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NTSC palette), and compute the matrix of pairwise perceptual differences between these colours, using CIE2000 delta values.
46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
import colormath.color_objects
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import colormath.color_diff
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import colormath.color_conversions
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import numpy as np
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from colours import DHGRColours
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def rgb(r, g, b):
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return colormath.color_objects.sRGBColor(r, g, b, is_upscaled=True)
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# Palette RGB values taken from BMP2DHGR's default NTSC palette
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# TODO: support other palettes as well, e.g. //gs RGB
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palette = {
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DHGRColours.BLACK: rgb(0, 0, 0),
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DHGRColours.MAGENTA: rgb(148, 12, 125),
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DHGRColours.BROWN: rgb(99, 77, 0),
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DHGRColours.ORANGE: rgb(249, 86, 29),
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DHGRColours.DARK_GREEN: rgb(51, 111, 0),
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DHGRColours.GREY1: rgb(126, 126, 126),
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DHGRColours.GREEN: rgb(67, 200, 0),
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DHGRColours.YELLOW: rgb(221, 206, 23),
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DHGRColours.DARK_BLUE: rgb(32, 54, 212),
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DHGRColours.VIOLET: rgb(188, 55, 255),
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DHGRColours.GREY2: rgb(126, 126, 126),
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DHGRColours.PINK: rgb(255, 129, 236),
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DHGRColours.MED_BLUE: rgb(7, 168, 225),
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DHGRColours.LIGHT_BLUE: rgb(158, 172, 255),
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DHGRColours.AQUA: rgb(93, 248, 133),
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DHGRColours.WHITE: rgb(255, 255, 255)
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}
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# Compute matrix of CIE2000 delta values for this palette, representing
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# perceptual distance between colours.
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diff_matrix = np.ndarray(shape=(16, 16), dtype=np.int)
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for colour1, a in palette.items():
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alab = colormath.color_conversions.convert_color(
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a, colormath.color_objects.LabColor)
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for colour2, b in palette.items():
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blab = colormath.color_conversions.convert_color(
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b, colormath.color_objects.LabColor)
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diff_matrix[colour1.value, colour2.value] = int(
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colormath.color_diff.delta_e_cie2000(alab, blab))
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