Convert an image RGB->Lab with python

Since 2010 when the linked question was asked the corresponding code moved from scipy to a separate toolkit:http://scikit-image.org/

So here's the code I was actually looking for:

from skimage import io, colorrgb = io.imread(filename)lab = color.rgb2lab(rgb)

It should also be noted that due to Lab nature srgb->lab conversion depends on an additional parameter: whitepoint, eg:
   • Photoshop uses a white point called D50 (which is a standard for icc)
   • OpenCV and skimage use D65 (which is a standard for srgb).
   • default Matlab implementation uses D50 (it is capable of using others),

This nice FAQ explains it this way:

You should use D65 unless you have a good reason to use something else.
The print industry commonly uses D50 and photography commonly uses D55.
These represent compromises between the conditions of indoor (tungsten) and daylight viewing.

You can tell which whitepoint you're dealing with by converting RGB (0,0,255) to Lab:
   • D50 would give you (30, 68, -112)
   • D55                         (30, 73, -110)
   • D65                         (32, 79, -108)

The numbers after 'D' correspond to (internally) used color temperature of white point: D50 = 5003 K (yellowish), D65 = 6504 K (blueish)

I'm grateful to Alex and Roman for their answers because they pointed me into the right direction.

I've found this code on the old Adobe Cookbook site and have adapted for Python. It doesn't require any third-party modules or components:

def rgb2lab ( inputColor ) :   num = 0   RGB = [0, 0, 0]   for value in inputColor :       value = float(value) / 255       if value > 0.04045 :           value = ( ( value + 0.055 ) / 1.055 ) ** 2.4       else :           value = value / 12.92       RGB[num] = value * 100       num = num + 1   XYZ = [0, 0, 0,]   X = RGB [0] * 0.4124 + RGB [1] * 0.3576 + RGB [2] * 0.1805   Y = RGB [0] * 0.2126 + RGB [1] * 0.7152 + RGB [2] * 0.0722   Z = RGB [0] * 0.0193 + RGB [1] * 0.1192 + RGB [2] * 0.9505   XYZ[ 0 ] = round( X, 4 )   XYZ[ 1 ] = round( Y, 4 )   XYZ[ 2 ] = round( Z, 4 )   XYZ[ 0 ] = float( XYZ[ 0 ] ) / 95.047         # ref_X =  95.047   Observer= 2°, Illuminant= D65   XYZ[ 1 ] = float( XYZ[ 1 ] ) / 100.0          # ref_Y = 100.000   XYZ[ 2 ] = float( XYZ[ 2 ] ) / 108.883        # ref_Z = 108.883   num = 0   for value in XYZ :       if value > 0.008856 :           value = value ** ( 0.3333333333333333 )       else :           value = ( 7.787 * value ) + ( 16 / 116 )       XYZ[num] = value       num = num + 1   Lab = [0, 0, 0]   L = ( 116 * XYZ[ 1 ] ) - 16   a = 500 * ( XYZ[ 0 ] - XYZ[ 1 ] )   b = 200 * ( XYZ[ 1 ] - XYZ[ 2 ] )   Lab [ 0 ] = round( L, 4 )   Lab [ 1 ] = round( a, 4 )   Lab [ 2 ] = round( b, 4 )   return Lab

Edit: Sample pyCMS code:

from PIL import Imageimport pyCMSim = Image.open(...)im2 = pyCMS.profileToProfile(im, pyCMS.createProfile("sRGB"), pyCMS.createProfile("LAB"))

Edit: Pillow, the PIL fork, seems to have pyCMS built in.

You might use pyCMS (http://www.cazabon.com/pyCMS/) which works with PIL images.

If speed is not a factor, use python-colormath (http://code.google.com/p/python-colormath/).