Metadata-Version: 2.1
Name: monai-weekly
Version: 0.6.dev2121
Summary: AI Toolkit for Healthcare Imaging
Home-page: https://monai.io/
Author: MONAI Consortium
Author-email: monai.contact@gmail.com
License: Apache License 2.0
Project-URL: Documentation, https://docs.monai.io/
Project-URL: Bug Tracker, https://github.com/Project-MONAI/MONAI/issues
Project-URL: Source Code, https://github.com/Project-MONAI/MONAI
Description: <p align="center">
          <img src="https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/MONAI-logo-color.png" width="50%" alt='project-monai'>
        </p>
        
        **M**edical **O**pen **N**etwork for **AI**
        
        [![License](https://img.shields.io/badge/license-Apache%202.0-green.svg)](https://opensource.org/licenses/Apache-2.0)
        [![CI Build](https://github.com/Project-MONAI/MONAI/workflows/build/badge.svg?branch=dev)](https://github.com/Project-MONAI/MONAI/commits/dev)
        [![Documentation Status](https://readthedocs.org/projects/monai/badge/?version=latest)](https://docs.monai.io/en/latest/?badge=latest)
        [![codecov](https://codecov.io/gh/Project-MONAI/MONAI/branch/dev/graph/badge.svg)](https://codecov.io/gh/Project-MONAI/MONAI)
        [![PyPI version](https://badge.fury.io/py/monai.svg)](https://badge.fury.io/py/monai)
        
        MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](LICENSE) framework for deep learning in healthcare imaging, part of [PyTorch Ecosystem](https://pytorch.org/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](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) 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](https://pypi.org/project/monai/), you can simply run:
        
        ```bash
        pip install monai
        ```
        
        For other installation methods (using the default GitHub branch, using Docker, etc.), please refer to [the installation guide](https://docs.monai.io/en/latest/installation.html).
        
        ## Getting Started
        
        [MedNIST demo](https://colab.research.google.com/drive/1wy8XUSnNWlhDNazFdvGBHLfdkGvOHBKe) and [MONAI for PyTorch Users](https://colab.research.google.com/drive/1boqy7ENpKrqaJoxFlbHIBnIODAs1Ih1T) are available on Colab.
        
        Examples and notebook tutorials are located at [Project-MONAI/tutorials](https://github.com/Project-MONAI/tutorials).
        
        Technical documentation is available at [docs.monai.io](https://docs.monai.io).
        
        ## Contributing
        For guidance on making a contribution to MONAI, see the [contributing guidelines](CONTRIBUTING.md).
        
        ## Community
        Join the conversation on Twitter [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9).
        
        Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions).
        
        ## Links
        - Website: https://monai.io/
        - API documentation: https://docs.monai.io
        - Code: https://github.com/Project-MONAI/MONAI
        - Project tracker: https://github.com/Project-MONAI/MONAI/projects
        - Issue tracker: https://github.com/Project-MONAI/MONAI/issues
        - Wiki: https://github.com/Project-MONAI/MONAI/wiki
        - Test status: https://github.com/Project-MONAI/MONAI/actions
        - PyPI package: https://pypi.org/project/monai/
        - Weekly previews: https://pypi.org/project/monai-weekly/
        - Docker Hub: https://hub.docker.com/r/projectmonai/monai
        
Platform: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown; charset=UTF-8
Provides-Extra: all
Provides-Extra: nibabel
Provides-Extra: skimage
Provides-Extra: pillow
Provides-Extra: tensorboard
Provides-Extra: gdown
Provides-Extra: ignite
Provides-Extra: torchvision
Provides-Extra: itk
Provides-Extra: tqdm
Provides-Extra: lmdb
Provides-Extra: psutil
Provides-Extra: cucim
Provides-Extra: openslide
