Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science.
It is freely available under the BSD-3-Clause terms.
Colour is an affiliated project of NumFOCUS, a 501(c)(3) nonprofit in the United States.
Table of Contents
- 1 Draft Release Notes
- 2 Sponsors
- 3 Features
- 3.1 Automatic Colour Conversion Graph -
colour.graph - 3.2 Chromatic Adaptation -
colour.adaptation - 3.3 Algebra -
colour.algebra - 3.4 Colour Appearance Models -
colour.appearance - 3.5 Colour Blindness -
colour.blindness - 3.6 Colour Correction -
colour characterisation - 3.7 ACES Input Transform -
colour characterisation - 3.8 Colorimetry -
colour.colorimetry - 3.9 Contrast Sensitivity Function -
colour.contrast - 3.10 Colour Difference -
colour.difference - 3.11 IO -
colour.io - 3.12 Colour Models -
colour.models - 3.13 Colour Notation Systems -
colour.notation - 3.14 Optical Phenomena -
colour.phenomena - 3.15 Light Quality -
colour.quality - 3.16 Spectral Up-Sampling & Recovery -
colour.recovery - 3.17 Correlated Colour Temperature Computation Methods -
colour.temperature - 3.18 Colour Volume -
colour.volume - 3.19 Geometry Primitives Generation -
colour.geometry - 3.20 Plotting -
colour.plotting
- 3.1 Automatic Colour Conversion Graph -
- 4 User Guide
- 5 API Reference
- 6 See Also
- 7 Code of Conduct
- 8 Contact & Social
- 9 Thank You!
- 10 About
The draft release notes of the develop branch are available at this url.
We are grateful 💖 for the support of our sponsors. If you'd like to join them, please consider becoming a sponsor on OpenCollective.
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Most of the objects are available from the colour namespace:
import colour
sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"]
colour.convert(sd, "Spectral Distribution", "sRGB", verbose={"mode": "Short"})===============================================================================
* *
* [ Conversion Path ] *
* *
* "sd_to_XYZ" --> "XYZ_to_sRGB" *
* *
===============================================================================
array([ 0.49034776, 0.30185875, 0.23587685])
illuminant = colour.SDS_ILLUMINANTS["FL2"]
colour.convert(
sd,
"Spectral Distribution",
"sRGB",
sd_to_XYZ={"illuminant": illuminant},
)array([ 0.47924575, 0.31676968, 0.17362725])
XYZ = [0.20654008, 0.12197225, 0.05136952]
D65 = colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["D65"]
A = colour.CCS_ILLUMINANTS["CIE 1931 2 Degree Standard Observer"]["A"]
colour.chromatic_adaptation(XYZ, colour.xy_to_XYZ(D65), colour.xy_to_XYZ(A))array([ 0.25331034, 0.13765286, 0.01543185])
sorted(colour.CHROMATIC_ADAPTATION_METHODS)['CIE 1994', 'CMCCAT2000', 'Fairchild 1990', 'Von Kries', 'Zhai 2018', 'vK20']
y = [5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500]
x = range(len(y))
colour.KernelInterpolator(x, y)([0.25, 0.75, 5.50])array([ 6.18062083, 8.08238488, 57.85783403])
y = [5.9200, 9.3700, 10.8135, 4.5100, 69.5900, 27.8007, 86.0500]
x = range(len(y))
colour.SpragueInterpolator(x, y)([0.25, 0.75, 5.50])array([ 6.72951612, 7.81406251, 43.77379185])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
XYZ_w = [95.05, 100.00, 108.88]
L_A = 318.31
Y_b = 20.0
colour.XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b)CAM_Specification_CIECAM02(J=34.434525727858997, C=67.365010921125915, h=22.279164147957076, s=62.814855853327131, Q=177.47124941102123, M=70.024939419291385, H=2.689608534423904, HC=None)
colour.XYZ_to_CIECAM16(XYZ, XYZ_w, L_A, Y_b)CAM_Specification_CIECAM16(J=33.880368498111686, C=69.444353357408033, h=19.510887327451748, s=64.03612114840314, Q=176.03752758512178, M=72.18638534116765, H=399.52975599115319, HC=None)
colour.XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b)CAM_Specification_CAM16(J=33.880368498111686, C=69.444353357408033, h=19.510887327451748, s=64.03612114840314, Q=176.03752758512178, M=72.18638534116765, H=399.52975599115319, HC=None)
colour.XYZ_to_Hellwig2022(XYZ, XYZ_w, L_A, Y_b)CAM_Specification_Hellwig2022(J=33.880368498111686, C=37.579419116276348, h=19.510887327451748, s=109.33343382561695, Q=45.34489577734751, M=49.577131618021212, H=399.52975599115319, HC=None, J_HK=39.41741758094139, Q_HK=52.755585941150315)
colour.XYZ_to_Kim2009(XYZ, XYZ_w, L_A)CAM_Specification_Kim2009(J=19.879918542450937, C=55.83905525087696, h=22.013388165090031, s=112.9797935493912, Q=36.309026130161513, M=46.346415858227871, H=2.3543198369639753, HC=None)
colour.XYZ_to_ZCAM(XYZ, XYZ_w, L_A, Y_b)CAM_Specification_ZCAM(J=38.347186278956357, C=21.121389892085183, h=33.711578931095183, s=81.444585609489536, Q=76.986725284523772, M=42.403805833900513, H=0.45779200212217158, HC=None, V=43.623590687423551, K=43.20894953152817, W=34.829588380192149)
import numpy as np
cmfs = colour.colorimetry.MSDS_CMFS_LMS["Stockman & Sharpe 2 Degree Cone Fundamentals"]
colour.msds_cmfs_anomalous_trichromacy_Machado2009(cmfs, np.array([15, 0, 0]))[450]array([ 0.08912884, 0.0870524 , 0.955393 ])
primaries = colour.MSDS_DISPLAY_PRIMARIES["Apple Studio Display"]
d_LMS = (15, 0, 0)
colour.matrix_anomalous_trichromacy_Machado2009(cmfs, primaries, d_LMS)array([[-0.27774652, 2.65150084, -1.37375432],
[ 0.27189369, 0.20047862, 0.52762768],
[ 0.00644047, 0.25921579, 0.73434374]])
import numpy as np
RGB = [0.17224810, 0.09170660, 0.06416938]
M_T = np.random.random((24, 3))
M_R = M_T + (np.random.random((24, 3)) - 0.5) * 0.5
colour.colour_correction(RGB, M_T, M_R)array([ 0.18147565, 0.08609354, 0.08569274])
sorted(colour.COLOUR_CORRECTION_METHODS)['Cheung 2004', 'Finlayson 2015', 'Vandermonde']
sensitivities = colour.MSDS_CAMERA_SENSITIVITIES["Nikon 5100 (NPL)"]
illuminant = colour.SDS_ILLUMINANTS["D55"]
colour.matrix_idt(sensitivities, illuminant)(array([[ 0.59368175, 0.30418371, 0.10213454],
[ 0.00457979, 1.14946003, -0.15403982],
[ 0.03552213, -0.16312291, 1.12760077]]), array([ 1.58214188, 1. , 1.28910346]))
colour.sd_to_XYZ(colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"])array([ 36.94726204, 32.62076174, 13.0143849 ])
sorted(colour.SPECTRAL_TO_XYZ_METHODS)['ASTM E308', 'Integration', 'astm2015']
msds = np.array(
[
[
[
0.01367208,
0.09127947,
0.01524376,
0.02810712,
0.19176012,
0.04299992,
],
[
0.00959792,
0.25822842,
0.41388571,
0.22275120,
0.00407416,
0.37439537,
],
[
0.01791409,
0.29707789,
0.56295109,
0.23752193,
0.00236515,
0.58190280,
],
],
[
[
0.01492332,
0.10421912,
0.02240025,
0.03735409,
0.57663846,
0.32416266,
],
[
0.04180972,
0.26402685,
0.03572137,
0.00413520,
0.41808194,
0.24696727,
],
[
0.00628672,
0.11454948,
0.02198825,
0.39906919,
0.63640803,
0.01139849,
],
],
[
[
0.04325933,
0.26825359,
0.23732357,
0.05175860,
0.01181048,
0.08233768,
],
[
0.02484169,
0.12027161,
0.00541695,
0.00654612,
0.18603799,
0.36247808,
],
[
0.03102159,
0.16815442,
0.37186235,
0.08610666,
0.00413520,
0.78492409,
],
],
[
[
0.11682307,
0.78883040,
0.74468607,
0.83375293,
0.90571451,
0.70054168,
],
[
0.06321812,
0.41898224,
0.15190357,
0.24591440,
0.55301750,
0.00657664,
],
[
0.00305180,
0.11288624,
0.11357290,
0.12924391,
0.00195315,
0.21771573,
],
],
]
)
colour.msds_to_XYZ(
msds,
method="Integration",
shape=colour.SpectralShape(400, 700, 60),
)array([[[ 7.68544647, 4.09414317, 8.49324254],
[ 17.12567298, 27.77681821, 25.52573685],
[ 19.10280411, 34.45851476, 29.76319628]],
[[ 18.03375827, 8.62340812, 9.71702574],
[ 15.03110867, 6.54001068, 24.53208465],
[ 37.68269495, 26.4411103 , 10.66361816]],
[[ 8.09532373, 12.75333339, 25.79613956],
[ 7.09620297, 2.79257389, 11.15039854],
[ 8.933163 , 19.39985815, 17.14915636]],
[[ 80.00969553, 80.39810464, 76.08184429],
[ 33.27611427, 24.38947838, 39.34919287],
[ 8.89425686, 11.05185138, 10.86767594]]])
sorted(colour.MSDS_TO_XYZ_METHODS)['ASTM E308', 'Integration', 'astm2015']
colour.sd_blackbody(5000)SpectralDistribution([[ 360. , 6654.27827064],
[ 361. , 6709.60527925],
[ 362. , 6764.82512152],
...
[ 778. , 10606.80038243],
[ 779. , 10590.33272593],
[ 780. , 10573.85196369]],
SpragueInterpolator,
{},
Extrapolator,
{'method': 'Constant', 'left': None, 'right': None})
xy = [0.54369557, 0.32107944]
xy_n = [0.31270000, 0.32900000]
colour.dominant_wavelength(xy, xy_n)(array(616.0),
array([ 0.68354746, 0.31628409]),
array([ 0.68354746, 0.31628409]))
colour.lightness(12.19722535)41.527875844653451
sorted(colour.LIGHTNESS_METHODS)['Abebe 2017',
'CIE 1976',
'Fairchild 2010',
'Fairchild 2011',
'Glasser 1958',
'Lstar1976',
'Wyszecki 1963']
colour.luminance(41.52787585)12.197225353400775
sorted(colour.LUMINANCE_METHODS)['ASTM D1535',
'CIE 1976',
'Fairchild 2010',
'Fairchild 2011',
'Newhall 1943',
'astm2008',
'cie1976']
XYZ = [95.00000000, 100.00000000, 105.00000000]
XYZ_0 = [94.80966767, 100.00000000, 107.30513595]
colour.whiteness(XYZ, XYZ_0)array([ 93.756 , -1.33000001])
sorted(colour.WHITENESS_METHODS)['ASTM E313',
'Berger 1959',
'CIE 2004',
'Ganz 1979',
'Stensby 1968',
'Taube 1960',
'cie2004']
XYZ = [95.00000000, 100.00000000, 105.00000000]
colour.yellowness(XYZ)4.3400000000000034
sorted(colour.YELLOWNESS_METHODS)['ASTM D1925', 'ASTM E313', 'ASTM E313 Alternative']
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_flux(sd)23807.655527367198
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_efficiency(sd)0.19943935624521045
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_efficacy(sd)136.21708031547874
colour.contrast_sensitivity_function(u=4, X_0=60, E=65)358.51180789884984
sorted(colour.CONTRAST_SENSITIVITY_METHODS)['Barten 1999']
Lab_1 = [100.00000000, 21.57210357, 272.22819350]
Lab_2 = [100.00000000, 426.67945353, 72.39590835]
colour.delta_E(Lab_1, Lab_2)94.035649026659485
sorted(colour.DELTA_E_METHODS)['CAM02-LCD',
'CAM02-SCD',
'CAM02-UCS',
'CAM16-LCD',
'CAM16-SCD',
'CAM16-UCS',
'CIE 1976',
'CIE 1994',
'CIE 2000',
'CMC',
'DIN99',
'HyAB',
'HyCH',
'ITP',
'cie1976',
'cie1994',
'cie2000']
RGB = colour.read_image("Ishihara_Colour_Blindness_Test_Plate_3.png")
RGB.shape(276, 281, 3)
components = colour.read_spectral_image_Fichet2021("Polarised.exr")
list(components.keys())['S0', 'S1', 'S2', 'S3']
LUT = colour.read_LUT("ACES_Proxy_10_to_ACES.cube")
print(LUT)LUT3x1D - ACES Proxy 10 to ACES
-------------------------------
Dimensions : 2
Domain : [[0 0 0]
[1 1 1]]
Size : (32, 3)
RGB = [0.17224810, 0.09170660, 0.06416938]
LUT.apply(RGB)array([ 0.00575674, 0.00181493, 0.00121419])
colour.XYZ_to_xyY([0.20654008, 0.12197225, 0.05136952])array([ 0.54369557, 0.32107944, 0.12197225])
colour.XYZ_to_Lab([0.20654008, 0.12197225, 0.05136952])array([ 41.52787529, 52.63858304, 26.92317922])
colour.XYZ_to_Luv([0.20654008, 0.12197225, 0.05136952])array([ 41.52787529, 96.83626054, 17.75210149])
colour.XYZ_to_UCS([0.20654008, 0.12197225, 0.05136952])array([ 0.13769339, 0.12197225, 0.1053731 ])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_UVW(XYZ)array([ 94.55035725, 11.55536523, 40.54757405])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
XYZ_w = [95.05, 100.00, 108.88]
L_A = 318.31
Y_b = 20.0
surround = colour.VIEWING_CONDITIONS_CIECAM02["Average"]
specification = colour.XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b, surround)
JMh = (specification.J, specification.M, specification.h)
colour.JMh_CIECAM02_to_CAM02UCS(JMh)array([ 47.16899898, 38.72623785, 15.8663383 ])
XYZ = [0.20654008, 0.12197225, 0.05136952]
XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100]
colour.XYZ_to_CAM02UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)array([ 47.16899898, 38.72623785, 15.8663383 ])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
XYZ_w = [95.05, 100.00, 108.88]
L_A = 318.31
Y_b = 20.0
surround = colour.VIEWING_CONDITIONS_CAM16["Average"]
specification = colour.XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b, surround)
JMh = (specification.J, specification.M, specification.h)
colour.JMh_CAM16_to_CAM16UCS(JMh)array([ 46.55542238, 40.22460974, 14.25288392])
XYZ = [0.20654008, 0.12197225, 0.05136952]
XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100]
colour.XYZ_to_CAM16UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)array([ 46.55542238, 40.22460974, 14.25288392])
Lab = [41.52787529, 52.63858304, 26.92317922]
colour.Lab_to_DIN99(Lab)array([ 53.22821988, 28.41634656, 3.89839552])
XYZ_to_ICaCb(np.array([0.20654008, 0.12197225, 0.05136952]))array([ 0.06875297, 0.05753352, 0.02081548])
colour.XYZ_to_IgPgTg([0.20654008, 0.12197225, 0.05136952])array([ 0.42421258, 0.18632491, 0.10689223])
colour.XYZ_to_IPT([0.20654008, 0.12197225, 0.05136952])array([ 0.38426191, 0.38487306, 0.18886838])
colour.XYZ_to_Jzazbz([0.20654008, 0.12197225, 0.05136952])array([ 0.00535048, 0.00924302, 0.00526007])
colour.XYZ_to_hdr_CIELab([0.20654008, 0.12197225, 0.05136952])array([ 51.87002062, 60.4763385 , 32.14551912])
colour.XYZ_to_hdr_IPT([0.20654008, 0.12197225, 0.05136952])array([ 25.18261761, -22.62111297, 3.18511729])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_Hunter_Lab(XYZ)array([ 34.92452577, 47.06189858, 14.38615107])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_Hunter_Rdab(XYZ)array([ 12.197225 , 57.12537874, 17.46241341])
colour.XYZ_to_Oklab([0.20654008, 0.12197225, 0.05136952])array([ 0.51634019, 0.154695 , 0.06289579])
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_OSA_UCS(XYZ)array([-3.0049979 , 2.99713697, -9.66784231])
colour.XYZ_to_ProLab([0.51634019, 0.15469500, 0.06289579])array([1.24610688, 2.39525236, 0.41902126])
colour.XYZ_to_IPT_Ragoo2021([0.20654008, 0.12197225, 0.05136952])array([ 0.42248243, 0.2910514 , 0.20410663])
colour.XYZ_to_Yrg([0.20654008, 0.12197225, 0.05136952])array([ 0.13137801, 0.49037645, 0.37777388])
colour.RGB_to_YCbCr([1.0, 1.0, 1.0])array([ 0.92156863, 0.50196078, 0.50196078])
colour.RGB_to_YCoCg([0.75, 0.75, 0.0])array([ 0.5625, 0.375 , 0.1875])
colour.RGB_to_ICtCp([0.45620519, 0.03081071, 0.04091952])array([ 0.07351364, 0.00475253, 0.09351596])
colour.RGB_to_HSV([0.45620519, 0.03081071, 0.04091952])array([ 0.99603944, 0.93246304, 0.45620519])
colour.RGB_to_IHLS([0.45620519, 0.03081071, 0.04091952])array([ 6.26236117, 0.12197943, 0.42539448])
colour.RGB_to_Prismatic([0.25, 0.50, 0.75])array([ 0.75 , 0.16666667, 0.33333333, 0.5 ])
XYZ = [0.21638819, 0.12570000, 0.03847493]
illuminant_XYZ = [0.34570, 0.35850]
illuminant_RGB = [0.31270, 0.32900]
chromatic_adaptation_transform = "Bradford"
matrix_XYZ_to_RGB = [
[3.24062548, -1.53720797, -0.49862860],
[-0.96893071, 1.87575606, 0.04151752],
[0.05571012, -0.20402105, 1.05699594],
]
colour.XYZ_to_RGB(
XYZ,
illuminant_XYZ,
illuminant_RGB,
matrix_XYZ_to_RGB,
chromatic_adaptation_transform,
)array([ 0.45595571, 0.03039702, 0.04087245])
p = [0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700]
w = [0.32168, 0.33767]
colour.normalised_primary_matrix(p, w)array([[ 9.52552396e-01, 0.00000000e+00, 9.36786317e-05],
[ 3.43966450e-01, 7.28166097e-01, -7.21325464e-02],
[ 0.00000000e+00, 0.00000000e+00, 1.00882518e+00]])
sorted(colour.RGB_COLOURSPACES)['ACES2065-1',
'ACEScc',
'ACEScct',
'ACEScg',
'ACESproxy',
'ARRI Wide Gamut 3',
'ARRI Wide Gamut 4',
'Adobe RGB (1998)',
'Adobe Wide Gamut RGB',
'Apple RGB',
'Best RGB',
'Beta RGB',
'Blackmagic Wide Gamut',
'CIE RGB',
'CIE XYZ-D65 - Scene-referred',
'Cinema Gamut',
'ColorMatch RGB',
'DCDM XYZ',
'DCI-P3',
'DCI-P3-P',
'DJI D-Gamut',
'DRAGONcolor',
'DRAGONcolor2',
'DaVinci Wide Gamut',
'Display P3',
'Don RGB 4',
'EBU Tech. 3213-E',
'ECI RGB v2',
'ERIMM RGB',
'Ekta Space PS 5',
'F-Gamut',
'F-Gamut C',
'FilmLight E-Gamut',
'Gamma 1.8 Encoded Rec.709',
'Gamma 2.2 Encoded AP1',
'Gamma 2.2 Encoded AdobeRGB',
'Gamma 2.2 Encoded Rec.709',
'ITU-R BT.2020',
'ITU-R BT.470 - 525',
'ITU-R BT.470 - 625',
'ITU-R BT.709',
'ITU-T H.273 - 22 Unspecified',
'ITU-T H.273 - Generic Film',
'Linear AdobeRGB',
'Linear P3-D65',
'Linear Rec.2020',
'Linear Rec.709 (sRGB)',
'Max RGB',
'N-Gamut',
'NTSC (1953)',
'NTSC (1987)',
'P3-D65',
'PLASA ANSI E1.54',
'Pal/Secam',
'ProPhoto RGB',
'Protune Native',
'REDWideGamutRGB',
'REDcolor',
'REDcolor2',
'REDcolor3',
'REDcolor4',
'RIMM RGB',
'ROMM RGB',
'Russell RGB',
'S-Gamut',
'S-Gamut3',
'S-Gamut3.Cine',
'SMPTE 240M',
'SMPTE C',
'Sharp RGB',
'V-Gamut',
'Venice S-Gamut3',
'Venice S-Gamut3.Cine',
'Xtreme RGB',
'aces',
'adobe1998',
'g18_rec709_scene',
'g22_adobergb_scene',
'g22_ap1_scene',
'g22_rec709_scene',
'lin_adobergb_scene',
'lin_ap0_scene',
'lin_ap1_scene',
'lin_ciexyzd65_scene',
'lin_p3d65_scene',
'lin_rec2020_scene',
'lin_rec709_scene',
'prophoto',
'sRGB',
'sRGB Encoded AP1',
'sRGB Encoded P3-D65',
'sRGB Encoded Rec.709 (sRGB)',
'srgb_ap1_scene',
'srgb_p3d65_scene',
'srgb_rec709_scene']
sorted(colour.OETFS)['ARIB STD-B67',
'Blackmagic Film Generation 5',
'DaVinci Intermediate',
'ITU-R BT.2020',
'ITU-R BT.2100 HLG',
'ITU-R BT.2100 PQ',
'ITU-R BT.601',
'ITU-R BT.709',
'ITU-T H.273 IEC 61966-2',
'ITU-T H.273 Log',
'ITU-T H.273 Log Sqrt',
'SMPTE 240M']
sorted(colour.EOTFS)['DCDM',
'DICOM GSDF',
'ITU-R BT.1886',
'ITU-R BT.2100 HLG',
'ITU-R BT.2100 PQ',
'ITU-T H.273 ST.428-1',
'SMPTE 240M',
'ST 2084',
'sRGB']
sorted(colour.OOTFS)['ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ']
sorted(colour.LOG_ENCODINGS)['ACEScc',
'ACEScct',
'ACESproxy',
'ARRI LogC3',
'ARRI LogC4',
'Apple Log Profile',
'Canon Log',
'Canon Log 2',
'Canon Log 3',
'Cineon',
'D-Log',
'ERIMM RGB',
'F-Log',
'F-Log2',
'Filmic Pro 6',
'L-Log',
'Log2',
'Log3G10',
'Log3G12',
'N-Log',
'PLog',
'Panalog',
'Protune',
'REDLog',
'REDLogFilm',
'S-Log',
'S-Log2',
'S-Log3',
'T-Log',
'V-Log',
'ViperLog']
sorted(colour.CCTF_ENCODINGS)['ACEScc',
'ACEScct',
'ACESproxy',
'ARIB STD-B67',
'ARRI LogC3',
'ARRI LogC4',
'Apple Log Profile',
'Blackmagic Film Generation 5',
'Canon Log',
'Canon Log 2',
'Canon Log 3',
'Cineon',
'D-Log',
'DCDM',
'DICOM GSDF',
'DaVinci Intermediate',
'ERIMM RGB',
'F-Log',
'F-Log2',
'Filmic Pro 6',
'Gamma 2.2',
'Gamma 2.4',
'Gamma 2.6',
'ITU-R BT.1886',
'ITU-R BT.2020',
'ITU-R BT.2100 HLG',
'ITU-R BT.2100 PQ',
'ITU-R BT.601',
'ITU-R BT.709',
'ITU-T H.273 IEC 61966-2',
'ITU-T H.273 Log',
'ITU-T H.273 Log Sqrt',
'ITU-T H.273 ST.428-1',
'L-Log',
'Log2',
'Log3G10',
'Log3G12',
'N-Log',
'PLog',
'Panalog',
'ProPhoto RGB',
'Protune',
'REDLog',
'REDLogFilm',
'RIMM RGB',
'ROMM RGB',
'S-Log',
'S-Log2',
'S-Log3',
'SMPTE 240M',
'ST 2084',
'T-Log',
'V-Log',
'ViperLog',
'sRGB']
colour.COLOUR_PRIMARIES_ITUTH273.keys()dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22, 23])
colour.models.describe_video_signal_colour_primaries(1)===============================================================================
* *
* Colour Primaries: 1 *
* ------------------- *
* *
* Primaries : [[ 0.64 0.33] *
* [ 0.3 0.6 ] *
* [ 0.15 0.06]] *
* Whitepoint : [ 0.3127 0.329 ] *
* Whitepoint Name : D65 *
* NPM : [[ 0.4123908 0.35758434 0.18048079] *
* [ 0.21263901 0.71516868 0.07219232] *
* [ 0.01933082 0.11919478 0.95053215]] *
* NPM -1 : [[ 3.24096994 -1.53738318 -0.49861076] *
* [-0.96924364 1.8759675 0.04155506] *
* [ 0.05563008 -0.20397696 1.05697151]] *
* FFmpeg Constants : ['AVCOL_PRI_BT709', 'BT709'] *
* *
===============================================================================
colour.TRANSFER_CHARACTERISTICS_ITUTH273.keys()dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
colour.models.describe_video_signal_transfer_characteristics(1)===============================================================================
* *
* Transfer Characteristics: 1 *
* --------------------------- *
* *
* Function : <function oetf_BT709 at 0x165bb3550> *
* FFmpeg Constants : ['AVCOL_TRC_BT709', 'BT709'] *
* *
===============================================================================
colour.MATRIX_COEFFICIENTS_ITUTH273.keys()dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
colour.models.describe_video_signal_matrix_coefficients(1)===============================================================================
* *
* Matrix Coefficients: 1 *
* ---------------------- *
* *
* Matrix Coefficients : [ 0.2126 0.0722] *
* FFmpeg Constants : ['AVCOL_SPC_BT709', 'BT709'] *
* *
===============================================================================
colour.munsell_value(12.23634268)4.0824437076525664
sorted(colour.MUNSELL_VALUE_METHODS)['ASTM D1535',
'Ladd 1955',
'McCamy 1987',
'Moon 1943',
'Munsell 1933',
'Priest 1920',
'Saunderson 1944',
'astm2008']
colour.xyY_to_munsell_colour([0.38736945, 0.35751656, 0.59362000])'4.2YR 8.1/5.3'
colour.munsell_colour_to_xyY("4.2YR 8.1/5.3")array([ 0.38736945, 0.35751656, 0.59362 ])
colour.sd_rayleigh_scattering()SpectralDistribution([[ 3.60000000e+02, 5.60246579e-01],
[ 3.61000000e+02, 5.53748137e-01],
[ 3.62000000e+02, 5.47344692e-01],
...
[ 7.78000000e+02, 2.37790178e-02],
[ 7.79000000e+02, 2.36559421e-02],
[ 7.80000000e+02, 2.35336632e-02]],
SpragueInterpolator,
{},
Extrapolator,
{'method': 'Constant', 'left': None, 'right': None})
colour.colour_fidelity_index(colour.SDS_ILLUMINANTS["FL2"])70.120824401428848
sorted(colour.COLOUR_FIDELITY_INDEX_METHODS)['ANSI/IES TM-30-18', 'CIE 2017']
colour.colour_quality_scale(colour.SDS_ILLUMINANTS["FL2"])64.111822015662824
sorted(colour.COLOUR_QUALITY_SCALE_METHODS)['NIST CQS 7.4', 'NIST CQS 9.0']
colour.colour_rendering_index(colour.SDS_ILLUMINANTS["FL2"])64.233724121664793
colour.spectral_similarity_index(
colour.SDS_ILLUMINANTS["C"], colour.SDS_ILLUMINANTS["D65"]
)94.0
colour.XYZ_to_sd([0.20654008, 0.12197225, 0.05136952])SpectralDistribution([[ 3.60000000e+02, 8.52694330e-02],
[ 3.65000000e+02, 8.52203359e-02],
[ 3.70000000e+02, 8.52841304e-02],
...
[ 7.70000000e+02, 4.46546872e-01],
[ 7.75000000e+02, 4.46638451e-01],
[ 7.80000000e+02, 4.46641739e-01]],
SpragueInterpolator,
{},
Extrapolator,
{'method': 'Constant', 'left': None, 'right': None})
sorted(colour.REFLECTANCE_RECOVERY_METHODS)['Jakob 2019', 'Mallett 2019', 'Meng 2015', 'Otsu 2018', 'Smits 1999']
illuminant = colour.colorimetry.SDS_ILLUMINANTS["D65"]
sensitivities = colour.characterisation.MSDS_CAMERA_SENSITIVITIES["Nikon 5100 (NPL)"]
reflectances = [
sd.copy().align(colour.recovery.SPECTRAL_SHAPE_BASIS_FUNCTIONS_DYER2017)
for sd in colour.characterisation.SDS_COLOURCHECKERS["BabelColor Average"].values()
]
reflectances = colour.colorimetry.sds_and_msds_to_msds(reflectances)
RGB = colour.colorimetry.msds_to_XYZ(
reflectances,
method="Integration",
cmfs=sensitivities,
illuminant=illuminant,
k=0.01,
shape=colour.recovery.SPECTRAL_SHAPE_BASIS_FUNCTIONS_DYER2017,
)
colour.recovery.RGB_to_msds_camera_sensitivities_Jiang2013(
RGB,
illuminant,
reflectances,
colour.recovery.BASIS_FUNCTIONS_DYER2017,
colour.recovery.SPECTRAL_SHAPE_BASIS_FUNCTIONS_DYER2017,
)RGB_CameraSensitivities([[ 4.00000000e+02, 7.04378461e-03, 9.21260449e-03,
-7.64080878e-03],
[ 4.10000000e+02, -8.76715607e-03, 1.12726694e-02,
6.37434190e-03],
[ 4.20000000e+02, 4.58126856e-02, 7.18000418e-02,
4.00001696e-01],
...
[ 6.80000000e+02, 4.00195568e-02, 5.55512389e-03,
1.36794925e-03],
[ 6.90000000e+02, -4.32240535e-03, 2.49731193e-03,
3.80303275e-04],
[ 7.00000000e+02, -6.00395414e-03, 1.54678227e-03,
5.40394352e-04]],
['red', 'green', 'blue'],
SpragueInterpolator,
{},
Extrapolator,
{'method': 'Constant', 'left': None, 'right': None})
colour.uv_to_CCT([0.1978, 0.3122])array([ 6.50747479e+03, 3.22334634e-03])
sorted(colour.UV_TO_CCT_METHODS)['Krystek 1985', 'Ohno 2013', 'Planck 1900', 'Robertson 1968', 'ohno2013', 'robertson1968']
sorted(colour.XY_TO_CCT_METHODS)['CIE Illuminant D Series',
'Hernandez 1999',
'Kang 2002',
'McCamy 1992',
'daylight',
'hernandez1999',
'kang2002',
'mccamy1992']
colour.RGB_colourspace_volume_MonteCarlo(colour.RGB_COLOURSPACE_RGB["sRGB"])821958.30000000005
colour.primitive("Grid")(array([ ([-0.5, 0.5, 0. ], [ 0., 1.], [ 0., 0., 1.], [ 0., 1., 0., 1.]),
([ 0.5, 0.5, 0. ], [ 1., 1.], [ 0., 0., 1.], [ 1., 1., 0., 1.]),
([-0.5, -0.5, 0. ], [ 0., 0.], [ 0., 0., 1.], [ 0., 0., 0., 1.]),
([ 0.5, -0.5, 0. ], [ 1., 0.], [ 0., 0., 1.], [ 1., 0., 0., 1.])],
dtype=[('position', '<f4', (3,)), ('uv', '<f4', (2,)), ('normal', '<f4', (3,)), ('colour', '<f4', (4,))]), array([[0, 2, 1],
[2, 3, 1]], dtype=uint32), array([[0, 2],
[2, 3],
[3, 1],
[1, 0]], dtype=uint32))
sorted(colour.PRIMITIVE_METHODS)['Cube', 'Grid']
colour.primitive_vertices("Quad MPL")array([[ 0., 0., 0.],
[ 1., 0., 0.],
[ 1., 1., 0.],
[ 0., 1., 0.]])
sorted(colour.PRIMITIVE_VERTICES_METHODS)
['Cube MPL', 'Grid MPL', 'Quad MPL', 'Sphere']
Most of the objects are available from the colour.plotting namespace:
from colour.plotting import *
colour_style()plot_visible_spectrum("CIE 1931 2 Degree Standard Observer")
plot_single_illuminant_sd("FL1")
blackbody_sds = [
colour.sd_blackbody(i, colour.SpectralShape(1, 10001, 10))
for i in range(1000, 15000, 1000)
]
plot_multi_sds(
blackbody_sds,
y_label="W / (sr m$^2$) / m",
plot_kwargs={"use_sd_colours": True, "normalise_sd_colours": True},
legend_location="upper right",
bounding_box=(0, 1250, 0, 2.5e6),
)
plot_single_cmfs(
"Stockman & Sharpe 2 Degree Cone Fundamentals",
y_label="Sensitivity",
bounding_box=(390, 870, 0, 1.1),
)
sd_mesopic_luminous_efficiency_function = (
colour.sd_mesopic_luminous_efficiency_function(0.2)
)
plot_multi_sds(
(
sd_mesopic_luminous_efficiency_function,
colour.colorimetry.SDS_LEFS_PHOTOPIC["CIE 1924 Photopic Standard Observer"],
colour.colorimetry.SDS_LEFS_SCOTOPIC["CIE 1951 Scotopic Standard Observer"],
),
y_label="Luminous Efficiency",
legend_location="upper right",
y_tighten=True,
margins=(0, 0, 0, 0.1),
)
from colour.characterisation.dataset.colour_checkers.sds import (
COLOURCHECKER_INDEXES_TO_NAMES_MAPPING,
)
plot_multi_sds(
[
colour.SDS_COLOURCHECKERS["BabelColor Average"][value]
for key, value in sorted(COLOURCHECKER_INDEXES_TO_NAMES_MAPPING.items())
],
plot_kwargs={
"use_sd_colours": True,
},
title=("BabelColor Average - " "Spectral Distributions"),
)
plot_single_colour_checker("ColorChecker 2005", text_kwargs={"visible": False})
plot_corresponding_chromaticities_prediction(2, "Von Kries", "Bianco 2010")
import numpy as np
RGB = np.random.random((32, 32, 3))
plot_RGB_chromaticities_in_chromaticity_diagram_CIE1931(
RGB,
"ITU-R BT.709",
colourspaces=["ACEScg", "S-Gamut", "Pointer Gamut"],
)
plot_single_sd_colour_rendering_index_bars(colour.SDS_ILLUMINANTS["FL2"])
plot_single_sd_colour_rendition_report(colour.SDS_ILLUMINANTS["FL2"])
plot_visible_spectrum_section(section_colours="RGB", section_opacity=0.15)
plot_RGB_colourspace_section("sRGB", section_colours="RGB", section_opacity=0.15)
plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(["A", "B", "C"])
Colour and its primary dependencies can be easily installed from the Python Package Index by issuing this command in a shell:
$ pip install --user colour-scienceThe detailed installation procedure for the secondary dependencies is described in the Installation Guide.
Colour is also available for Anaconda from Continuum Analytics via conda-forge:
$ conda install -c conda-forge colour-scienceThe static tutorial provides an introduction to Colour. An interactive version is available via Google Colab.
The Google Colab How-To guide for Colour shows various techniques to solve specific problems and highlights some interesting use cases.
If you would like to contribute to Colour, please refer to the following Contributing guide.
The changes are viewable on the Releases page.
The bibliography is available on the Bibliography page.
It is also viewable directly from the repository in BibTeX format.
The main technical reference for Colour is the API Reference:
Python
- ColorAide by Muse, I.
- ColorPy by Kness, M.
- Colorspacious by Smith, N. J., et al.
- python-colormath by Taylor, G., et al.
Go
- go-colorful by Beyer, L., et al.
.NET
- Colourful by Pažourek, T., et al.
Julia
- Colors.jl by Holy, T., et al.
Matlab & Octave
- COLORLAB by Malo, J., et al.
- Psychtoolbox by Brainard, D., et al.
- The Munsell and Kubelka-Munk Toolbox by Centore, P.
The Code of Conduct, adapted from the Contributor Covenant 1.4, is available on the Code of Conduct page.
The Colour Developers can be reached via different means:
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Colour by Colour Developers
Copyright 2013 Colour Developers – colour-developers@colour-science.org
This software is released under terms of BSD-3-Clause: https://opensource.org/licenses/BSD-3-Clause
