A framework and associated tools to design, verify and analyze performance of MONAI apps
Project description
💡 If you want to know more about MONAI Deploy WG vision, overall structure, and guidelines, please read https://github.com/Project-MONAI/monai-deploy first.
MONAI Deploy App SDK
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
Features
- Build medical imaging inference applications using a flexible, extensible & usable Pythonic API
- Easy management of inference applications via programmable Directed Acyclic Graphs (DAGs)
- Built-in operators to load DICOM data to be ingested in an inference app
- Out-of-the-box support for in-proc PyTorch based inference
- Easy incorporation of MONAI based pre and post transformations in the inference application
- Package inference application with a single command into a portable MONAI Application Package
- Locally run and debug your inference application using App Runner
Installation
To install the current release, you can simply run:
pip install monai-deploy-app-sdk # '--pre' to install a pre-release version.
Getting Started
pip install monai-deploy-app-sdk # '--pre' to install a pre-release version.
# Clone monai-deploy-app-sdk repository for accessing examples.
git clone https://github.com/Project-MONAI/monai-deploy-app-sdk.git
cd monai-deploy-app-sdk
# Install necessary dependencies for simple_imaging_app
pip install scikit-image
# Execute the app locally
python examples/apps/simple_imaging_app/app.py -i examples/apps/simple_imaging_app/brain_mr_input.jpg -o output
# Package app (creating MAP Docker image), using `-l DEBUG` option to see progress.
monai-deploy package examples/apps/simple_imaging_app -t simple_app:latest -l DEBUG
# Run the app with docker image and an input file locally
## Copy a test input file to 'input' folder
mkdir -p input && rm -rf input/*
cp examples/apps/simple_imaging_app/brain_mr_input.jpg input/
## Launch the app
monai-deploy run simple_app:latest input output
MedNIST demo is available on Colab.
Examples and notebook tutorials are located at Project-MONAI/monai-deploy-app-sdk.
Technical documentation is available at docs.monai.io.
Contributing
For guidance on making a contribution to MONAI Deploy App SDK, see the contributing guidelines.
Community
To participate in the MONAI Deploy WG, please review https://github.com/Project-MONAI/MONAI/wiki/Deploy-Working-Group.
Join the conversation on Twitter @ProjectMONAI or join our Slack channel.
Ask and answer questions over on MONAI Deploy App SDK's GitHub Discussions tab.
Links
- Website: https://monai.io
- API documentation: https://docs.monai.io/projects/monai-deploy-app-sdk
- Code: https://github.com/Project-MONAI/monai-deploy-app-sdk
- Project tracker: https://github.com/Project-MONAI/monai-deploy-app-sdk/projects
- Issue tracker: https://github.com/Project-MONAI/monai-deploy-app-sdk/issues
- Wiki: https://github.com/Project-MONAI/monai-deploy-app-sdk/wiki
- Test status: https://github.com/Project-MONAI/monai-deploy-app-sdk/actions
- PyPI package: http://mirror-pypi-de.runflare.com/project/monai-deploy-app-sdk
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