Colorblind Friendly Palette Generator
Design accessible, contrast-ready color schemes for UI/UX design, scientific charts, and data visualization in Python Seaborn or Matplotlib.
Standard Palette Guide
Proposed by Masataka Okabe and Kei Ito (2002). The gold standard for scientific journals to guarantee legibility across all forms of color blindness.
Engineered by IBM for maximum contrast perception. Ensures clarity for UI design elements, dashboards, and complex data graphs.
Native colorblind palette used by Python data scientists to build clear Matplotlib and Seaborn visualization figures without ambiguity.
Upload UI mockups or charts directly. Image processing is performed entirely in your browser client — no files are uploaded to any server.
Live Interactive Palette Builder
InteractiveUpload Image / Chart Simulator
Test your chart screenshot or interface design under vision deficiency filters.
FAQ
Everything you need to know about colorblind friendly palettes and accessibility.
What is the Okabe-Ito color palette?
The Okabe-Ito palette is a set of 8 distinct colors proposed by Masataka Okabe and Kei Ito in 2002. It is designed to be unambiguously distinguishable by people with various types of color vision deficiency (Protanopia, Deuteranopia, Tritanopia). It is considered the gold standard in scientific publishing.
How do I use colorblind palettes in Python Seaborn / Matplotlib?
You can use Seaborn's built-in palette by calling sns.color_palette("colorblind") or pass custom HEX codes into sns.set_palette(['#E69F00', '#56B4E9', ...]). Use the code exporter above to generate Python snippets instantly.
Which type of colorblindness is most common?
Deuteranopia (green-blindness) and Protanopia (red-blindness) are the most common, affecting approximately 8% of men and 0.5% of women of Northern European descent. Avoid relying solely on Red vs. Green contrast for critical information.