Simple example of usage of streamlit and FastAPI for ML model serving described on https://davidefiocco.github.io/2020/06/27/streamlit-fastapi-ml-serving.html.
When developing simple APIs that serve machine learning models, it can be useful to have both a backend (with API documentation) for other applications to call and a frontend for users to experiment with the functionality.
In this example, we serve an image semantic segmentation model using FastAPI for the backend service and streamlit for the frontend service. docker-compose orchestrates the two services and allows communication between them.
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