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End to end deep learning app. Applying containerization & kubernetes to practice. Task is of token classification.

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vqa-e2e

End to end visual question and answering application

Docker Commands

Building docker

docker build -t vqa-e2e .

Running docker

docker run -p 8501:8501 -p 8000:8000 vqa-e2e

Running docker interactive, // is important to turn off GitBash's automatic path conversion

docker run -it --rm vqa-e2e //bin/bash

Streamlit App

localhost:8501

FastAPI

localhost:8000/docs

Kubernetes

Save the Docker image locally

docker save vqa-e2e:latest -o image.tar

Use Minikube's docker daemon via minikube ssh to load the image. This command will SSH into the Minikube VM and execute the docker load command to load the Docker image from the image.tar file.

minikube ssh -- docker load -i image.tar

Create a Kubernetes deployment using the loaded Docker image.

kubectl apply -f deployment.yaml

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End to end deep learning app. Applying containerization & kubernetes to practice. Task is of token classification.

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