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Update treatment of convert2lab in slic

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It still defaults to `True` but only when the last dimension of the
input array could be construed as RGB.

Also, update ValueError description in docstring.
This commit is contained in:
Juan Nunez-Iglesias
2015-01-16 13:11:25 +11:00
parent c102a0bf0e
commit 879a7b0bb5
2 changed files with 32 additions and 16 deletions
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skimage/segmentation/slic_superpixels.py
+10 -9
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@@ -12,7 +12,7 @@ from skimage.color import rgb2lab
def slic(image, n_segments=100, compactness=10., max_iter=10, sigma=0,
spacing=None, multichannel=True, convert2lab=True,
spacing=None, multichannel=True, convert2lab=None,
enforce_connectivity=False, min_size_factor=0.5, max_size_factor=3,
slic_zero=False):
"""Segments image using k-means clustering in Color-(x,y,z) space.
@@ -47,8 +47,9 @@ def slic(image, n_segments=100, compactness=10., max_iter=10, sigma=0,
channels or another spatial dimension.
convert2lab : bool, optional
Whether the input should be converted to Lab colorspace prior to
segmentation. For this purpose, the input is assumed to be RGB. Highly
recommended.
segmentation. The input image *must* be RGB. Highly recommended.
This option defaults to ``True`` when ``multichannel=True`` *and*
``image.shape[-1] == 3``.
enforce_connectivity: bool, optional (default False)
Whether the generated segments are connected or not
min_size_factor: float, optional
@@ -68,9 +69,8 @@ def slic(image, n_segments=100, compactness=10., max_iter=10, sigma=0,
Raises
------
ValueError
If:
- the image dimension is not 2 or 3 and `multichannel == False`, OR
- the image dimension is not 3 or 4 and `multichannel == True`
If ``convert2lab`` is set to ``True`` but the last array
dimension is not of length 3.
Notes
-----
@@ -141,10 +141,11 @@ def slic(image, n_segments=100, compactness=10., max_iter=10, sigma=0,
sigma = list(sigma) + [0]
image = ndimage.gaussian_filter(image, sigma)
if convert2lab and multichannel:
if image.shape[3] != 3:
if multichannel and (convert2lab or convert2lab is None):
if image.shape[-1] != 3 and convert2lab:
raise ValueError("Lab colorspace conversion requires a RGB image.")
image = rgb2lab(image)
elif image.shape[-1] == 3:
image = rgb2lab(image)
depth, height, width = image.shape[:3]