colour.RGB_to_XYZ#

colour.RGB_to_XYZ(RGB: ArrayLike, colourspace: RGB_Colourspace | LiteralRGBColourspace | str, illuminant: ArrayLike | None = None, chromatic_adaptation_transform: LiteralChromaticAdaptationTransform | str | None = 'CAT02', apply_cctf_decoding: bool = False, *args: Any, **kwargs: Any) → NDArrayFloat[source]#

Convert given RGB colourspace array to CIE XYZ tristimulus values.

Parameters:

RGB (ArrayLike) – RGB colourspace array.
colourspace (RGB_Colourspace | LiteralRGBColourspace | str) – Input RGB colourspace.
illuminant (ArrayLike | None) – CIE xy chromaticity coordinates or CIE xyY colourspace array of the illuminant for the output CIE XYZ tristimulus values.
chromatic_adaptation_transform (LiteralChromaticAdaptationTransform | str | None) – Chromatic adaptation transform, if None no chromatic adaptation is performed.
apply_cctf_decoding (bool) – Apply the RGB colourspace decoding colour component transfer function / opto-electronic transfer function.
args (Any) – Arguments for deprecation management.
kwargs (Any) – Keywords arguments for deprecation management.

Returns:

CIE XYZ tristimulus values.

Return type:

numpy.ndarray

Notes

Domain	Scale - Reference	Scale - 1
`RGB`	[0, 1]	[0, 1]
`illuminant_XYZ`	[0, 1]	[0, 1]
`illuminant_RGB`	[0, 1]	[0, 1]

Range	Scale - Reference	Scale - 1
`XYZ`	[0, 1]	[0, 1]

Examples

>>> from colour.models import RGB_COLOURSPACE_sRGB
>>> RGB = np.array([0.45595571, 0.03039702, 0.04087245])
>>> illuminant = np.array([0.34570, 0.35850])
>>> RGB_to_XYZ(RGB, RGB_COLOURSPACE_sRGB, illuminant, "Bradford")
... 
array([ 0.2163881...,  0.1257    ,  0.0384749...])
>>> RGB_to_XYZ(RGB, "sRGB", illuminant, "Bradford")
... 
array([ 0.2163881...,  0.1257    ,  0.0384749...])

colour.RGB_to_XYZ#

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