Implement hsv2rgb.

scikits/image/color/colorconv.py

@@ -8,7 +8,7 @@
 
 from __future__ import division
 
-__all__ = ["rgb2hsv"]
+__all__ = ['rgb2hsv', 'hsv2rgb']
 __docformat__ = "restructuredtext en"
 
 import numpy as np
@@ -83,3 +83,61 @@ def rgb2hsv(rgb):
 
     return out
 
+
+def hsv2rgb(hsv):
+    """HSV to RGB color space conversion.
+
+    Parameters
+    ----------
+    hsv : ndarray
+        The image in HSV format, in a 3-D array of shape (.., .., 3).
+
+    Returns
+    -------
+    out : ndarray
+        The image in RGB format, in a 3-D array of shape (.., .., 3).
+
+    Raises
+    ------
+    ValueError
+        If `hsv` is not a 3-D array of shape (.., .., 3).
+
+    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 = rgb2hsv(lena)
+    >>> lena_rgb = hsv2rgb(lena_hsv)
+    """
+
+    if type(hsv) != np.ndarray:
+        raise TypeError, "the input array 'hsv' must be a numpy.ndarray"
+
+    if hsv.ndim != 3 or hsv.shape[2] != 3:
+        msg = "the input array 'hsv' must be have a shape == (.,.,3))"
+        raise ValueError, msg
+
+    arr = hsv.astype("float32")
+
+    hi = np.floor(arr[:,:,0] * 6)
+    f = arr[:,:,0] * 6 - hi
+    p = arr[:,:,2] * (1 - arr[:,:,1])
+    q = arr[:,:,2] * (1 - f * arr[:,:,1])
+    t = arr[:,:,2] * (1 - (1 - f) * arr[:,:,1])
+    v = arr[:,:,2]
+
+    hi = np.dstack([hi, hi, hi]).astype("uint8") % 6
+    out = np.choose(hi, [np.dstack((v, t, p)),
+                         np.dstack((q, v, p)),
+                         np.dstack((p, v, t)),
+                         np.dstack((p, q, v)),
+                         np.dstack((t, p, v)),
+                         np.dstack((v, p, q))])
+
+    # remove NaN
+    out[np.isnan(out)] = 0
+
+    return out

scikits/image/color/tests/test_colorconv.py

@@ -14,17 +14,20 @@ from numpy.testing import *
 from scikits.image.io import imread
 from scikits.image.color import (
     rgb2hsv,
+    hsv2rgb,
     )
 
 from scikits.image import data_dir
 
 import colorsys
 
+
 class TestColorconv(TestCase):
 
     img_rgb = imread(os.path.join(data_dir, 'color.png'))
     img_grayscale = imread(os.path.join(data_dir, 'camera.png'))
 
+    # RGB to HSV
     def test_rgb2hsv_conversion(self):
         rgb = self.img_rgb.astype("float32")[::16, ::16]
         hsv = rgb2hsv(rgb).reshape(-1, 3)
@@ -43,6 +46,27 @@ class TestColorconv(TestCase):
     def test_rgb2hsv_error_list(self):
         self.assertRaises(TypeError, rgb2hsv, [self.img_rgb[0,0]])
 
+
+    # HSV to RGB
+    def test_hsv2rgb_conversion(self):
+        rgb = self.img_rgb.astype("float32")[::16, ::16]
+        # create HSV image with colorsys
+        hsv = np.array([colorsys.rgb_to_hsv(pt[0], pt[1], pt[2])
+                        for pt in rgb.reshape(-1, 3)]).reshape(rgb.shape)
+        # convert back to RGB and compare with original.
+        # float32 -> relative precision about 1e-6
+        assert_almost_equal(rgb, hsv2rgb(hsv), decimal=4)
+
+    def test_hsv2rgb_error_grayscale(self):
+        self.assertRaises(ValueError, hsv2rgb, self.img_grayscale)
+
+    def test_hsv2rgb_error_one_element(self):
+        self.assertRaises(ValueError, hsv2rgb, self.img_rgb[0,0])
+
+    def test_hsv2rgb_error_list(self):
+        self.assertRaises(TypeError, hsv2rgb, [self.img_rgb[0,0]])
+
+
 if __name__ == "__main__":
     run_module_suite()