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Graph Analyzer

Graph Analyzer is a Django-based web application that allows users to upload an image of a graph, extract the underlying data, and analyze it for key features such as minima, maxima, and predicted future values. This tool is useful for visualizing network traffic or analyzing real-world data represented in graph form, including the scientific and financial data.

Installation and Setup

Prerequisites

Ensure you have the following installed:

  • Python 3.8+
  • pip (Python package manager)
  • Django 4.x
  • OpenCV 4.x
  • NumPy
  • scikit-learn

Clone the Repository

git clone https://github.com/<your_username>/Graph-Analyzer.git
cd Graph-Analyzer

Create a Virtual Environment

python3 -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

Install Dependencies

pip install -r requirements.txt

Apply Migrations

python manage.py migrate

Run the Development Server

python manage.py runserver

Visit http://127.0.0.1:8000/ in your browser to start uploading graph images.

Usage

  1. Upload a Graph Image: Navigate to the home page and choose an image file that contains a graph.
  2. Graph Analysis: The application will process the image, extract data points, and find the minima, maxima, and predict the next 5 values.
  3. View Results: Once processed, the results will display the detected minima, maxima, and predicted values.

Example Workflow

  1. Step 1: Upload an image of a line graph showing time vs network traffic.
  2. Step 2: The application extracts the data points from the image.
  3. Step 3: Minima, maxima, and the next 5 values are calculated and displayed on the home page.

Troubleshooting

If you encounter issues with the image not loading properly or the image processing functions failing, ensure that:

  • The image is correctly uploaded.
  • The image path is accessible to the application (check permissions and file locations).

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature-name)
  3. Commit your changes (git commit -m "Add some feature")
  4. Push to the branch (git push origin feature-name)
  5. Open a pull request

License

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