KIRAN-KUMAR-K3/Image-Color-Compression-using-K-Means

A Python tool that compresses images using K-Means, shows both the original and compressed images, and lets you save the compressed version while displaying file sizes.

Image Color Compression using K-Means

This project demonstrates color compression of images using the K-Means clustering algorithm. The main script main.py allows you to select an image file, specify the number of colors for compression, and saves the compressed image to an outputs directory.

Features

• Image Input: Supports PNG, JPG, JPEG, BMP, and GIF images.
• Color Compression: Utilizes K-Means clustering to reduce the number of distinct colors.
• File Size Information: Displays original and compressed image file sizes.
• Output: Saves the compressed image to an outputs directory and displays both the original and compressed images side by side.

Requirements

• Python 3.x
• Pillow (PIL)
• NumPy
• Matplotlib
• scikit-learn

Installation

1. Clone the repository:

   git clone https://github.com/KIRAN-KUMAR-K3/Image-Color-Compression-using-K-Means.git
   cd Image-Color-Compression-using-K-Means

2. Install dependencies:

   pip install -r requirements.txt

Usage

1. Ensure you have images in the images directory.
2. Run main.py:

   python main.py

3. Follow the prompts to:
   • Enter the path to the image file.
   • Specify the number of colors for compression.
   • Save the compressed image to the outputs directory.
4. View the original and compressed images, as well as their file sizes.

Example

License

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