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· 2 min read
Pajman Samadi
summary
  • An AI model for lung segmentation in CXR images, deploying with FastAPI.
  • Use DVC for data version control, and dockerizing web-app.
  • Deploy projects w/ K8s.

This app uses FastAPI as backend. Check repository on GitHub.

Usage for app.py​

First install required libraries by running:

pip install -r requirements.txt

To run the application run following command in src dir:

uvicorn app:app --reload

or

chmod +x app.sh
./app.sh

Tutorial for app.py​

app.gif

Tutorial​

main page​

http://localhost:8000/

main.png

fastapi documentation​

http://localhost:8000/docs

docs.png

show results​

http://localhost:8000/imshow

imshow.png

DVC​

pip install dvc dvc-gdrive

# pull weights from Google Drive
dvc pull

in weights directory

weights
├── cxr_resunet.tflite
├── cxr_resunet.tflite.dvc
├── cxr_unet.tflite
└── cxr_unet.tflite.dvc

Docker​

# Build image
docker build -t IMAGE_NAME:TAG_NAME .
docker run -p 8000:8000 -d IMAGE_NAME:TAG_NAME

Or

# for amd64 systems
docker run -d -p 8000:8000 pejmans21/ls-fastapi:0.1.0

#### OR

# for arm64 systems
docker run -d -p 8000:8000 pejmans21/ls-fastapi:aarch64

Kubernetes​

kubectl apply -f ls-fastapi-k8s-config.yaml

to see output

kubectl port-forward service/lsapi-service 8000

Now check http://127.0.0.1:8000/

Stop process​

kubectl delete -f ls-fastapi-k8s-config.yaml