jonasdieker / image_classification_ml_app

Simple ML web app using FastAPI for the backend and Streamlit for the frontend

ML App for Classifying Images

The model was training on CIFAR10 and thus only supports the following classes:

["airplane", "car", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck"]

You can download model weights, download the code, run docker-compose to build and run the backend and frontend with the following steps:

Download model weights

Place the model weights in folder image_classification_ml_app/state_dicts.

Model weights to Google drive for weights of simple VGG model trained on CIFAR10 dataset.

Install locally

git clone [email protected]:jonasdieker/image_classification_ml_app.git
cd image_classification_ml_app
docker-compose up -d --build

Then go to http://localhost:8501/ to interact with the web app and classify some images!