iWantHue

iWantHue generates and refines color palettes for data scientists, with data visualization as a stated use. Users can set hue, chroma, and lightness constraints, then sort colors by difference, hue, chroma, lightness, or randomly. The generator computes colors in CIE Lab and uses HCL to set constraints. It offers k-means clustering and force-vector repulsion to distribute colors, plus an option to improve palettes for colorblind users. The web interface exports HEX, RGB, HCL, and LAB JSON, CSS color lists, and JavaScript settings. Developers can install the JavaScript package with npm for Node.js or browser use; its generator accepts a seed to reproduce a palette. The package also includes precomputed palettes from 2 to 15 colors, with colorblind alternatives. Very large palettes can contain similar colors when the selected color space cannot provide enough distinction, though the first colors are ordered for the greatest possible separation. The Fancy preset is limited to generic palettes of up to 10 colors because of its narrow chroma and lightness ranges. iWantHue is free, and help or bug reports are directed to GitHub Issues.

iWantHue offers detailed palette controls, multiple generation methods, and several export options at no cost. Users requesting large palettes should account for possible similarity among colors.

iWantHue suits data scientists and developers who need to build or refine palettes for data visualization. Its export formats and JavaScript package also suit users who want palettes in code or stylesheets.

iWantHue is a free palette generator built around color distinction in data visualization. It is best suited to data scientists and developers who want control over how colors are distributed and a way to reproduce palettes in JavaScript. Its perceptual controls and export choices make it a focused tool for that work.

Overview

Instead of choosing from a fixed collection, users shape palettes by hue, chroma, and lightness. iWantHue computes colors in CIE Lab and uses HCL to set those constraints, giving users direct control over the palette’s color range. Results can then be sorted by difference, hue, chroma, lightness, or randomly. That refinement is useful when the order or separation of colors matters to a visualization, but it gives the tool a more technical focus than a general-purpose palette picker.

Palettes are generated with either k-means clustering or force-vector repulsion. Both methods distribute colors within the chosen constraints, while a colorblind improvement option and JavaScript colorblind distance functions provide additional ways to account for accessibility. These features support careful palette design, though they do not remove the limits of the selected color space: with a large enough request, some colors may be similar. The first colors are sorted to be as distinct as possible.

Key features

The web interface exports HEX, RGB, HCL, and LAB JSON, along with CSS color lists and JavaScript settings. This is a practical range for moving a palette into code or a stylesheet without manually converting each color. Developers can install the project with npm for Node.js or browser use and generate palettes in JavaScript. A seed can reproduce the same palette from a data attribute, which helps when a visualization needs consistent colors across runs. The npm module also includes precomputed palettes from two to 15 colors, including colorblind alternatives.

The Fancy preset produces generic palettes up to 10 colors. Its narrow chroma and lightness ranges constrain the maximum palette size, so users who need more colors should expect to adjust their approach rather than rely on that preset.

Pricing

iWantHue is free, with no free trial because there is no paid plan to trial. There are no seat charges or published quotas to weigh against the free offering. That makes it accessible for individual projects and developer use; users seeking paid support or a commercial service tier will need another product. Help, bug reports, and contact go through GitHub Issues.

Platforms

iWantHue is available on the web and supports Android, iOS, Linux, macOS, and Windows. Its API and JavaScript package add options for developers who want to generate palettes in software rather than only through the web interface.

Who it's for

Data scientists choosing colors for visualizations are the clearest fit, especially when color separation, hue and lightness constraints, or colorblind options matter. Developers can also benefit from the npm package, seeded output, and multiple export formats. People who only need a quick decorative palette may find the controls more involved than their task requires.

Pros and cons

• Pros: Hue, chroma, and lightness controls plus multiple sorting options let users refine palettes for specific visualization needs.
• Pros: Multiple color formats, CSS output, JavaScript settings, and seeded generation support a direct path from palette design to implementation.
• Pros: Colorblind improvement options and precomputed alternatives make accessibility part of palette selection.
• Cons: Very large palettes can contain similar colors when the selected color space runs out of room.
• Cons: The Fancy preset tops out at 10 colors because of its narrow chroma and lightness ranges.
• Cons: Support is routed through GitHub Issues, which may not suit users who expect a dedicated support channel.

Alternatives

For access to a large color library and search, picking, and measuring tools, consider Pantone Connect Palette Generator, which offers a free account-based plan and a trial. Choose Coolors for its free plan or Pro option at $3 a month when billed monthly. Lift Color Palette Generator is a paid option at $14.99 a month initially, then $29.99 a month on autorenewal. Other free options include Colordot, ColorKit, ColorPalette Pro, and the Linux-focused Gpick. If unlimited generations, every export format, shareable links, and API access are the priority, Color Palette Generator AI offers those features for free without requiring an account. Browse more choices in Color Palette Generators.

Verdict

Choose iWantHue if you need to tune colors for data visualization and want reproducible palettes with developer-ready exports. Its control over color distribution is the main reason to pick it; the possibility of similar colors in large palettes is the main reason to look elsewhere when every category needs a clearly distinct color.