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Machine Learning (Imagenet) User Interface Demo application using Streamlit

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streamlit-ml-demo

A demo application to showcase the responsive UI for ImageNet using Streamlit. Streamlit provides an alternative to building full stack applications for the Machine Learning interface. Here, streamlit is used to upload an image for inference from the model.

Screenshot of the demo application

This demo is created using Streamlit.

The ImageNet model code using TensorFlow has been adapted from PyImageSearch

How to Run?

Install the requirements

pip install -r requirements.txt

Run the application

streamlit run ml_frontend.py

The application will run on localhost:8501 by default.

Sample Screenshots

Screenshot from a PC Screenshot from Mobile Device

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Machine Learning (Imagenet) User Interface Demo application using Streamlit

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