Added Cataract disease Detection using Machine learning

[RajKhanke]

Resolves #174

This project involves developing a machine learning model to detect cataracts from eye images and deploying it using a Streamlit web application. The project begins with data preparation in a Colab notebook, where the cataract dataset, consisting of images categorized into 'Cataract' and 'Normal', is loaded and preprocessed. A Convolutional Neural Network (CNN) model is then built and trained for 10 epochs on this dataset. The model's performance is evaluated using accuracy, precision, recall, F1 score, a classification report, and a confusion matrix.

Once the model is trained and evaluated, it is saved in the H5 format for future use. The Streamlit application is developed to allow users to upload eye images and receive predictions on whether the image indicates cataract or not. The application displays prediction results using st.error for 'Cataract' and st.success for 'Normal', with proper alignment and CSS styling for a user-friendly interface. Additionally, the application provides comprehensive information about cataracts, including global prevalence, leading causes, remedies, and risks, fetched from reputable sources such as the WHO.

To enhance user experience, the application features embedded Google Maps links for users to locate nearby eye clinics and dieticians, initially focused on Pune, with an option to enter any city and redirect to Google Maps. The app also includes visual aids like pie charts to represent statistical data. Overall, this project combines image processing, machine learning, and web development to create a practical tool for cataract detection and information dissemination.

model : CNN

also done entire data analysis and data science steps.

deploy on streamlit application for proper user input - output .

webapp.mp4

[RajKhanke]

@Avdhesh-Varshney @Atharv714 @TAHIR0110 please merge this pr along with level and label , it will resolve issue no 174. please also look towards my other PR's of maternal health risk , HIV , Dementia.

[Avdhesh-Varshney]

LGTM.

[github-actions]

🎉 Your pull request has been successfully merged! 🎉 Thank you for your valuable contribution to our project. Your efforts are greatly appreciated. Feel free to reach out if you have any more contributions or if there's anything else we can assist you with. Keep up the fantastic work! 🚀