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Vine Leaf Disease Detection

A machine learning-based web application that uses convolutional neural networks (CNNs) to detect vine leaf diseases. This project features a full-stack implementation with a React front-end, Flask back-end, and Firebase integration.

Award Nomination

This project was nominated for the Best Project of the Year Award, showcasing its innovation and technical excellence.

Features

  • Image-based disease detection using trained CNN models.
  • Upload leaf images and receive predictions in real-time.
  • Interactive front-end interface for visualization of results.
  • Secure data handling with Firebase integration.

Technologies Used

  • Frontend: React, CSS

  • Backend: Flask, TensorFlow

  • Database: Firebase

  • Machine Learning: Convolutional Neural Networks

    Redownload node modules

In this project there are a couple of things you need to do to make it run.

  1. Redownload the node modules using npm install

  2. Direct yourself to the main directory of the project ensuring the directory is in FinalYearProject

  3. To start the project run npm start

  4. in a seperate terminal direct yourself to Backend

  5. Make sure youre in the Backend directory and run either python3 server.py or python server.py

Getting Started with Create React App

This project was bootstrapped with Create React App.

Available Scripts

In the project directory, you can run:

npm start

Runs the app in the development mode.
Open http://localhost:3000 to view it in your browser.

The page will reload when you make changes.
You may also see any lint errors in the console.

npm test

Launches the test runner in the interactive watch mode.
See the section about running tests for more information.

npm run build

Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.

The build is minified and the filenames include the hashes.
Your app is ready to be deployed!

See the section about deployment for more information.

npm run eject

Note: this is a one-way operation. Once you eject, you can't go back!

If you aren't satisfied with the build tool and configuration choices, you can eject at any time. This command will remove the single build dependency from your project.

Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject will still work, but they will point to the copied scripts so you can tweak them. At this point you're on your own.

You don't have to ever use eject. The curated feature set is suitable for small and middle deployments, and you shouldn't feel obligated to use this feature. However we understand that this tool wouldn't be useful if you couldn't customize it when you are ready for it.

Learn More

You can learn more in the Create React App documentation.

To learn React, check out the React documentation.

Code Splitting

This section has moved here: https://facebook.github.io/create-react-app/docs/code-splitting

Analyzing the Bundle Size

This section has moved here: https://facebook.github.io/create-react-app/docs/analyzing-the-bundle-size

Making a Progressive Web App

This section has moved here: https://facebook.github.io/create-react-app/docs/making-a-progressive-web-app

Advanced Configuration

This section has moved here: https://facebook.github.io/create-react-app/docs/advanced-configuration

Deployment

This section has moved here: https://facebook.github.io/create-react-app/docs/deployment

npm run build fails to minify

This section has moved here: https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify

About

Final Year Project - A machine learning-based web application using convolutional neural networks (CNNs) to detect vine leaf diseases. Includes a full-stack implementation with an interactive front-end and Firebase integration.

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