Pixel Segmentation Using k-means Clustering

Overview

Explore the realm of image processing with our project on pixel segmentation using k-means clustering. This tool is designed to demonstrate how k-means clustering can transform images into segmented visuals and compile the process into a GIF.

Features

• Image Segmentation: Utilize k-means to segment images by pixel color.
• Dynamic Visualization: Generate GIFs to visualize the segmentation process across different k-values.
• Customizable: Suitable for any image to experiment with segmentation levels.

Getting Started

Prerequisites

• Python 3.6+
• Libraries: numpy, OpenCV-python, Pillow

Installation

1. Clone the repository:

   git clone https://github.com/NisargBhavsar25/pixel-segmentation-using-kmeans.git

2. Navigate to the project directory:

   cd pixel-segmentation-using-kmeans

3. Install the required packages:

   pip install -r requirements.txt

Usage

Run the main script with an optional path to your image:

python main.py --path /path/to/your/image.jpg

• Default image path: images/input-image.jpg
• Output GIF: images/output.gif
• Segmented images: images/segmented-images/

Sample Input and Output

Input Image

Output GIF

Shows the segmentation process at varying levels of k-values.