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Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.

It is open source and freely available under the New BSD License terms.

Features

Colour features a rich dataset and collection of objects, please see the features page for more information.

Installation

Anaconda from Continuum Analytics is the Python distribution we use to develop Colour: it ships all the scientific dependencies we require and is easily deployed cross-platform:

$ conda create -y -n python-colour
$ source activate python-colour
$ conda install -y -c conda-forge colour-science

Colour can be easily installed from the Python Package Index by issuing this command in a shell:

$ pip install colour-science

The detailed installation procedure is described in the Installation Guide.

Usage

The two main references for Colour usage are the Colour Manual and the Jupyter Notebooks with detailed historical and theoretical context and images:

Examples

Chromatic Adaptation

>>> import colour
>>> XYZ = [0.07049534, 0.10080000, 0.09558313]
>>> A = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['A']
>>> D65 = colour.ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']
>>> colour.chromatic_adaptation(
...     XYZ, colour.xy_to_XYZ(A), colour.xy_to_XYZ(D65))
array([ 0.08398225,  0.11413379,  0.28629643])
>>> sorted(colour.CHROMATIC_ADAPTATION_METHODS.keys())
['CIE 1994', 'CMCCAT2000', 'Fairchild 1990', 'Von Kries']

Algebra

>>> 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])
array([  6.18062083,   8.08238488,  57.85783403])
>>> colour.SpragueInterpolator(x, y)([0.25, 0.75, 5.50])
array([  6.72951612,   7.81406251,  43.77379185])

Spectral Computations

>>> import colour
>>> colour.spectral_to_XYZ(colour.LIGHT_SOURCES_RELATIVE_SPDS['Neodimium Incandescent'])
array([ 36.94726204,  32.62076174,  13.0143849 ])
>>> sorted(colour.SPECTRAL_TO_XYZ_METHODS.keys())
[u'ASTM E308-15', u'Integration', u'astm2015']

Blackbody Spectral Radiance Computation

>>> import colour
>>> colour.blackbody_spd(5000)
SpectralPowerDistribution([[  3.60000000e+02,   6.65427827e+12],
                           [  3.61000000e+02,   6.70960528e+12],
                           [  3.62000000e+02,   6.76482512e+12],
                           ...
                           [  7.78000000e+02,   1.06068004e+13],
                           [  7.79000000e+02,   1.05903327e+13],
                           [  7.80000000e+02,   1.05738520e+13]],
                          interpolator=SpragueInterpolator,
                          interpolator_args={},
                          extrapolator=Extrapolator,
                          extrapolator_args={u'right': None, u'method': u'Constant', u'left': None})

Dominant, Complementary Wavelength & Colour Purity Computation

>>> import colour
>>> xy = [0.26415, 0.37770]
>>> xy_n = [0.31270, 0.32900]
>>> colour.dominant_wavelength(xy, xy_n)
(array(504.0),
 array([ 0.00369694,  0.63895775]),
 array([ 0.00369694,  0.63895775]))

Lightness Computation

>>> import colour
>>> colour.lightness(10.08)
24.902290269546651
>>> sorted(colour.LIGHTNESS_METHODS.keys())
[u'CIE 1976',
 u'Fairchild 2010',
 u'Glasser 1958',
 u'Lstar1976',
 u'Wyszecki 1963']

Luminance Computation

>>> import colour
>>> colour.luminance(37.98562910)
10.080000001314646
>>> sorted(colour.LUMINANCE_METHODS.keys())
[u'ASTM D1535-08',
 u'CIE 1976',
 u'Fairchild 2010',
 u'Newhall 1943',
 u'astm2008',
 u'cie1976']

Whiteness Computation

>>> import colour
>>> colour.whiteness(xy=[0.3167, 0.3334], Y=100, xy_n=[0.3139, 0.3311])
array([ 93.85 ,  -1.305])
>>> sorted(colour.WHITENESS_METHODS.keys())
[u'ASTM E313',
 u'Berger 1959',
 u'CIE 2004',
 u'Ganz 1979',
 u'Stensby 1968',
 u'Taube 1960',
 u'cie2004']

Yellowness Computation

>>> import colour
>>> XYZ = [95.00000000, 100.00000000, 105.00000000]
>>> colour.yellowness(XYZ)
11.065000000000003
>>> sorted(colour.YELLOWNESS_METHODS.keys())
[u'ASTM D1925', u'ASTM E313']

Luminous Flux, Efficiency & Efficacy Computation

>>> import colour
>>> spd = colour.LIGHT_SOURCES_RELATIVE_SPDS['Neodimium Incandescent']
>>> colour.luminous_flux(spd)
3807.655527367202
>>> colour.luminous_efficiency(spd)
0.19943935624521045
>>> colour.luminous_efficiency(spd)
136.21708031547874

Colour Models

>>> import colour
>>> XYZ = [0.07049534, 0.10080000, 0.09558313]
>>> colour.XYZ_to_Lab(XYZ)
array([ 37.9856291 , -23.62907688,  -4.41746615])
>>> colour.XYZ_to_Luv(XYZ)
array([ 37.9856291 , -28.80219593,  -1.35800706])
>>> colour.XYZ_to_UCS(XYZ)
array([ 0.04699689,  0.1008    ,  0.1637439 ])
>>> colour.XYZ_to_UVW(XYZ)
array([ 4.0680797 ,  0.12787175, -5.36516614])
>>> colour.XYZ_to_xyY(XYZ)
array([ 0.26414772,  0.37770001,  0.1008    ])
>>> colour.XYZ_to_hdr_CIELab(XYZ)
array([ 24.90206646, -46.83127607, -10.14274843])
>>> colour.XYZ_to_hdr_IPT(XYZ)
array([ 25.18261761, -22.62111297,   3.18511729])
>>> colour.XYZ_to_Hunter_Lab([7.049534, 10.080000, 9.558313])
array([ 31.74901573, -15.11462629,  -2.78660758])
>>> colour.XYZ_to_Hunter_Rdab([7.049534, 10.080000, 9.558313])
array([ 10.08      , -18.67653764,  -3.44329925])
>>> colour.XYZ_to_IPT(XYZ)
array([ 0.36571124, -0.11114798,  0.01594746])

>>> XYZ = np.array([19.01, 20.00, 21.78])
>>> XYZ_w = np.array([95.05, 100.00, 108.88])
>>> L_A = 318.31
>>> Y_b = 20.0
>>> surround = colour.CIECAM02_VIEWING_CONDITIONS['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([ 54.90433134,  -0.08442362,  -0.06848314])
>>> 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([ 54.89102616,  -9.42910274,  -5.52845976])

>>> XYZ = [0.07049534, 0.10080000, 0.09558313]
>>> illuminant_XYZ = [0.34570, 0.35850]
>>> illuminant_RGB = [0.31270, 0.32900]
>>> chromatic_adaptation_transform = 'Bradford'
>>> XYZ_to_RGB_matrix = [
         [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,
         XYZ_to_RGB_matrix,
         chromatic_adaptation_transform)
array([ 0.01100154,  0.12735048,  0.11632713])

>>> colour.RGB_to_ICTCP([0.35181454, 0.26934757, 0.21288023])
array([ 0.09554079, -0.00890639,  0.01389286])

>>> colour.RGB_to_HSV([0.49019608, 0.98039216, 0.25098039])
array([ 0.27867383,  0.744     ,  0.98039216])

>>> 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]])

>>> colour.RGB_to_Prismatic([0.25, 0.50, 0.75])
array([ 0.75      ,  0.16666667,  0.33333333,  0.5       ])

>>> colour.RGB_to_YCbCr([1.0, 1.0, 1.0])
array([ 0.92156863,  0.50196078,  0.50196078])

RGB Colourspaces

>>> import colour
>>> sorted(colour.RGB_COLOURSPACES.keys())
[u'ACES2065-1',
 u'ACEScc',
 u'ACEScct',
 u'ACEScg',
 u'ACESproxy',
 u'ALEXA Wide Gamut',
 u'Adobe RGB (1998)',
 u'Adobe Wide Gamut RGB',
 u'Apple RGB',
 u'Best RGB',
 u'Beta RGB',
 u'CIE RGB',
 u'Cinema Gamut',
 u'ColorMatch RGB',
 u'DCI-P3',
 u'DCI-P3+',
 u'DRAGONcolor',
 u'DRAGONcolor2',
 u'Don RGB 4',
 u'ECI RGB v2',
 u'ERIMM RGB',
 u'Ekta Space PS 5',
 u'ITU-R BT.2020',
 u'ITU-R BT.470 - 525',
 u'ITU-R BT.470 - 625',
 u'ITU-R BT.709',
 u'Max RGB',
 u'NTSC',
 u'Pal/Secam',
 u'ProPhoto RGB',
 u'Protune Native',
 u'REDWideGamutRGB',
 u'REDcolor',
 u'REDcolor2',
 u'REDcolor3',
 u'REDcolor4',
 u'RIMM RGB',
 u'ROMM RGB',
 u'Russell RGB',
 u'S-Gamut',
 u'S-Gamut3',
 u'S-Gamut3.Cine',
 u'SMPTE 240M',
 u'V-Gamut',
 u'Xtreme RGB',
 'aces',
 'adobe1998',
 'prophoto',
 u'sRGB']

OETFs

>>> import colour
>>> sorted(colour.OETFS.keys())
['ARIB STD-B67',
 'DCI-P3',
 'DICOM GSDF',
 'ITU-R BT.2020',
 'ITU-R BT.2100 HLG',
 'ITU-R BT.2100 PQ',
 'ITU-R BT.601',
 'ITU-R BT.709',
 'ProPhoto RGB',
 'RIMM RGB',
 'ROMM RGB',
 'SMPTE 240M',
 'ST 2084',
 'sRGB']

EOTFs

>>> import colour
>>> sorted(colour.EOTFS.keys())
['DCI-P3',
 'DICOM GSDF',
 'ITU-R BT.1886',
 'ITU-R BT.2020',
 'ITU-R BT.2100 HLG',
 'ITU-R BT.2100 PQ',
 'ProPhoto RGB',
 'RIMM RGB',
 'ROMM RGB',
 'SMPTE 240M',
 'ST 2084']

OOTFs

>>> import colour
>>> sorted(colour.OOTFS.keys())
['ITU-R BT.2100 HLG', 'ITU-R BT.2100 PQ']

Log Encoding / Decoding Curves

>>> import colour
>>> sorted(colour.LOG_ENCODING_CURVES.keys())
['ACEScc',
 'ACEScct',
 'ACESproxy',
 'ALEXA Log C',
 'Canon Log',
 'Canon Log 2',
 'Canon Log 3',
 'Cineon',
 'ERIMM RGB',
 'Log3G10',
 'Log3G12',
 'PLog',
 'Panalog',
 'Protune',
 'REDLog',
 'REDLogFilm',
 'S-Log',
 'S-Log2',
 'S-Log3',
 'V-Log',
 'ViperLog']

Chromatic Adaptation Models

>>> import colour
>>> XYZ = [0.07049534, 0.10080000, 0.09558313]
>>> XYZ_w = [1.09846607, 1.00000000, 0.35582280]
>>> XYZ_wr = [0.95042855, 1.00000000, 1.08890037]
>>> colour.chromatic_adaptation_VonKries(XYZ, XYZ_w, XYZ_wr)
array([ 0.08397461,  0.11413219,  0.28625545])

Colour Appearance Models

>>> import colour
>>> XYZ = [19.01, 20.00, 21.78]
>>> 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)
CIECAM02_Specification(J=41.731091132513917, C=0.10470775717103062, h=219.04843265831178, s=2.3603053739196032, Q=195.37132596607671, M=0.10884217566914849, H=278.06073585667758, HC=None)

Colour Difference

>>> 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)
94.035649026659485
>>> sorted(colour.DELTA_E_METHODS.keys())
['CAM02-LCD',
 'CAM02-SCD',
 'CAM02-UCS',
 'CAM16-LCD',
 'CAM16-SCD',
 'CAM16-UCS',
 'CIE 1976',
 'CIE 1994',
 'CIE 2000',
 'CMC',
 'cie1976',
 'cie1994',
 'cie2000']

Colour Notation Systems

>>> import colour
>>> colour.munsell_value(10.1488096782)
3.7462971142584354
>>> sorted(colour.MUNSELL_VALUE_METHODS.keys())
[u'ASTM D1535-08',
 u'Ladd 1955',
 u'McCamy 1987',
 u'Moon 1943',
 u'Munsell 1933',
 u'Priest 1920',
 u'Saunderson 1944',
 u'astm2008']
>>> colour.xyY_to_munsell_colour([0.38736945, 0.35751656, 0.59362000])
u'4.2YR 8.1/5.3'
>>> colour.munsell_colour_to_xyY('4.2YR 8.1/5.3')
array([ 0.38736945,  0.35751656,  0.59362   ])

Optical Phenomena

>>> import colour
>>> colour.rayleigh_scattering_spd()
SpectralPowerDistribution([[  3.60000000e+02,   5.99101337e-01],
                           [  3.61000000e+02,   5.92170690e-01],
                           [  3.62000000e+02,   5.85341006e-01],
                           ...
                           [  7.78000000e+02,   2.55208377e-02],
                           [  7.79000000e+02,   2.53887969e-02],
                           [  7.80000000e+02,   2.52576106e-02]],
                          interpolator=SpragueInterpolator,
                          interpolator_args={},
                          extrapolator=Extrapolator,
                          extrapolator_args={u'right': None, u'method': u'Constant', u'left': None})

Light Quality

>>> import colour
>>> colour.colour_quality_scale(colour.ILLUMINANTS_RELATIVE_SPDS['F2'])
64.686416902221609
>>> colour.colour_rendering_index(colour.ILLUMINANTS_RELATIVE_SPDS['F2'])
64.151520202968015

Reflectance Recovery

>>> import colour
>>> colour.XYZ_to_spectral([0.07049534, 0.10080000, 0.09558313])
SpectralPowerDistribution([[  3.60000000e+02,   7.96361498e-04],
                           [  3.65000000e+02,   7.96489667e-04],
                           [  3.70000000e+02,   7.96543669e-04],
                           ...
                           [  8.20000000e+02,   1.71014294e-04],
                           [  8.25000000e+02,   1.71621924e-04],
                           [  8.30000000e+02,   1.72026883e-04]],
                          interpolator=SpragueInterpolator,
                          interpolator_args={},
                          extrapolator=Extrapolator,
                          extrapolator_args={u'right': None, u'method': u'Constant', u'left': None})
>>> sorted(colour.REFLECTANCE_RECOVERY_METHODS.keys())
['Meng 2015', 'Smits 1999']

Correlated Colour Temperature Computation Methods

>>> import colour
>>> colour.uv_to_CCT([0.1978, 0.3122])
array([  6.50751282e+03,   3.22335875e-03])
>>> sorted(colour.UV_TO_CCT_METHODS.keys())
[u'Ohno 2013', u'Robertson 1968', u'ohno2013', u'robertson1968']
>>> sorted(colour.UV_TO_CCT_METHODS.keys())
[u'Krystek 1985',
 u'Ohno 2013',
 u'Robertson 1968',
 u'ohno2013',
 u'robertson1968']
 >>> sorted(colour.XY_TO_CCT_METHODS.keys())
 [u'Hernandez 1999', u'McCamy 1992', u'hernandez1999', u'mccamy1992']
 >>> sorted(colour.CCT_TO_XY_METHODS.keys())
 [u'CIE Illuminant D Series', u'Kang 2002', su'cie_d', u'kang2002']

Volume

>>> import colour
>>> colour.RGB_colourspace_volume_MonteCarlo(colour.sRGB_COLOURSPACE)
857011.5

Contributing

If you would like to contribute to Colour, please refer to the following Contributing guide.

Changes

The changes are viewable on the Releases page.

Bibliography

The bibliography is available on the Bibliography page.

It is also viewable directly from the repository in BibTeX format.

See Also

Here is a list of notable colour science packages sorted by languages:

Python

.NET

Julia

Matlab & Octave

About

Colour by Colour Developers - 2013-2018
Copyright © 2013-2018 – Colour Developers – colour-science@googlegroups.com
This software is released under terms of New BSD License: http://opensource.org/licenses/BSD-3-Clause
http://github.com/colour-science/colour

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.4.7)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for KelSolaar from gravatar.com KelSolaar

Credits

Author: Colour Developers

License

OSI Approved (New BSD License - http://opensource.org/licenses/BSD-3-Clause)

Classifiers

Report project as malware

Metadata

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.4.7)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for KelSolaar from gravatar.com KelSolaar

Credits

Author: Colour Developers

License

OSI Approved (New BSD License - http://opensource.org/licenses/BSD-3-Clause)

Classifiers

Report project as malware

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