🌿 Plant Disease Detection with Weather-Aware Deep Learning (TFLite Version)

This project is a lightweight yet powerful web app for plant disease detection using deep learning models converted to TensorFlow Lite. It takes a plant leaf image as input and enhances the disease prediction by factoring in real-time weather data from the user’s location. The app returns Top-K disease predictions along with actionable recommendations.

🚀 Key Features

• ✅ Leaf Verification: Checks if the uploaded image is a plant leaf.
• 🌱 Plant Type Classification: Identifies the plant (apple, grape, corn, potato, etc).
• 🧠 Unified Disease Prediction: A single TFLite model predicts the disease with weather data as additional input
• ☁️ Live Weather Integration: Automatically fetches temperature, humidity, etc., based on user location
• 🎯 Top-K Predictions: Displays multiple possible diseases with confidence scores
• 🌐 Flask Web App Interface: User-friendly UI for image upload and results

🔗 Live Demo 🌐 Try it now: https://plant-disease-dl.onrender.com/

🔧 Installation & Setup

1. Clone the repository

--git clone https://github.com/AtharvaSamant4/Plant_Disease_DL.git

2. Install the required packages

-- pip install -r requirements.txt

3. Start the Flask server

-- python app.py

🛠 Tech Stack:

Python, Flask TensorFlow Lite HTML, CSS OpenWeatherMap API

📌 To-Do / Enhancements:

Add UI for mobile Expand to more plants Upload history for users

👤 Author

Atharva Samant https://github.com/AtharvaSamant4