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🌾 Crop Disease Detection 🚜
Detect crop diseases and check weather conditions effortlessly using deep learning and an intuitive web interface!
🌟 Overview
Welcome to the Crop Disease Detection project! This Django-based web application allows users to detect crop diseases by uploading an image or providing an image URL. It leverages a TensorFlow Lite (TFLite) model for predictions and includes additional features like weather updates for user convenience.
🌟 Features
- Upload Images 📷: Upload a crop image to analyze for diseases.
- Predict Diseases 🔍: Powered by TensorFlow Lite for accurate predictions with confidence levels.
🛠️ Technology Stack
- Backend: Django, Python
- Frontend: HTML, CSS, JavaScript
- Machine Learning: TensorFlow Lite
- Database: SQLite
⚙️ Setup and Installation
1️⃣ Clone the Repository
git clone https://github.com/KarthikB6360/Crop_Disease_Prediction.git
cd crop-disease
2️⃣ Install Dependencies
pip install -r requirements.txt
3️⃣ Apply Migrations
4️⃣ Run the Development Server
python manage.py runserver
Access the app at http://127.0.0.1:8000/. 🎉
🔬 How It Works
- **Upload IMG **: Use the interface to upload a crop image.
- Model Prediction: The uploaded image is resized, normalized, and passed to a TensorFlow Lite model for disease detection.
- Get Results: View the predicted disease name and confidence percentage.
🖼️ Screenshots
📸 Upload Page
![Upload Page] (image pending)
🔎 Prediction Results
![Prediction Result] (image pending)
📜 Usage Details
- File Upload: Click “Upload Image” to browse and upload a file.
🧩 Future Enhancements
- 🌍 Multi-language support.
- 📊 Detailed disease treatment recommendations.
- 📱 Mobile-friendly responsive design.
🌟 Acknowledgments
- TensorFlow Lite: For enabling lightweight ML predictions.
development