Add a function to convert from any color space directly to any other space.

scikits/image/color/colorconv.py

@@ -43,8 +43,8 @@ References
 
 from __future__ import division
 
-__all__ = ['rgb2hsv', 'hsv2rgb', 'rgb2xyz', 'xyz2rgb', 'rgb2rgbcie',
-           'rgbcie2rgb']
+__all__ = ['convert_colorspace', 'rgb2hsv', 'hsv2rgb', 'rgb2xyz', 'xyz2rgb',
+           'rgb2rgbcie', 'rgbcie2rgb']
 
 __docformat__ = "restructuredtext en"
 
@@ -52,6 +52,56 @@ import numpy as np
 from scipy import linalg
 
 
+def convert_colorspace(arr, fromspace, tospace):
+    """Convert an image array to a new color space.
+
+    Parameters
+    ----------
+    arr : ndarray
+        The image to convert.
+    fromspace : str
+        The color space to convert from. Valid color space strings are
+        ['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower
+        case.
+    tospace : str
+        The color space to convert to. Valid color space strings are
+        ['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower
+        case.
+
+    Returns
+    -------
+    newarr : ndarray
+        The converted image.
+
+    Notes
+    -----
+    Conversion occurs through the "central" RGB color space, i.e. conversion
+    from XYZ to HSV is implemented as XYZ -> RGB -> HSV instead of directly.
+
+    Examples
+    --------
+    >>> import os
+    >>> from scikits.image import data_dir
+    >>> from scikits.image.io import imread
+
+    >>> lena = imread(os.path.join(data_dir, 'lena.png'))
+    >>> lena_hsv = convert_colorspace(lena, 'RGB', 'HSV')
+    """
+    fromdict = {'RGB':lambda im: im, 'HSV':hsv2rgb, 'RGB CIE':rgbcie2rgb,
+                'XYZ':xyz2rgb}
+    todict = {'RGB':lambda im:im, 'HSV':rgb2hsv, 'RGB CIE':rgb2rgbcie,
+              'XYZ':rgb2xyz}
+
+    fromspace = fromspace.upper()
+    tospace = tospace.upper()
+    if not fromspace in fromdict.keys():
+        raise ValueError, 'fromspace needs to be one of %s'%fromdict.keys()
+    if not tospace in todict.keys():
+        raise ValueError, 'tospace needs to be one of %s'%todict.keys()
+
+    return todict[tospace](fromdict[fromspace](arr))
+
+
 def _prepare_colorarray(arr, dtype="float32"):
     """Check the shape of the array, and give it the requested type"""
     if type(arr) != np.ndarray:

scikits/image/color/tests/test_colorconv.py

@@ -20,7 +20,8 @@ from scikits.image.io import imread
 from scikits.image.color import (
     rgb2hsv, hsv2rgb,
     rgb2xyz, xyz2rgb,
-    rgb2rgbcie, rgbcie2rgb
+    rgb2rgbcie, rgbcie2rgb,
+    convert_colorspace
     )
 
 from scikits.image import data_dir
@@ -130,6 +131,25 @@ class TestColorconv(TestCase):
         assert_almost_equal(rgbcie2rgb(rgb2rgbcie(self.colbars_array)),
                             self.colbars_array)
 
+    def test_convert_colorspace(self):
+        colspaces = ['HSV', 'RGB CIE', 'XYZ']
+        colfuncs_from = [hsv2rgb, rgbcie2rgb, xyz2rgb]
+        colfuncs_to = [rgb2hsv, rgb2rgbcie, rgb2xyz]
+
+        assert_almost_equal(convert_colorspace(self.colbars_array, 'RGB',
+                                               'RGB'), self.colbars_array)
+        for i, space in enumerate(colspaces):
+            gt = colfuncs_from[i](self.colbars_array)
+            assert_almost_equal(convert_colorspace(self.colbars_array, space,
+                                                  'RGB'), gt)
+            gt = colfuncs_to[i](self.colbars_array)
+            assert_almost_equal(convert_colorspace(self.colbars_array, 'RGB',
+                                                   space), gt)
+
+        self.assertRaises(ValueError, convert_colorspace, self.colbars_array,
+                                                           'nokey', 'XYZ')
+        self.assertRaises(ValueError, convert_colorspace, self.colbars_array,
+                                                           'RGB', 'nokey')
 
 if __name__ == "__main__":
     run_module_suite()