f8dd17a8f4
Added code which optimises the color matrices based off delta E values for the calibration images. Working in LAB color space. Signed-off-by: Ben Benson <ben.benson@raspberrypi.com> Reviewed-by: David Plowman <david.plowman@raspberrypi.com> Reviewed-by: Naushir Patuck <naush@raspberrypi.com> Signed-off-by: Naushir Patuck <naush@raspberrypi.com>
30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
# colors.py - Program to convert from RGB to LAB color space
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def RGB_to_LAB(RGB): # where RGB is a 1x3 array. e.g RGB = [100, 255, 230]
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num = 0
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XYZ = [0, 0, 0]
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# converted all the three R, G, B to X, Y, Z
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X = RGB[0] * 0.4124 + RGB[1] * 0.3576 + RGB[2] * 0.1805
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Y = RGB[0] * 0.2126 + RGB[1] * 0.7152 + RGB[2] * 0.0722
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Z = RGB[0] * 0.0193 + RGB[1] * 0.1192 + RGB[2] * 0.9505
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XYZ[0] = X / 255 * 100
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XYZ[1] = Y / 255 * 100 # XYZ Must be in range 0 -> 100, so scale down from 255
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XYZ[2] = Z / 255 * 100
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XYZ[0] = XYZ[0] / 95.047 # ref_X = 95.047 Observer= 2°, Illuminant= D65
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XYZ[1] = XYZ[1] / 100.0 # ref_Y = 100.000
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XYZ[2] = XYZ[2] / 108.883 # ref_Z = 108.883
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num = 0
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for value in XYZ:
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if value > 0.008856:
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value = value ** (0.3333333333333333)
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else:
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value = (7.787 * value) + (16 / 116)
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XYZ[num] = value
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num = num + 1
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# L, A, B, values calculated below
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L = (116 * XYZ[1]) - 16
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a = 500 * (XYZ[0] - XYZ[1])
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b = 200 * (XYZ[1] - XYZ[2])
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return [L, a, b]
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