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
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" *
* *
===============================================================================
[ 0.49034776 0.30185875 0.23587685]
import colour
sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"]
illuminant = colour.SDS_ILLUMINANTS["FL2"]
colour.convert(
sd,
"Spectral Distribution",
"sRGB",
sd_to_XYZ={"illuminant": illuminant},
)[ 0.47924575 0.31676968 0.17362725]
import colour
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))[ 0.25331034 0.13765286 0.01543185]
import colour
sorted(colour.CHROMATIC_ADAPTATION_METHODS)['CIE 1994', 'CMCCAT2000', 'Fairchild 1990', 'Li 2025', 'Von Kries', 'Zhai 2018', 'vK20']
import colour
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])[ 6.18062083 8.08238488 57.85783403]
import colour
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])[ 6.72951612 7.81406251 43.77379185]
import colour
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)
import colour
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_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)
import colour
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_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)
import colour
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_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)
import colour
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_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)
import colour
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_sCAM(XYZ, XYZ_w, L_A, Y_b)CAM_Specification_sCAM(J=42.550992142462782, C=40.419439198593302, h=20.904455433026421, Q=175.74578999778015, M=14.325369984981474, H=7.1106008503613021, HC=None, V=81.92545469934403, K=18.07454530065597, W=0.023675944970833029, D=99.976324055029167)
import colour
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_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 colour
cmfs = colour.colorimetry.MSDS_CMFS_LMS["Stockman & Sharpe 2 Degree Cone Fundamentals"]
colour.msds_cmfs_anomalous_trichromacy_Machado2009(cmfs, [15, 0, 0])[450][ 0.08912884 0.0870524 0.955393 ]
import colour
cmfs = colour.colorimetry.MSDS_CMFS_LMS["Stockman & Sharpe 2 Degree Cone Fundamentals"]
primaries = colour.MSDS_DISPLAY_PRIMARIES["Apple Studio Display"]
d_LMS = (15, 0, 0)
colour.matrix_anomalous_trichromacy_Machado2009(cmfs, primaries, d_LMS)[[-0.27774652 2.65150084 -1.37375432]
[ 0.27189369 0.20047862 0.52762768]
[ 0.00644047 0.25921579 0.73434374]]
import colour
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)[ 0.17960686 0.08935744 0.06766639] # (results will vary due to random inputs)
import colour
sorted(colour.COLOUR_CORRECTION_METHODS)['Cheung 2004', 'Finlayson 2015', 'Vandermonde']
import colour
sensitivities = colour.MSDS_CAMERA_SENSITIVITIES["Nikon 5100 (NPL)"]
illuminant = colour.SDS_ILLUMINANTS["D55"]
colour.matrix_idt(sensitivities, illuminant)(array([[ 0.59368175, 0.30418373, 0.10213451],
[ 0.0045798 , 1.14946005, -0.15403985],
[ 0.03552214, -0.16312291, 1.12760078]]), array([ 1.58214188, 1. , 1.28910346]))
import colour
colour.sd_to_XYZ(colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"])[ 36.94726204 32.62076174 13.0143849 ]
import colour
sorted(colour.SD_TO_XYZ_METHODS)['ASTM E308', 'Integration', 'astm2015']
import colour
msds = [
[
[
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),
)[[[ 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]]]
import colour
sorted(colour.MSDS_TO_XYZ_METHODS)['ASTM E308', 'Integration', 'astm2015']
import colour
colour.sd_blackbody(5000)[[ 360. 6654.27827064]
[ 361. 6709.60527925]
[ 362. 6764.82512152]
...
[ 780. 10573.85196369]]
import colour
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]))
import colour
colour.lightness(12.19722535)41.5278758447
import colour
sorted(colour.LIGHTNESS_METHODS)['Abebe 2017', 'CIE 1976', 'Fairchild 2010', 'Fairchild 2011', 'Glasser 1958', 'Lstar1976', 'Wyszecki 1963']
import colour
colour.luminance(41.52787585)12.1972253534
import colour
sorted(colour.LUMINANCE_METHODS)['ASTM D1535', 'Abebe 2017', 'CIE 1976', 'Fairchild 2010', 'Fairchild 2011', 'Newhall 1943', 'astm2008', 'cie1976']
import colour
XYZ = [95.00000000, 100.00000000, 105.00000000]
XYZ_0 = [94.80966767, 100.00000000, 107.30513595]
colour.whiteness(XYZ, XYZ_0)[ 93.756 -1.33000001]
import colour
sorted(colour.WHITENESS_METHODS)['ASTM E313', 'Berger 1959', 'CIE 2004', 'Ganz 1979', 'Stensby 1968', 'Taube 1960', 'cie2004']
import colour
XYZ = [95.00000000, 100.00000000, 105.00000000]
colour.yellowness(XYZ)4.34
import colour
sorted(colour.YELLOWNESS_METHODS)['ASTM D1925', 'ASTM E313', 'ASTM E313 Alternative']
import colour
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_flux(sd)23807.6555274
import colour
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_efficiency(sd)0.199439356245
import colour
sd = colour.SDS_LIGHT_SOURCES["Neodimium Incandescent"]
colour.luminous_efficacy(sd)136.217080315
import colour
colour.contrast_sensitivity_function(u=4, X_0=60, E=65)358.511807899
import colour
sorted(colour.CONTRAST_SENSITIVITY_METHODS)['Barten 1999']
import colour
Lab_1 = [100.00000000, 21.57210357, 272.22819350]
Lab_2 = [100.00000000, 426.67945353, 72.39590835]
colour.delta_E(Lab_1, Lab_2)94.0356490267
import colour
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']
import colour
RGB = colour.read_image("Ishihara_Colour_Blindness_Test_Plate_3.png")
RGB.shape(276, 281, 3)
import colour
components = colour.read_spectral_image_Fichet2021("Polarised.exr")
list(components.keys())['S0', 'S1', 'S2', 'S3']
import colour
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)
import colour
RGB = [0.17224810, 0.09170660, 0.06416938]
LUT.apply(RGB)[ 0.00575674, 0.00181493, 0.00121419]
import colour
colour.XYZ_to_xyY([0.20654008, 0.12197225, 0.05136952])[ 0.54369557 0.32107944 0.12197225]
import colour
colour.XYZ_to_Lab([0.20654008, 0.12197225, 0.05136952])[ 41.52787529 52.63858304 26.92317922]
import colour
colour.XYZ_to_Luv([0.20654008, 0.12197225, 0.05136952])[ 41.52787529 96.83626054 17.75210149]
import colour
colour.XYZ_to_UCS([0.20654008, 0.12197225, 0.05136952])[ 0.13769339 0.12197225 0.1053731 ]
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_UVW(XYZ)[ 94.55035725 11.55536523 40.54757405]
import colour
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)[ 47.16899898 38.72623785 15.8663383 ]
import colour
XYZ = [0.20654008, 0.12197225, 0.05136952]
XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100]
L_A = 318.31
Y_b = 20.0
colour.XYZ_to_CAM02UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)[ 47.16899898 38.72623785 15.8663383 ]
import colour
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)[ 46.55542238 40.22460974 14.25288392]
import colour
XYZ = [0.20654008, 0.12197225, 0.05136952]
XYZ_w = [95.05 / 100, 100.00 / 100, 108.88 / 100]
L_A = 318.31
Y_b = 20.0
colour.XYZ_to_CAM16UCS(XYZ, XYZ_w=XYZ_w, L_A=L_A, Y_b=Y_b)[ 46.55542238 40.22460974 14.25288392]
import colour
Lab = [41.52787529, 52.63858304, 26.92317922]
colour.Lab_to_DIN99(Lab)[ 53.22821988 28.41634656 3.89839552]
import colour
colour.XYZ_to_ICaCb([0.20654008, 0.12197225, 0.05136952])[ 0.06875297 0.05753352 0.02081548]
import colour
colour.XYZ_to_IgPgTg([0.20654008, 0.12197225, 0.05136952])[ 0.42421258 0.18632491 0.10689223]
import colour
colour.XYZ_to_IPT([0.20654008, 0.12197225, 0.05136952])[ 0.38426191 0.38487306 0.18886838]
import colour
colour.XYZ_to_Jzazbz([0.20654008, 0.12197225, 0.05136952])[ 0.00535048 0.00924302 0.00526007]
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_Hunter_Lab(XYZ)[ 34.92452577 47.06189858 14.38615107]
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_Hunter_Rdab(XYZ)[ 12.197225 57.12537874 17.46241341]
import colour
colour.XYZ_to_Oklab([0.20654008, 0.12197225, 0.05136952])[ 0.51634019 0.154695 0.06289579]
import colour
XYZ = [0.20654008 * 100, 0.12197225 * 100, 0.05136952 * 100]
colour.XYZ_to_OSA_UCS(XYZ)[-3.0049979 2.99713697 -9.66784231]
import colour
colour.XYZ_to_ProLab([0.51634019, 0.15469500, 0.06289579])[ 59.8466286 115.0396354 20.12510352]
import colour
colour.XYZ_to_IPT_Ragoo2021([0.20654008, 0.12197225, 0.05136952])[ 0.42248243 0.2910514 0.20410663]
import colour
colour.XYZ_to_Yrg([0.20654008, 0.12197225, 0.05136952])[ 0.13137801 0.49037645 0.37777388]
import colour
colour.XYZ_to_hdr_CIELab([0.20654008, 0.12197225, 0.05136952])[ 51.87002062 60.4763385 32.14551912]
import colour
colour.XYZ_to_hdr_IPT([0.20654008, 0.12197225, 0.05136952])[ 25.18261761 -22.62111297 3.18511729]
import colour
colour.RGB_to_YCbCr([1.0, 1.0, 1.0])[ 0.92156863 0.50196078 0.50196078]
import colour
colour.RGB_to_YCoCg([0.75, 0.75, 0.0])[ 0.5625 0.375 0.1875]
import colour
colour.RGB_to_ICtCp([0.45620519, 0.03081071, 0.04091952])[ 0.07351364 0.00475253 0.09351596]
import colour
colour.RGB_to_HSV([0.45620519, 0.03081071, 0.04091952])[ 0.99603944 0.93246304 0.45620519]
import colour
colour.RGB_to_IHLS([0.45620519, 0.03081071, 0.04091952])[ 6.26236117 0.12197943 0.42539448]
import colour
colour.RGB_to_Prismatic([0.25, 0.50, 0.75])[ 0.75 0.16666667 0.33333333 0.5 ]
import colour
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,
)[ 0.45595571 0.03039702 0.04087245]
import colour
p = [0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700]
w = [0.32168, 0.33767]
colour.normalised_primary_matrix(p, w)[[ 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]]
import colour
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', 'FilmLight E-Gamut 2', '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']
import colour
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']
import colour
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']
import colour
sorted(colour.OOTFS)['ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ']
import colour
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']
import colour
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']
import colour
colour.COLOUR_PRIMARIES_ITUTH273.keys()dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 22, 23])
import colour
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'] *
* *
===============================================================================
import colour
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])
import colour
colour.models.describe_video_signal_transfer_characteristics(1)===============================================================================
* *
* Transfer Characteristics: 1 *
* --------------------------- *
* *
* Function : <function oetf_BT709 at 0x7f7b918776a0> *
* FFmpeg Constants : ['AVCOL_TRC_BT709', 'BT709'] *
* *
===============================================================================
import colour
colour.MATRIX_COEFFICIENTS_ITUTH273.keys()dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
import colour
colour.models.describe_video_signal_matrix_coefficients(1)===============================================================================
* *
* Matrix Coefficients: 1 *
* ---------------------- *
* *
* Matrix Coefficients : [ 0.2126 0.0722] *
* FFmpeg Constants : ['AVCOL_SPC_BT709', 'BT709'] *
* *
===============================================================================
import colour
colour.munsell_value(12.23634268)4.08244370765
import colour
sorted(colour.MUNSELL_VALUE_METHODS)['ASTM D1535', 'Ladd 1955', 'McCamy 1987', 'Moon 1943', 'Munsell 1933', 'Priest 1920', 'Saunderson 1944', 'astm2008']
import colour
colour.xyY_to_munsell_colour([0.38736945, 0.35751656, 0.59362000])4.2YR 8.1/5.3
import colour
colour.munsell_colour_to_xyY("4.2YR 8.1/5.3")[ 0.38736945 0.35751656 0.59362 ]
import colour
colour.sd_rayleigh_scattering()[[ 3.60000000e+02 5.60246579e-01]
[ 3.61000000e+02 5.53748137e-01]
[ 3.62000000e+02 5.47344692e-01]
...
[ 7.80000000e+02 2.35336632e-02]]
import colour
colour.colour_fidelity_index(colour.SDS_ILLUMINANTS["FL2"])70.1208244014
import colour
sorted(colour.COLOUR_FIDELITY_INDEX_METHODS)['ANSI/IES TM-30-18', 'CIE 2017']
import colour
colour.colour_quality_scale(colour.SDS_ILLUMINANTS["FL2"])64.1118220157
import colour
sorted(colour.COLOUR_QUALITY_SCALE_METHODS)['NIST CQS 7.4', 'NIST CQS 9.0']
import colour
colour.colour_rendering_index(colour.SDS_ILLUMINANTS["FL2"])64.2337241217
import colour
sorted(colour.COLOUR_RENDERING_INDEX_METHODS)['CIE 1995', 'CIE 2024']
import colour
colour.spectral_similarity_index(
colour.SDS_ILLUMINANTS["C"], colour.SDS_ILLUMINANTS["D65"]
)94.0
import colour
colour.XYZ_to_sd([0.20654008, 0.12197225, 0.05136952])[[ 3.60000000e+02 8.42398617e-02]
[ 3.65000000e+02 8.42355431e-02]
[ 3.70000000e+02 8.42689564e-02]
...
[ 7.80000000e+02 4.46952477e-01]]
import colour
sorted(colour.XYZ_TO_SD_METHODS)['Jakob 2019', 'Mallett 2019', 'Meng 2015', 'Otsu 2018', 'Smits 1999']
import colour
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.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})
import colour
colour.uv_to_CCT([0.1978, 0.3122])[ 6.50747479e+03 3.22334634e-03]
import colour
sorted(colour.UV_TO_CCT_METHODS)['Krystek 1985', 'Ohno 2013', 'Planck 1900', 'Robertson 1968', 'ohno2013', 'robertson1968']
import colour
sorted(colour.XY_TO_CCT_METHODS)['CIE Illuminant D Series', 'Hernandez 1999', 'Kang 2002', 'McCamy 1992', 'daylight', 'hernandez1999', 'kang2002', 'mccamy1992']
import colour
colour.RGB_colourspace_volume_MonteCarlo(colour.RGB_COLOURSPACE_RGB["sRGB"])821958.30000000005
import colour
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', '<f8', (3,)), ('uv', '<f8', (2,)), ('normal', '<f8', (3,)), ('colour', '<f8', (4,))]), array([[0, 2, 1],
[2, 3, 1]]), array([[0, 2],
[2, 3],
[3, 1],
[1, 0]]))
import colour
sorted(colour.PRIMITIVE_METHODS)['Cube', 'Grid']
import colour
colour.primitive_vertices("Quad MPL")[[ 0. 0. 0.]
[ 1. 0. 0.]
[ 1. 1. 0.]
[ 0. 1. 0.]]
Most of the objects are available from the colour.plotting namespace:
from colour.plotting import *
colour_style()from colour.plotting import *
plot_visible_spectrum("CIE 1931 2 Degree Standard Observer")(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'The Visible Spectrum - CIE 1931 2$^\\circ$ Standard Observer'}, xlabel='Wavelength $\\lambda$ (nm)'>)
from colour.plotting import *
plot_single_illuminant_sd("FL1")(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'Illuminant FL1 - CIE 1931 2$^\\circ$ Standard Observer'}, xlabel='Wavelength $\\lambda$ (nm)', ylabel='Relative Power'>)
import colour
from colour.plotting import *
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),
)(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='Wavelength $lambda$ (nm)', ylabel='W / (sr m$^2$) / m'>)
from colour.plotting import *
plot_single_cmfs(
"Stockman & Sharpe 2 Degree Cone Fundamentals",
y_label="Sensitivity",
bounding_box=(390, 870, 0, 1.1),
)(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'Stockman & Sharpe 2$^circ$ Cone Fundamentals - Colour Matching Functions'}, xlabel='Wavelength $lambda$ (nm)', ylabel='Sensitivity'>)
import colour
from colour.plotting import *
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),
)(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='Wavelength $lambda$ (nm)', ylabel='Luminous Efficiency'>)
import colour
from colour.plotting import *
plot_multi_sds(
list(colour.SDS_COLOURCHECKERS["BabelColor Average"].values()),
plot_kwargs={
"use_sd_colours": True,
},
title=("BabelColor Average - " "Spectral Distributions"),
)(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'BabelColor Average - Spectral Distributions'}, xlabel='Wavelength $lambda$ (nm)', ylabel='Spectral Distribution'>)
from colour.plotting import *
plot_single_colour_checker("ColorChecker 2005", text_kwargs={"visible": False})(<Figure size 640x480 with 1 Axes>, <Axes: title={'center': 'ColorChecker 2005'}>)
from colour.plotting import *
plot_corresponding_chromaticities_prediction(
2, "Von Kries", {"transform": "Bianco 2010"}
)(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'Corresponding Chromaticities Prediction - Von Kries - Experiment 2 - CIE 1976 UCS Chromaticity Diagram'}, xlabel="CIE u'", ylabel="CIE v'">)
import numpy as np
from colour.plotting import *
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"],
)(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'ACEScg, S-Gamut, ITU-R BT.709\nCIE 1931 2 Degree Standard Observer - CIE 1931 Chromaticity Diagram'}, xlabel='CIE x',
ylabel='CIE y'>
import colour
from colour.plotting import *
plot_single_sd_colour_rendering_index_bars(colour.SDS_ILLUMINANTS["FL2"])(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'Colour Rendering Index - FL2'}>)
import colour
from colour.plotting import *
plot_single_sd_colour_rendition_report(colour.SDS_ILLUMINANTS["FL2"])(<Figure size 827x1169 with 13 Axes>, <Axes: >)
from colour.plotting import *
plot_visible_spectrum_section(section_colours="RGB", section_opacity=0.15)(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'Visible Spectrum Section - 50.0% - CIE xyY - CIE 1931 2$^\\circ$ Standard Observer'}, xlabel='x', ylabel='y'>)
from colour.plotting import *
plot_RGB_colourspace_section("sRGB", section_colours="RGB", section_opacity=0.15)(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'sRGB Section - 50.0% - CIE xyY'}, xlabel='x', ylabel='y'>)
from colour.plotting import *
plot_planckian_locus_in_chromaticity_diagram_CIE1960UCS(["A", "B", "C"])(<Figure size 640x640 with 1 Axes>, <Axes: title={'center': 'A, B, C Illuminants - Planckian Locus\nCIE 1960 UCS Chromaticity Diagram - CIE 1931 2 Degree Standard Observer'}, xlabel='CIE u', ylabel='CIE v'>)
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 – [email protected]
This software is released under terms of BSD-3-Clause: https://opensource.org/licenses/BSD-3-Clause