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Tensorflow-based Object Detection on the CIFAR-10 dataset, served with FastAPI

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FastAPI TensorFlow Serving

Python Tensorflow FastAPI Jupyter Docker

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GitHub project for Tensorflow-based Object Detection on the CIFAR-10 dataset, served with FastAPI.

Tech Stack

Up and Running

Developer Setup

1. Create and activate a virtualenv with conda:

conda create -n tfserve python=3.11 -y
conda activate tfserve

2. Install the dependencies on pyproject.toml:

pdm sync --no-self

3. Start the app with gunicorn with:

uvicorn --app-dir app/ main:app --host 0.0.0.0 --port 8000 --reload

or simply execute:

make run

4. Access the Swagger UI at:

open http://localhost:8000

Containerization and Testing

1. Build the Docker Image with:

make docker-image

2. Spin up the container with:

make docker-run

3. Access the Swagger UI at:

open http://localhost:8000

TODO

  • PEP-517: Packaging and dependency management with PDM
  • Code format/lint with Ruff
  • Run on Docker
  • Serve it with Streamlit
  • GitHub CI

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Tensorflow-based Object Detection on the CIFAR-10 dataset, served with FastAPI

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