This Python script extracts the dominant color palette from an image and displays it along with color information in various formats (RGB, Hex, and CMYK). The script uses the K-Means clustering algorithm from scikit-learn to identify the most prominent colors.

1. Ensure you have the required Python libraries installed: Pillow (PIL), NumPy, Matplotlib, and scikit-learn.

   pip install Pillow numpy matplotlib scikit-learn
   

2. Replace "photo.jpg" with the path to your desired image in the following line:

   img = Image.open(`"photo.jpg"`)
   

3. Run the script:

   python extract-color.py
   

4. The script will display the following:

• The original image.
• The extracted color palette in a visual format.
• Detailed color information, including RGB, Hexadecimal, and CMYK values.

• The rgb_to_cmyk function is used to convert RGB values to CMYK values.
• The image is loaded, and its pixel matrix is flattened for analysis.
• The script identifies a specified number of dominant colors using K-Means clustering.
• The dominant colors are presented in both hexadecimal and RGB formats.
• CMYK values are calculated and displayed alongside RGB and Hex values.

Original code Link: https://twitter.com/clcoding/status/1711620072001901050

Result

• clcoding

• Eduanayardo

Feel free to customize and use this script to analyze and visualize color palettes in images.

Note: Please ensure that you have the necessary image ("photo.jpg" in this example) available or replace it with the path to your preferred image.