A project to showcase model deployment using Flask and Streamlit
I chose an image classification problem for this task. Specifically, I used CIFAR-100 dataset to train Effnet-b2 model. Due to computational limitations, I only trained for 10 epochs. However, I managed to achieve accuracy of 0.88.
Accuracy: 0.88
Everything runs via docker compose
docker compose up
Got localhost:3000
for Streamlit
Currenly, only one route is avaliable
POST /classify
Here's an example curl command
curl --location 'localhost:8000/classify' \
--form 'image=@"/path/to/img.png"'
Any PIL compatable image works
Output in the class of the image