Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

project-monai

Medical Open Network for AI

License CI Build Documentation Status codecov PyPI version

MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem. Its ambitions are:

  • developing a community of academic, industrial and clinical researchers collaborating on a common foundation;
  • creating state-of-the-art, end-to-end training workflows for healthcare imaging;
  • providing researchers with the optimized and standardized way to create and evaluate deep learning models.

Features

The codebase is currently under active development. Please see the technical highlights and What's New of the current milestone release.

  • flexible pre-processing for multi-dimensional medical imaging data;
  • compositional & portable APIs for ease of integration in existing workflows;
  • domain-specific implementations for networks, losses, evaluation metrics and more;
  • customizable design for varying user expertise;
  • multi-GPU data parallelism support.

Installation

To install the current release, you can simply run:

pip install monai

For other installation methods (using the default GitHub branch, using Docker, etc.), please refer to the installation guide.

Getting Started

MedNIST demo and MONAI for PyTorch Users are available on Colab.

Examples and notebook tutorials are located at Project-MONAI/tutorials.

Technical documentation is available at docs.monai.io.

Contributing

For guidance on making a contribution to MONAI, see the contributing guidelines.

Community

Join the conversation on Twitter @ProjectMONAI or join our Slack channel.

Ask and answer questions over on MONAI's GitHub Discussions tab.

Release files for monai-weekly 0.8.dev2142

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for monai-weekly 0.8.dev2142
File Size Uploaded
monai-weekly-0.8.dev2142.tar.gz 500.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for monai-weekly 0.8.dev2142
File Interpreter ABI Platform
monai_weekly-0.8.dev2142-py3-none-any.whl Python 3 none any Details

Total release size: 1.2 MB

Release files / monai-weekly-0.8.dev2142.tar.gz

Download URL monai-weekly-0.8.dev2142.tar.gz
Size 500.2 kB
Tags Source
SHA-256 checksum
How to use checksums
02fac34fef1bcd1467bf86787ca948316e0179a2bbe0f8ad84b59ce34f0b2cda
BLAKE2b-256 checksum
How to use checksums
8061ad5bd4d0056b4db9ba1641e25e73cc63101085c7852045e8888bfd24f348
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

Release files / monai_weekly-0.8.dev2142-py3-none-any.whl

Download URL monai_weekly-0.8.dev2142-py3-none-any.whl
Size 666.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
0aa541c56bdeef8b556ff6d98646730ea50c52dd4551d164c9a548d2df9d013b
BLAKE2b-256 checksum
How to use checksums
44145362de351cf7c5da3cee22016fb3733568ca7816990d2b3392656e25ad82
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

Release history Release notifications | RSS feed

This release

0.8.dev2142 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page