This project aims to identify accident zones using clustering techniques. It utilizes Flask, a Python web framework, to deploy a web application for identifying accident-prone areas based on provided data.
- Utilizes clustering and DB Scan algorithms to identify accident-prone areas.
- Provides a web interface for users to input data and visualize results.
- Implements Flask for the backend server and routing.
- Allows for customization of clustering algorithms and parameters.
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Clone the repository:
git clone https://github.com/Prureddy/identifying_accident_zones_using_clustering.git -
Navigate to the project directory:
cd identifying_accident_zones_using_clustering -
Install dependencies using pip:
pip install -r requirements.txt
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Run the Flask application:
python app.py -
Access the web application by visiting http://localhost:5000 in your web browser.
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Use the provided interface to input data and visualize accident-prone areas.
config.py: Contains configuration settings for the Flask application.
Contributions are welcome! Please feel free to submit issues, pull requests, or suggestions.
- This project was developed as part of my Freelancing Work