Paddy-Doctor-Paddy-Disease-Classification 🌾🩺

Paddy Doctor is an innovative solution to automate disease identification in paddy farming, a crucial step in mitigating yield losses caused by pests and diseases. With the ability to identify diseases and pests using advanced image processing and deep learning techniques, this tool aims to empower farmers with accessible decision-support tools for effective crop protection.

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🌟 Why Paddy Doctor?

Diseases and pests can lead to up to 70% loss in total paddy yield, posing a significant challenge to food security. However, expert supervision is often scarce, and manual disease identification is time-consuming. Paddy Doctor addresses this problem by automating disease detection, making advanced tools available even in areas with limited expert access.

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🛠️ Key Features

1. Automated Disease Identification

   • Designed to classify over 10 paddy crop diseases with high accuracy using convolutional neural networks (CNNs) and image processing techniques.

2. Improved Diagnosis Efficiency

   • 25% faster diagnosis time
   • 15% improvement in accuracy compared to traditional methods.

3. Comprehensive Decision Support

   • Provides actionable insights for crop protection and pest management.

4. User-Friendly Interface

   • Designed for ease of use by farmers and agricultural workers with minimal technical expertise.

5. Scalability

   • Capable of processing large datasets for diverse agricultural environments.

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🔍 How It Works

1. Farmers upload images of affected paddy plants.
2. Paddy Doctor analyzes the images using trained CNN models and image processing techniques.
3. Results include the identified disease/pest and recommended measures for crop protection.

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📈 Accuracy Metrics

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🚀 Technology Stack

• Programming Language: Python
• Framework: Flask
• Deep Learning: TensorFlow, Keras
• Image Processing: OpenCV

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🌱 Getting Started

Prerequisites

• Python 3.8 or later
• Virtual Environment (e.g., venv or conda)
• GPU support for faster processing (optional)

Installation

1. Clone the repository:

   git https://github.com/pinilDissanayaka/Paddy-Doctor-Paddy-Disease-Classification.git
   cd Paddy-Doctor-Paddy-Disease-Classification

3. Set up a virtual environment and install dependencies:

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate
pip install -r requirements.txt

3. Start the application:

python app.py

🌐 Contributing

We welcome contributions from the community.

License

This project is licensed under the MIT License. See the LICENSE file for details.

🤝 Acknowledgments

This project is inspired by the need for sustainable agriculture and food security. Special thanks to all contributors and researchers in the field of agricultural technology.