https://github.com/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.
https://github.com/kiran-kumar-k3/image-color-compression-using-k-means

images matplotlib numpy pillow python scikit-learn

Last synced: about 3 hours ago
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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.

• Host: GitHub
• URL: https://github.com/kiran-kumar-k3/image-color-compression-using-k-means
• Owner: KIRAN-KUMAR-K3
• License: mit
• Created: 2024-07-17T20:52:01.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-08-04T08:34:01.000Z (5 months ago)
• Last Synced: 2024-11-12T10:20:45.943Z (2 months ago)
• Topics: images, matplotlib, numpy, pillow, python, scikit-learn
• Language: Python
• Homepage:
• Size: 2.05 MB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        

# 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:

   ```bash

   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:

   ```bash

   pip install -r requirements.txt

   ```

## Usage

1. Ensure you have images in the `images` directory.

2. Run `main.py`:

   ```bash

   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

![Original and Compressed Image](images/comparision.png)

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.