This repository contains the implementation of a graph-based image segmentation algorithm. It was developed as an assignment for a computer vision post-graduate course.
Image segmentation is a fundamental task in computer vision, aiming to partition an image into meaningful regions. The graph-based image segmentation algorithm used in this project utilizes the concepts of graph theory to identify homogeneous regions within an image.
Below is an example that demonstrates the original image and its corresponding segmented output:
In the example above, the algorithm successfully separates the objects in the image into distinct regions, enabling further analysis and processing.
To use this implementation, follow these steps:
- Clone the repository:
git clone https://github.com/igeor/Graph-based-Image-Segmentation.git- Navigate to the repository:
cd Graph-based-Image-Segmentation- Run the segmentation algorithm on your desired image:
python run.py --image_path images/your_image.jpg --image_size 128 --sigma 4. --neigh 3 --K 120