huehush 0.0.1

huehush is a Python module that provides functionality to segment images into distinct clusters using the K-means clustering algorithm. This module is useful for tasks such as image segmentation, color quantization, and image compression.

Chroma Squeeze

This Python module performs K-means clustering on an image to segment it into a specified number of clusters.

Installation

You can install the module via pip:

pip install chroma_squeeze==0.0.1

Usage

from chroma_squeeze import cluster_image

# Example usage:
cluster_image('input_image.jpg', num_clusters=5, save_path='clustered_image.jpg')

How it Works

The cluster_image function takes an input image, the number of clusters (K) to create, and an optional path to save the resulting clustered image. It applies K-means clustering to the colors in the image, replacing each pixel's color with the nearest cluster center.

Example

Here's an example of using cluster_image function:

cluster_image('input_image.jpg', num_clusters=5, save_path='clustered_image.jpg')

This would read the 'input_image.jpg', perform K-means clustering with 5 clusters, and save the resulting clustered image as 'clustered_image.jpg'.

License

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

Credits

• numpy
• matplotlib
• scikit-learn
• Pillow

Author

Aravind.M.S