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eXAI Image Insights


BACKEND

To run with Python Virtual Environment

  • Clone the project
git clone https://github.com/Error-404-UCD/eXAI
cd eXAI/Backend
  • Setup the virtual environment for backend (Discard if pyenv already created)
python -m venv pyenv
  • Start the virtual environment
source pyenv/bin/activate
  • Install the requirements
pip install -r requirements.txt
  • In the backend directory create folders named data and models
  • In models directory create another folder checkpoints
  • Download and extract the datasets in the data folder such that the path would be example, data/Astronomy/galaxies_heic0007b.jpg
  • Make sure that the datasets contain images that store classname_ in it's file name
  • Start the server in the Backend folder so that the paths are correctly received in the main file
python app/server_launch.py
  • Run unit tests with
python -m unittest discover -s tests

To run with Docker

  • Clone the project
git clone https://github.com/Error-404-UCD/eXAI
cd eXAI/Backend
  • Build the docker image
 docker build -t docker-exai . 
  • Run the docker container. Here the port numbers are in the format > frontend_portnumber:docker_backend_portnumber. Make sure to write the frontend_port number in the React POST request URL (127.0.0.1:5000). HERE frontend_portnumber= 5000 and docker_backend_portnumber= 5000
 docker run -p 5000:5000 docker-exai  
  • Wait for the model to train and the server to start. It will display a localhost URL. Note that the port number of this URL is connected to the exposed docker_backend_portnumber.

FRONTEND

  • Change Directory to Frontend
cd Frontend
  • Install NPM packages
npm install
  • Start react server
npm start

Download the datasets from here


Refer Google Coding Style guide to push into repository


Dataset sources

AWS Setup Guide

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A Full Stack Explainable AI approach for Displaying LIME & SHAP explanations

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