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medvae

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0.0.7 medvae-0.0.7-py3-none-any.whl
0.0.6 medvae-0.0.6-py3-none-any.whl

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Project: medvae
Version: 0.0.6
Filename: medvae-0.0.6-py3-none-any.whl
Download: [link]
Size: 28180
MD5: 57e26d2beb03feb2e4c2eef0ecb2c3ad
SHA256: ba372aa3717062b85a2fc42921eacb4197babbcbac9a7deebb52b91c0bce0b77
Uploaded: 2025-02-05 05:23:02 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.2
Name: medvae
Version: 0.0.6
Summary: MedVAE is a family of six medical image autoencoders that can encode high-dimensional medical images into latent representations.
Author: Stanford Machine Intelligence for Medical Imaging (MIMI)
Author-Email: Maya Varma <mayavarma[at]cs.stanford.edu>, Ashwin Kumar <akkumar[at]stanford.edu>, Rogier van der Sluijs <sluijs[at]stanford.edu>
Project-Url: homepage, https://github.com/StanfordMIMI/MedVAE
Project-Url: repository, https://github.com/StanfordMIMI/MedVAE
License: MIT License Copyright (c) 2025 Stanford MIMI Lab Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Keywords: deep learning,image compression,compression,efficiency,computer aided diagnosis,medical image analysis,autoencoders,representation learning,Med-VAE,medvae
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.9
Requires-Dist: torch (>=2.4.1)
Requires-Dist: accelerate (>=0.34.2)
Requires-Dist: wandb (==0.14.0)
Requires-Dist: tqdm
Requires-Dist: dicom2nifti
Requires-Dist: scipy
Requires-Dist: batchgenerators (>=0.25)
Requires-Dist: numpy (>=1.24)
Requires-Dist: scikit-learn
Requires-Dist: scikit-image (>=0.19.3)
Requires-Dist: SimpleITK (>=2.4.0)
Requires-Dist: omegaconf (>=2.3.0)
Requires-Dist: pandas
Requires-Dist: requests
Requires-Dist: nibabel
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: imagecodecs
Requires-Dist: yacs
Requires-Dist: batchgeneratorsv2 (>=0.2)
Requires-Dist: einops (>=0.8.0)
Requires-Dist: monai (>=1.3.2)
Requires-Dist: torchvision (>=0.19.1)
Requires-Dist: gdown
Requires-Dist: nilearn
Requires-Dist: black; extra == "dev"
Requires-Dist: ruff; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Provides-Extra: dev
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 3455 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.8.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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medvae/medvae.py sha256=beVTomiL2nMtMUZ_xM0ZQuT8jIJhX5wXgRQOj5O9il4 2939
medvae/medvae_inference.py sha256=nBBbG6ipgLzOtsonMht-cRhKEpr7uajGe5c4wVmJEzY 4769
medvae/models/__init__.py sha256=r_9r-nBX_ZDs6wiEStedFTvt5nMJvh9KSxppH6Ij0fw 204
medvae/models/autoencoder_kl.py sha256=vAn8qX85ph8etNA3-ZbYMyEjWHukQO5NW_cQPow59K4 3318
medvae/models/autoencoder_kl_3d.py sha256=0xhgFHoQ09gpYpIp-8KL7X9zhNrGT_6pzFESQjFL3Vc 4801
medvae/utils/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
medvae/utils/extras.py sha256=YKCNNRvWtZOYVi59Hh7PIHC5WJAWlzQFXligtWhimGY 1722
medvae/utils/factory.py sha256=hK-I7qC2ab0xTUB3mYE21_wXOFv86S2NrU1499Vv1BI 3554
medvae/utils/loaders.py sha256=xEbXZ1zaoM1C7LBX15-w75eyXP5G7ry2IdiLAlsM8jM 3475
medvae/utils/lora.py sha256=-mkXMv1dl4Y5GLkVFhyDBRB4otLMt5cOQIv-9xVdcHc 38330
medvae/utils/vae/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
medvae/utils/vae/diffusionmodels.py sha256=R3Uj8JYH9kqT_7Jljx_Xm-wohRNo0ULyamTC51r-6ts 13761
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medvae/utils/vae/distributions.py sha256=t8L95EpH2wUfdewD2VhLA8xwiesdaWMpOwGI1gMa59I 1633
medvae-0.0.6.dist-info/LICENSE sha256=wZi4ZZJw9bXEzB0p2ucdahGrutlS0P0zDIbiA2aZMOc 1073
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medvae-0.0.6.dist-info/entry_points.txt sha256=2CxmsSmMcrgC2RAUXZknsV5rOaQDZAO5hmMAfDuWxnc 66
medvae-0.0.6.dist-info/top_level.txt sha256=KUgXPTfRvpNURR4uij52zpAvxuihy4iXG4W7x9gmmYU 7
medvae-0.0.6.dist-info/RECORD — —

top_level.txt

medvae

entry_points.txt

[console_scripts]
medvae_inference = medvae.medvae_inference:main