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Algorithmic Quartet Image Generation

Building a Pokemon Image Generator with MLOps best practices!

Flow Chart of the pipeline

Training Pipeline

The training is done with PyTorch and HuggingFace on Lightning.ai Studios. The data for it is stored on a GCP Cloud Bucket and downloaded to the GPU device for training.

Frontend

The frontend is a streamlit UI that renders the generated images.
It is continously deployed with GCP Cloud Build and is live on a GCP Cloud Run instance.

Backend

The image generation service uses FastAPI to serve the latest trained model and runs on a GCP Cloud Run instance.

Automated training & Continous Delivery

Autmated Training is described best in this video: https://vimeo.com/948396185

The Frontend and Backend are both built and deployed automatically when a Git Tag is added to a certain commit with either a frontend/VERSION or backend/VERSION.

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A showcase Machine Learning Operations (MLOps) Project.

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