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The support in LibWeb is quite easy as the previous commits introduced helpers to support lab-like colors. Now for the methods in Color: - The formulas in `from_lab()` are derived from the CIEXYZ to CIELAB formulas the "Colorimetry" paper published by the CIE. - The conversion in `from_xyz50()` can be decomposed in multiple steps XYZ D50 -> XYZ D65 -> Linear sRGB -> sRGB. The two first conversion are done with a singular matrix operation. This matrix was generated with a Python script [1]. This commit makes us pass all the `css/css-color/lab-00*.html` WPT tests (0 to 7 at the time of writing). [1] Python script used to generate the XYZ D50 -> Linear sRGB conversion: ```python import numpy as np # http://www.brucelindbloom.com/index.html?Eqn_ChromAdapt.html # First let's convert from D50 to D65 using the Bradford method. m_a = np.array([ [0.8951000, 0.2664000, -0.1614000], [-0.7502000, 1.7135000, 0.0367000], [0.0389000, -0.0685000, 1.0296000] ]) # D50 chromaticities_source = np.array([0.96422, 1, 0.82521]) # D65 chromaticities_destination = np.array([0.9505, 1, 1.0890]) cone_response_source = m_a @ chromaticities_source cone_response_destination = m_a @ chromaticities_destination cone_response_ratio = cone_response_destination / cone_response_source m = np.linalg.inv(m_a) @ np.diagflat(cone_response_ratio) @ m_a D50_to_D65 = m # https://en.wikipedia.org/wiki/SRGB#From_CIE_XYZ_to_sRGB # Then, the matrix to convert to linear sRGB. xyz_65_to_srgb = np.array([ [3.2406, - 1.5372, - 0.4986], [-0.9689, + 1.8758, 0.0415], [0.0557, - 0.2040, 1.0570] ]) # Finally, let's retrieve the final transformation. xyz_50_to_srgb = xyz_65_to_srgb @ D50_to_D65 print(xyz_50_to_srgb) ``` |
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.. | ||
ComponentValue.cpp | ||
ComponentValue.h | ||
Dimension.h | ||
GradientParsing.cpp | ||
Helpers.cpp | ||
MediaParsing.cpp | ||
Parser.cpp | ||
Parser.h | ||
ParsingContext.cpp | ||
ParsingContext.h | ||
SelectorParsing.cpp | ||
Token.cpp | ||
Token.h | ||
Tokenizer.cpp | ||
Tokenizer.h | ||
TokenStream.h | ||
Types.cpp | ||
Types.h |