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OpenVoiceOS's multilingual color parsing and formatting library

Project description

OVOS Color Parser

Turn natural-language color descriptions into color objects, and color objects back into names, in 23 languages. Pure Python, zero network, no ML model — just bundled wordlists and color math.

from ovos_color_parser import color_from_description

c = color_from_description("dark red", lang="en")
print(c.hex_str)   # "#3B1315"
print(c.as_hls)    # HLSColor(h=357, l=0.153..., s=0.513..., ...)

It ships as part of the OpenVoiceOS voice stack, but it is a standalone library first: nothing here imports OVOS. It is equally useful for NER over free text, describing colors for text-to-speech, and mapping color descriptions to hex for UI theming or LED control.

Installation

pip install ovos-color-parser
# or, with uv:
uv pip install ovos-color-parser

30-second quickstart

from ovos_color_parser import color_from_description, lookup_name, sRGBAColor

# text -> color
c = color_from_description("warm mustard yellow", lang="en")
print(c.hex_str, (c.r, c.g, c.b))     # #FFDA3E (255, 218, 62)

# color -> text (any supported language)
print(lookup_name(sRGBAColor.from_hex_str("#1E90FF"), lang="pt"))  # "Azul furtivo"

# nothing matches -> None
print(color_from_description("qzxwv", lang="en"))  # None

Features

  • Color extractioncolor_from_description("light blue", lang="fr") matches bundled color wordlists (web colors, xkcd survey, crayola, RAL, Pantone, ISCC-NBS, traditional Japanese colors, ...) and object colors ("carrot", "banana"), then applies modifiers such as light/dark, vivid/muted, warm/cool and transparent/opaque. Names are matched on word boundaries and weighted by specificity, so "moss green" outweighs a bare "green" and "green" is never matched inside "evergreen".
  • Color naming and namespaceslookup_name(color, lang) returns a color's name. Every wordlist is an addressable namespace, so you can ask for the name in a specific palette (namespace="RAL_classic") or fall back to the perceptually nearest named color (nearest=True).
  • Color modelssRGBAColor, HLSColor, HSVColor and SpectralColor (wavelength) dataclasses with conversions, stable hex round-trips and validation. SpectralColor.is_visible separates real colors from infrared, ultraviolet and beyond.
  • Gamut handling — choose how a computed color that leaves the sRGB gamut is resolved: clamp per channel, map towards grey while preserving hue, or reject (gamut=GamutPolicy.MAP).
  • Utilities — perceptual color distance (CIEDE2000), linear-light color averaging, Kelvin color temperature to RGB, CMYK conversion, contrasting black/white text color and hex validation.

Use it anywhere

Every snippet below is plain Python — pip install ovos-color-parser and run it. Each has a matching runnable script in examples/.

Extract colors from free text (NER)

Pull color references out of a sentence and resolve each to a structured color — no ML model, no network. Great for tagging product copy, design briefs or support tickets.

from ovos_color_parser import color_from_description

text = "Paint the fence dark forest green and the door navy blue"
for phrase in ("dark forest green", "navy blue"):
    c = color_from_description(phrase, lang="en", fuzzy=False)
    print(phrase, "->", c.hex_str)   # dark forest green -> #162914 ; navy blue -> #0F43BE

Full sliding-window extractor with span offsets: examples/ner_colors.py.

Describe a color out loud (TTS-adjacent)

Go the other way: a raw RGB/hex value from a color picker, sensor or smart bulb becomes a speakable name.

from ovos_color_parser import sRGBAColor, lookup_name

c = sRGBAColor.from_hex_str("#2E8B57")
print(f"The color is {lookup_name(c, lang='en').lower()}.")   # "The color is sea green."

See examples/describe_rgb.py.

Map descriptions to hex for UI, theming and LEDs

from ovos_color_parser import color_from_description

theme = {var: color_from_description(desc, lang="en").hex_str.lower()
         for var, desc in {"--accent": "vivid teal", "--bg": "very dark blue"}.items()}
print(theme)   # {'--accent': '#38bfc4', '--bg': '#121a34'}

CSS variables, NeoPixel/WLED tuples and Kelvin white-balance in examples/ui_theming.py.

In an OVOS skill vs. standalone

The same call powers a voice intent and a plain script — only the surrounding code differs:

# standalone color utility
from ovos_color_parser import color_from_description
hex_str = color_from_description("moss green", lang="en").hex_str

# inside an OVOS skill handler
def handle_set_color(self, message):
    utterance = message.data["utterance"]
    color = color_from_description(utterance, lang=self.lang)
    if color:
        self.set_lamp(color.hex_str)

Supported languages

23 locales: Aragonese, Arabic, Asturian, Basque, Bulgarian, Catalan, Croatian, Czech, Danish, Dutch, English, French, German, Italian, Kabyle, Occitan, Polish, Portuguese, Romanian, Russian, Slovak, Spanish and West Frisian. Any BCP-47 tag resolves to the closest bundled locale (for example en-GBen-US). The per-language feature matrix — entry counts, modifier and object support — is in docs/languages.md.

Documentation

Runnable examples

Usage notes

Color names are ambiguous — the same name can map to several hex values across wordlists. When several entries match, the parser blends them in linear light, weighted by match specificity. To force a known, named color from the matched candidates instead:

color = color_from_description("red", lang="en", cast_to_palette=True)
print(color.name)  # a named wordlist color, e.g. "Dusty Red"

When nothing matches, color_from_description returns None.

Descriptions of impossible colors ("reddish green") still produce an output — the parser blends whatever it matches, which may not be meaningful.

Runnable scripts live in examples/ and the full API reference in docs/api.md.

Related projects

Credits

Color wordlists include data derived from the xkcd color survey, crayola, RAL, Pantone, ISCC-NBS, traditional Japanese colors and Wikipedia color lists. Spectral color terms follow Wikipedia's spectral color tables.

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