Ocular Disease Image Recognition

Introduction

This repository contains the source code of our project with the Department of Computer Science, Kirori Mal College. The project aims to develop a deep learning model to classify the type of ocular disease from the fundus images of the eye. The model is trained on the Kaggle dataset.

Folder Structure

├───Backend
|───DL-Project
├───Frontend
├───Practice

The Backend folder contains the code for the backend of the web application. The DL-Project folder contains the code for the deep learning model. The Frontend folder contains the code for the frontend of the web application. The Practice folder contains the code for the practice notebooks.

Important Links

• Link to web application: https://dl-predictor.netlify.app/
• Link to project report: Report.pdf

Note: The web appliation can take upto 10 minutes to start after uploading the image since backend container is deployed on free azure server.

Note: The deplyoyed application is only for educational purposes and the model may not give correct results.

Contributors

• Ms. Geethanjali Kher
• Vaibhav Sachdeva
• Manik Jain

Acknowledgements

The project was carried out under the guidance of Ms. Geethanjali Kher, Department of Computer Science, Kirori Mal College, University of Delhi. Thank you for your support and guidance throughout the project.