🎨 Color Palette Creator

Use K-Means clustering to compress image colors!

🎮 Controls

🏆 Challenge:

Find the minimum K that keeps the image recognizable!

Target: < 10 colors, Quality> 80%

Original Colors:0
Compressed Colors:0
Compression:0%
Quality Score:0%

💡 How K-Means Works:

1. Pick K random colors (centroids)
2. Assign each pixel to nearest centroid
3. Update centroids to cluster average
4. Repeat until converged

Result: Image uses only K colors!

Compression Score

0

Balance compression ratio vs image quality

Original Image

Compressed (K-Means)

Color Palette:

Compress an image to see the color palette!

📚 Real-World Applications

K-Means color quantization is used in: GIF compression (limited to 256 colors), image optimization for web (reduce file size), color palette extraction for design, and image segmentation in computer vision. By reducing the number of colors, we can dramatically reduce file sizes while maintaining visual quality - perfect for faster web loading times!