (3.1%)
Downloading model: 12.6MB / 308.3MB (4.1%)
Downloading model: 15.8MB / 308.3MB (5.1%)
Downloading model: 18.9MB / 308.3MB (6.1%)
Downloading model: 22.0MB / 308.3MB (7.1%)
Downloading model: 25.1MB / 308.3MB (8.2%)
Downloading model: 28.2MB / 308.3MB (9.2%)
Downloading model: 31.4MB / 308.3MB (10.2%)
Downloading model: 34.5MB / 308.3MB (11.2%)
Downloading model: 37.6MB / 308.3MB (12.2%)
Downloading model: 40.8MB / 308.3MB (13.2%)
Downloading model: 43.9MB / 308.3MB (14.2%)
Downloading model: 47.0MB / 308.3MB (15.2%)
Downloading model: 50.1MB / 308.3MB (16.3%)
Downloading model: 53.2MB / 308.3MB (17.3%)
Downloading model: 56.4MB / 308.3MB (18.3%)
Downloading model: 59.5MB / 308.3MB (19.3%)
Downloading model: 62.6MB / 308.3MB (20.3%)
Downloading model: 65.8MB / 308.3MB (21.3%)
Downloading model: 68.9MB / 308.3MB (22.3%)
Downloading model: 72.0MB / 308.3MB (23.4%)
Downloading model: 75.1MB / 308.3MB (24.4%)
Downloading model: 78.2MB / 308.3MB (25.4%)
Downloading model: 81.4MB / 308.3MB (26.4%)
Downloading model: 84.5MB / 308.3MB (27.4%)
Downloading model: 87.6MB / 308.3MB (28.4%)
Downloading model: 90.8MB / 308.3MB (29.4%)
Downloading model: 93.9MB / 308.3MB (30.5%)
Downloading model: 97.0MB / 308.3MB (31.5%)
Downloading model: 100.1MB / 308.3MB (32.5%)
Downloading model: 103.2MB / 308.3MB (33.5%)
Downloading model: 106.4MB / 308.3MB (34.5%)
Downloading model: 109.5MB / 308.3MB (35.5%)
Downloading model: 112.6MB / 308.3MB (36.5%)
Downloading model: 115.8MB / 308.3MB (37.5%)
Downloading model: 118.9MB / 308.3MB (38.6%)
Downloading model: 122.0MB / 308.3MB (39.6%)
Downloading model: 125.1MB / 308.3MB (40.6%)
Downloading model: 128.2MB / 308.3MB (41.6%)
Downloading model: 131.4MB / 308.3MB (42.6%)
Downloading model: 134.5MB / 308.3MB (43.6%)
Downloading model: 137.6MB / 308.3MB (44.6%)
Downloading model: 140.8MB / 308.3MB (45.7%)
Downloading model: 143.9MB / 308.3MB (46.7%)
Downloading model: 147.0MB / 308.3MB (47.7%)
Downloading model: 150.1MB / 308.3MB (48.7%)
Downloading model: 153.2MB / 308.3MB (49.7%)
Downloading model: 156.4MB / 308.3MB (50.7%)
Downloading model: 159.5MB / 308.3MB (51.7%)
Downloading model: 162.6MB / 308.3MB (52.8%)
Downloading model: 165.8MB / 308.3MB (53.8%)
Downloading model: 168.9MB / 308.3MB (54.8%)
Downloading model: 172.0MB / 308.3MB (55.8%)
Downloading model: 175.1MB / 308.3MB (56.8%)
Downloading model: 178.2MB / 308.3MB (57.8%)
Downloading model: 181.4MB / 308.3MB (58.8%)
Downloading model: 184.5MB / 308.3MB (59.8%)
Downloading model: 187.6MB / 308.3MB (60.9%)
Downloading model: 190.8MB / 308.3MB (61.9%)
Downloading model: 193.9MB / 308.3MB (62.9%)
Downloading model: 197.0MB / 308.3MB (63.9%)
Downloading model: 200.1MB / 308.3MB (64.9%)
Downloading model: 203.2MB / 308.3MB (65.9%)
Downloading model: 206.4MB / 308.3MB (66.9%)
Downloading model: 209.5MB / 308.3MB (68.0%)
Downloading model: 212.6MB / 308.3MB (69.0%)
Downloading model: 215.8MB / 308.3MB (70.0%)
Downloading model: 218.9MB / 308.3MB (71.0%)
Downloading model: 222.0MB / 308.3MB (72.0%)
Downloading model: 225.1MB / 308.3MB (73.0%)
Downloading model: 228.2MB / 308.3MB (74.0%)
Downloading model: 231.4MB / 308.3MB (75.1%)
Downloading model: 234.5MB / 308.3MB (76.1%)
Downloading model: 237.6MB / 308.3MB (77.1%)
Downloading model: 240.8MB / 308.3MB (78.1%)
Downloading model: 243.9MB / 308.3MB (79.1%)
Downloading model: 247.0MB / 308.3MB (80.1%)
Downloading model: 250.1MB / 308.3MB (81.1%)
Downloading model: 253.2MB / 308.3MB (82.2%)
Downloading model: 256.4MB / 308.3MB (83.2%)
Downloading model: 259.5MB / 308.3MB (84.2%)
Downloading model: 262.6MB / 308.3MB (85.2%)
Downloading model: 265.8MB / 308.3MB (86.2%)
Downloading model: 268.9MB / 308.3MB (87.2%)
Downloading model: 272.0MB / 308.3MB (88.2%)
Downloading model: 275.1MB / 308.3MB (89.2%)
Downloading model: 278.2MB / 308.3MB (90.3%)
Downloading model: 281.4MB / 308.3MB (91.3%)
Downloading model: 284.5MB / 308.3MB (92.3%)
Downloading model: 287.6MB / 308.3MB (93.3%)
Downloading model: 290.8MB / 308.3MB (94.3%)
Downloading model: 293.9MB / 308.3MB (95.3%)
Downloading model: 297.0MB / 308.3MB (96.3%)
Downloading model: 300.1MB / 308.3MB (97.4%)
Downloading model: 303.2MB / 308.3MB (98.4%)
Downloading model: 306.4MB / 308.3MB (99.4%)
Download finished. Extracting to C:\Users\wangzhenlin\.MONAIAuto3DSeg\models\abdominal-organs-3mm-v2.0.0...
Cleaning up temporary model download folder...
Processing started
Writing input file to C:/Users/wangzhenlin/AppData/Local/Temp/Slicer/__SlicerTemp__2024-09-24_17+56+23.048/input-volume0.nrrd
Creating segmentations with MONAIAuto3DSeg AI...
Auto3DSeg command: ['C:/Users/wangzhenlin/AppData/Local/slicer.org/Slicer 5.7.0-2024-09-21/bin/../bin\\PythonSlicer.EXE', 'C:/Users/wangzhenlin/AppData/Local/slicer.org/Slicer 5.7.0-2024-09-21/slicer.org/Extensions-33025/MONAIAuto3DSeg/lib/Slicer-5.7/qt-scripted-modules\\Scripts\\auto3dseg_segresnet_inference.py', '--model-file', 'C:\\Users\\wangzhenlin\\.MONAIAuto3DSeg\\models\\abdominal-organs-3mm-v2.0.0\\model.pt', '--image-file', 'C:/Users/wangzhenlin/AppData/Local/Temp/Slicer/__SlicerTemp__2024-09-24_17+56+23.048/input-volume0.nrrd', '--result-file', 'C:/Users/wangzhenlin/AppData/Local/Temp/Slicer/__SlicerTemp__2024-09-24_17+56+23.048/output-segmentation.nrrd']
`apex.normalization.InstanceNorm3dNVFuser` is not installed properly, use nn.InstanceNorm3d instead.
Model epoch 294 metric 0.9070999026298523
Using crop_foreground
Using resample with resample_resolution [3.0, 3.0, 3.0]
Running Inference ...
preds inverted torch.Size([512, 512, 88])
Computation time log:
Loading volumes: 2.19 seconds
Importing segmentation results...
Cleaning up temporary folder.
Processing was completed in 22.38 seconds.
Processing finished.