Skip to main content
Pre-release

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

MONAI Label

License CI Build Documentation Status codecov PyPI version

MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI. It is an open-source and easy-to-install ecosystem that can run locally on a machine with one or two GPUs. Both server and client work on the same/different machine. However, initial support for multiple users is restricted. It shares the same principles with MONAI.

Brief Demo

Features

The codebase is currently under active development.

  • framework for developing and deploying MONAI Label Apps to train and infer AI models
  • compositional & portable APIs for ease of integration in existing workflows
  • customizable design for varying user expertise
  • 3DSlicer support

Installation

MONAI Label supports following OS with GPU/CUDA enabled.

To install the current release, you can simply run:

  pip install monailabel
  
  # download sample apps/dataset
  monailabel apps --download --name deepedit_left_atrium --output apps
  monailabel datasets --download --name Task02_Heart --output datasets
  
  # run server
  monailabel start_server --app apps\deepedit_left_atrium --studies datasets\Task02_Heart\imagesTr
  

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

Once you start the MONAI Label Server, by default it will be up and serving at http://127.0.0.1:8000/. Open the serving URL in browser. It will provide you the list of Rest APIs available.

3D Slicer

Download Preview Release from https://download.slicer.org/ and install MONAI Label plugin from Slicer Extension Manager.

Refer 3D Slicer plugin for other options to install and run MONAI Label plugin in 3D Slicer.

To avoid accidentally using an older Slicer version, you may want to uninstall any previously installed 3D Slicer package.

Contributing

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

Community

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

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

Metadata

Release files for monailabel-weekly 0.2.dev2134

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

Source distribution (sdist)

Source distribution for monailabel-weekly 0.2.dev2134
File Size Uploaded Provenance
monailabel-weekly-0.2.dev2134.tar.gz 3.8 MB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for monailabel-weekly 0.2.dev2134
File Interpreter ABI Platform
monailabel_weekly-0.2.dev2134-py3-none-any.whl Python 3 none any Details

Total release size: 7.7 MB

Release files / monailabel-weekly-0.2.dev2134.tar.gz

Download URL monailabel-weekly-0.2.dev2134.tar.gz
Size 3.8 MB
Tags Source
SHA-256 checksum
How to use checksums
50f0a64eda48bd6858881797c2bb5d99e8bef8202483216d12c48c8073cb1502
BLAKE2b-256 checksum
How to use checksums
a5490d91fc0c00e490e0cd21686d4015db33e0e807417420abefabf1c1a53e34
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.9.6

Release files / monailabel_weekly-0.2.dev2134-py3-none-any.whl

Download URL monailabel_weekly-0.2.dev2134-py3-none-any.whl
Size 3.9 MB
Tags Python 3
SHA-256 checksum
How to use checksums
f7df8ba778ea61d9e2949977b8564cf708b50332b957d22427d8881f763dc91a
BLAKE2b-256 checksum
How to use checksums
9dbec797fb34cb827ddc7e4dbc779d267d297c6338a0adde33c18d19e5011916
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.9.6

Security for monailabel-weekly 0.2.dev2134

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release
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