CultiKure - Plant Disease Prediction Web Application

CultiKure is a web-based tool designed to help users detect and address diseases in plants. By analyzing images of plant leaves, this application employs advanced AI technology to identify potential plant health issues, ensuring healthier crops and better yields.

Key Features:

• AI-Powered Disease Detection: Upload plant leaf images to get real-time analysis and detection of diseases.
• Informative Reports: Receive detailed reports about detected diseases, including descriptions, preventive measures, and product recommendations.
• Supplement Market: Explore a selection of supplements and fertilizers to support plant health.
• User-Friendly Interface: An intuitive and easy-to-navigate interface for a seamless user experience.

Technologies Used:

• AI Model: VGG (Visual Geometry Group) model for image analysis.
• Web Framework: Flask for the back-end.
• Front-end: HTML, CSS, JavaScript.
• Libraries/Frameworks: Bootstrap for styling.

How to Use:

1. Navigate to the CultiKure Web Application
2. Upload an image of a plant leaf.
3. Receive detailed information about the detected disease, including tips and product recommendations.

Why Plant Disease Detection Matters:

Plant diseases can significantly impact crop health and yield. Early detection and intervention are crucial. CultiKure helps users identify and address potential issues, ensuring healthier crops and better yields.

Installation:

1. Clone the repository:

   git clone https://github.com/yourusername/CultiKure.git

2. Install Python Packages

   pip install -r requirements.txt

3.Activate Virtual-Environment (.venv )

   ./activate.bat

4.Activate the virtual environment

source ./venv/bin/activate

5.Run the Django server:

python manage.py runserver   

Video-Demonstration

Video.mp4

Contributions

1. Ansh Joshi
2. Bhavik Sharma
3. Bhavika Darpe
4. Devendra Singh Pawar