https://github.com/arefin994/verdantguard
VerdantGuard is an advanced plant disease prediction web application designed to help users identify plant diseases using cutting-edge AI models. This project includes a React frontend, a Node.js backend, and a Flask-based Deep Learning API for real-time disease detection. 🚀
https://github.com/arefin994/verdantguard
deep-learning expressjs flask mongodb nodejs react tensorflow
Last synced: 4 months ago
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VerdantGuard is an advanced plant disease prediction web application designed to help users identify plant diseases using cutting-edge AI models. This project includes a React frontend, a Node.js backend, and a Flask-based Deep Learning API for real-time disease detection. 🚀
- Host: GitHub
- URL: https://github.com/arefin994/verdantguard
- Owner: Arefin994
- Created: 2025-01-19T03:51:21.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-19T04:31:55.000Z (over 1 year ago)
- Last Synced: 2025-06-11T14:18:00.077Z (about 1 year ago)
- Topics: deep-learning, expressjs, flask, mongodb, nodejs, react, tensorflow
- Language: JavaScript
- Homepage:
- Size: 1.32 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🌱 VerdantGuard: Plant Disease Prediction Web App 🌿
VerdantGuard is an advanced plant disease prediction web application designed to help users identify plant diseases using cutting-edge AI models. This project includes a **React frontend**, a **Node.js backend**, and a **Flask-based Deep Learning API** for real-time disease detection. 🚀
---
## ✨ Features
- 🗼️ Upload images of plants for disease prediction.
- 📊 View detailed prediction results with confidence scores.
- 🌐 Fully responsive and user-friendly interface.
- 🔄 Real-time API integration for fast and accurate predictions.
- 🔐 Secure and robust backend with token-based authentication.
---
## 🛠️ Tech Stack
- **Frontend:** React.js + Tailwind CSS
- **Backend:** Node.js + Express.js
- **ML API:** Flask + TensorFlow + OpenCV
- **Database:** MongoDB
---
## ⚙️ Installation & Setup
Follow the steps below to run the project locally.
### Prerequisites
Make sure you have the following installed:
- Node.js >= 16.x
- Python >= 3.8
- MongoDB (Local or Atlas)
### 1⃣ Clone the Repository
```bash
git clone https://github.com/your-username/VerdantGuard.git
cd VerdantGuard
```
### 2⃣ Frontend Setup
Navigate to the `VerdantGuard_Frontend` folder:
```bash
cd VerdantGuard_Frontend
npm install
npm run dev
```
### 3⃣ Backend Setup
Navigate to the `VerdantGuard_Backend` folder:
```bash
cd ../VerdantGuard_Backend
npm install
npm run serve
```
### 4⃣ Flask API Setup
Navigate to the `VerdantGuard_Model_Api_Flask` folder:
```bash
cd ../VerdantGuard_Model_Api_Flask
pip install -r requirements.txt
python api.py
```
---
## 🌟 Usage
1. Start all three services: **Frontend**, **Backend**, and **Flask API**.
2. Open the frontend in your browser: [http://localhost:5173](http://localhost:5173)
3. Upload a plant image, and the app will return the predicted disease and confidence score.
---
## 📁 Project Structure
```plaintext
VerdantGuard/
├── VerdantGuard_Frontend/ # React frontend
├── VerdantGuard_Backend/ # Node.js backend
├── VerdantGuard_Model_Api_Flask/ # Flask API for ML model
└── README.md # Project documentation
```
---
### 📷 Screenshots (Optional)
Will add later
---
## 🌍 Environment Variables
Ensure you set up the following `.env` files:
### Frontend (`VerdantGuard_Frontend/.env`)
```plaintext
VITE_API_URL=http://localhost:5000
```
### Backend (`VerdantGuard_Backend/.env`)
```plaintext
MONGO_URI=mongodb://localhost:27017/verdantguard
JWT_SECRET=your-secret-key
PORT=5000
```
### Flask API (`VerdantGuard_Model_Api_Flask/.env`)
```plaintext
MODEL_PATH=./models/disease_model.h5
```
---
## 🤝 Contributing
Feel free contributions to improve VerdantGuard! Create an issue or submit a pull request to suggest enhancements. 💡
---
## 🚀 About the Author
Developed with ❤️ by [Arefin Amin](https://github.com/arefinamin). Connect with me on [LinkedIn](https://linkedin.com/in/arefinamin) or check out my other projects on [GitHub](https://github.com/arefinamin).
---