Welcome to the Plant Disease Prediction App, an AI-powered tool to detect plant diseases from leaf images using deep learning and intelligent knowledge retrieval.
👉 https://plant-using-ht.onrender.com
⚠️ Please note: This project is hosted on Render's free tier, so it may take a few seconds to load if it hasn’t been accessed in the past 15 minutes.
As a student, I currently cannot afford the paid Render plan. Thank you for your patience and support!
This system is designed to help farmers, researchers, and gardeners by providing instant, reliable plant disease detection from leaf images. It uses a Convolutional Neural Network (CNN) model for classification, along with Wikipedia and Gemini 1.5 Flash (Google AI) to provide disease-related information and suggested remedies.
The model is trained using the PlantVillage dataset and saved in .h5 format.
📁 Download the trained model file (.h5)
| Technology | Purpose |
|---|---|
| TensorFlow / Keras | Deep learning & CNN for image classification |
| HTML, CSS, JS | Frontend for web interface |
| Flask | Python-based backend for handling requests |
| Streamlit | Additional UI layer for dynamic rendering |
| Wikipedia API | Primary source for disease info |
| Gemini 1.5 Flash | AI-generated fallback responses for reliability |
| NumPy & Pillow | Image and data processing |
- ✅ Upload plant leaf images to predict diseases in real time
- ✅ Display disease name, symptoms, and cure suggestions
- ✅ Dual-source knowledge (Wikipedia + Gemini AI)
- ✅ Fully responsive UI for mobile and desktop
- ✅ Lightweight, fast, and informative
- ✅ AI fallback ensures no empty responses
- User uploads an image of a diseased leaf.
- The backend (Flask + TensorFlow) runs inference using the trained CNN model.
- Once the disease is identified:
- The app fetches detailed info from Wikipedia.
- If Wikipedia lacks data, Gemini 1.5 Flash generates a reliable fallback answer.
- The user is shown disease name, symptoms, and treatment steps.
- 🚜 Crop disease detection for farmers
- 🧪 Tools for agriculture and biology researchers
- 📱 Instant mobile diagnostics in remote areas
- 🎓 Projects for AI and bioinformatics students
- 💡 Use in tech fairs, hackathons, and exhibitions
“This project is a meaningful blend of AI, computer vision, and real-world utility. It was made with a lot of learning, passion, and love for solving genuine problems in agriculture.”
Built with ❤️ as part of a student innovation journey. Inspired by a conversation titled "Plant Disease Prediction App" with ChatGPT (OpenAI), which guided the AI logic, deployment, and design philosophy.
Feel free to reach out if you'd like to contribute, share feedback, or showcase this project :
- GitHub: https://github.com/Dipukumar1997
- Email: [email protected]
- LinkedIn: LinkedIn Profile
💚 Let’s make agriculture smarter — one leaf at a time.