Skip to content

zeroruntime/DetectMe-frontend

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

🌿 Plant Disease Detector - React Native App

This is a React Native mobile app built with Expo that allows users to capture or upload plant images and detect potential diseases using a Flask-based AI model. 🚀


📌 Features

Camera Integration – Capture plant images directly
Gallery Upload – Select images from the device
AI Disease Detection – Sends images to the Flask API for predictions
Clean UI – User-friendly interface with smooth navigation
Multi-Screen Navigation – Organized structure using Expo Router


📂 Project Structure

plant-disease-detector/
├── app/                # Main screens
│   ├── index.js        # Home screen
│   ├── _layout.js      # Layout wrapper for navigation
│   ├── camera.js       # Camera functionality
│   ├── results.js      # Displays prediction results
│   └── about.js        # About page
├── components/         # Reusable UI components
│   ├── Button.js       
│   ├── DiseaseCard.js  
│   ├── Header.js       
│   └── LoadingOverlay.js  
├── services/           # API communication
│   └── api.js          
├── constants/          # UI constants (Colors, Layout)
│   ├── Colors.js       
│   └── Layout.js       
├── assets/             # Static assets (images, fonts)
│   ├── images/         
│   └── fonts/          
├── app.json            # Expo configuration  
├── babel.config.js     # Babel settings  
├── package.json        # Dependencies & scripts  
└── README.md           # Documentation  

🔧 Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/zeroruntime/DetectMe-frontend.git
cd DetectMe-frontend

2️⃣ Install Dependencies

Make sure you have Node.js and Expo CLI installed.

npm install

3️⃣ Start the App

For Android:

npm run android

For iOS (Mac only):

npm run ios

For Web Preview:

npm run web

For Expo:

npx expo start

📡 API Integration

The app communicates with the Flask backend for disease detection.
Modify services/api.js to match your backend URL:

import axios from 'axios';

const API_URL = 'http://your-backend-ip:5000';

📜 Dependencies

📌 Key libraries used in this project:

  • expo-camera – Capture images
  • expo-image-picker – Upload from gallery
  • axios – API requests
  • react-navigation – Multi-screen navigation

Install missing dependencies with:

npm install

📸 Screens

1️⃣ Home Screen – Welcome screen with buttons to capture or upload images
2️⃣ Camera Screen – Uses device camera to take pictures
3️⃣ Results Screen – Displays disease predictions and confidence score


🔗 Future Enhancements

✅ Improve UI/UX with better styling
✅ Support more plant diseases
✅ Offline prediction using on-device TensorFlow


🤝 Contributing

Feel free to fork, create issues, or submit PRs! 🎉


🏷 License

MIT License © 2025 DetectMe Team


About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published