Codes are based on this github repo:
https://github.com/pejmanS21/LungSegmentation_Streamlit
I use streamlit as frontend for application and it's sending requests to backend for Flask. all the predictions and processes will run in backend and results will send to frontend for visualization.
In order to get the best performance, you have to run streamlit server and flask server at the same time.
so you can:
chmod +x start.sh
./start.sh
chmod +x run.sh
./run.sh
or
chmod +x main.sh
./main.sh
in terminal, also you can run main.py to start the application, as well as mentioned methods.
after that application will be serving on Local URL http://localhost:8501
and Network URL http://192.168.1.6:8501. flask will serve on port :5000
you can use pretrained weights for models from here:
https://github.com/pejmanS21/LungSegmentation_Streamlit/tree/master/weigths