Felzenszwalb Graph Segmentation

Welcome to the felzenszwalb_graph_segmentation repository! This project implements the Felzenszwalb and Huttenlocher's graph-based image segmentation algorithm using Jupyter Notebooks.

Table of Contents

• Introduction
• Installation
• Usage
• Examples
• Contributing
• License

Introduction

This repository contains my implementation of the Felzenszwalb and Huttenlocher's graph-based image segmentation algorithm, done for my Image Processing and Applications class (CSD357). This algorithm is widely used for segmenting an image into visually coherent regions. The implementation is provided in a series of Jupyter Notebooks, allowing for easy experimentation and visualization of results.

Installation

To get started with this project, clone the repository and install the required dependencies.

git clone https://github.com/Ja-Crispy/felzenszwalb_graph_segmentation.git
cd felzenszwalb_graph_segmentation
pip install -r requirements.txt

Make sure you have Jupyter installed. If not, you can install it using the following command:

pip install jupyter

Usage

To use the segmentation algorithm, simply open the Jupyter Notebook and run the cells. The notebook has the code for defining the functions, implementing the algorithm, and finally, to see the output of executing the algorithm on the test files provided.

Contributing

Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request. Make sure to follow the contributing guidelines when submitting changes.

License

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