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Merge pull request #1033 from jni/label_image

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Add "average segment color" method for `label2rgb`
This commit is contained in:
Stefan van der Walt
2014-06-18 11:49:24 +02:00
parent df7a7eeb6b fdc848b6a7
commit 57b9e67b31
2 changed files with 121 additions and 8 deletions
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skimage/color/colorlabel.py
+88 -8
View File
@@ -64,28 +64,76 @@ def _match_label_with_color(label, colors, bg_label, bg_color):
def label2rgb(label, image=None, colors=None, alpha=0.3,
bg_label=-1, bg_color=None, image_alpha=1):
bg_label=-1, bg_color=None, image_alpha=1, kind='overlay'):
"""Return an RGB image where color-coded labels are painted over the image.
Parameters
----------
label : array
label : array, shape (M, N)
Integer array of labels with the same shape as `image`.
image : array
image : array, shape (M, N, 3), optional
Image used as underlay for labels. If the input is an RGB image, it's
converted to grayscale before coloring.
colors : list
colors : list, optional
List of colors. If the number of labels exceeds the number of colors,
then the colors are cycled.
alpha : float [0, 1]
alpha : float [0, 1], optional
Opacity of colorized labels. Ignored if image is `None`.
bg_label : int
bg_label : int, optional
Label that's treated as the background.
bg_color : str or array
bg_color : str or array, optional
Background color. Must be a name in `color_dict` or RGB float values
between [0, 1].
image_alpha : float [0, 1]
image_alpha : float [0, 1], optional
Opacity of the image.
kind : string, one of {'overlay', 'avg'}
The kind of color image desired. 'overlay' cycles over defined colors
and overlays the colored labels over the original image. 'avg' replaces
each labeled segment with its average color, for a stained-class or
pastel painting appearance.
Returns
-------
result : array of float, shape (M, N, 3)
The result of blending a cycling colormap (`colors`) for each distinct
value in `label` with the image, at a certain alpha value.
"""
if kind == 'overlay':
return _label2rgb_overlay(label, image, colors, alpha, bg_label,
bg_color, image_alpha)
else:
return _label2rgb_avg(label, image, bg_label, bg_color)
def _label2rgb_overlay(label, image=None, colors=None, alpha=0.3,
bg_label=-1, bg_color=None, image_alpha=1):
"""Return an RGB image where color-coded labels are painted over the image.
Parameters
----------
label : array, shape (M, N)
Integer array of labels with the same shape as `image`.
image : array, shape (M, N, 3), optional
Image used as underlay for labels. If the input is an RGB image, it's
converted to grayscale before coloring.
colors : list, optional
List of colors. If the number of labels exceeds the number of colors,
then the colors are cycled.
alpha : float [0, 1], optional
Opacity of colorized labels. Ignored if image is `None`.
bg_label : int, optional
Label that's treated as the background.
bg_color : str or array, optional
Background color. Must be a name in `color_dict` or RGB float values
between [0, 1].
image_alpha : float [0, 1], optional
Opacity of the image.
Returns
-------
result : array of float, shape (M, N, 3)
The result of blending a cycling colormap (`colors`) for each distinct
value in `label` with the image, at a certain alpha value.
"""
if colors is None:
colors = DEFAULT_COLORS
@@ -134,3 +182,35 @@ def label2rgb(label, image=None, colors=None, alpha=0.3,
result[label == bg_label] = image[label == bg_label]
return result
def _label2rgb_avg(label_field, image, bg_label=0, bg_color=(0, 0, 0)):
"""Visualise each segment in `label_field` with its mean color in `image`.
Parameters
----------
label_field : array of int
A segmentation of an image.
image : array, shape ``label_field.shape + (3,)``
A color image of the same spatial shape as `label_field`.
bg_label : int, optional
A value in `label_field` to be treated as background.
bg_color : 3-tuple of int, optional
The color for the background label
Returns
-------
out : array, same shape and type as `image`
The output visualization.
"""
out = np.zeros_like(image)
labels = np.unique(label_field)
bg = (labels == bg_label)
if bg.any():
labels = labels[labels != bg_label]
out[bg] = bg_color
for label in labels:
mask = (label_field == label).nonzero()
color = image[mask].mean(axis=0)
out[mask] = color
return out
skimage/color/tests/test_colorlabel.py
+33
View File
@@ -89,6 +89,39 @@ def test_leave_labels_alone():
label2rgb(labels, bg_label=1)
assert_array_equal(labels, labels_saved)
def test_avg():
label_field = np.array([[1, 1, 1, 2],
[1, 2, 2, 2],
[3, 3, 3, 3]], dtype=np.uint8)
r = np.array([[1., 1., 0., 0.],
[0., 0., 1., 1.],
[0., 0., 0., 0.]])
g = np.array([[0., 0., 0., 1.],
[1., 1., 1., 0.],
[0., 0., 0., 0.]])
b = np.array([[0., 0., 0., 1.],
[0., 1., 1., 1.],
[0., 0., 1., 1.]])
image = np.dstack((r, g, b))
out = label2rgb(label_field, image, kind='avg')
rout = np.array([[0.5, 0.5, 0.5, 0.5],
[0.5, 0.5, 0.5, 0.5],
[0. , 0. , 0. , 0. ]])
gout = np.array([[0.25, 0.25, 0.25, 0.75],
[0.25, 0.75, 0.75, 0.75],
[0. , 0. , 0. , 0. ]])
bout = np.array([[0. , 0. , 0. , 1. ],
[0. , 1. , 1. , 1. ],
[0.5, 0.5, 0.5, 0.5]])
expected_out = np.dstack((rout, gout, bout))
assert_array_equal(out, expected_out)
out_bg = label2rgb(label_field, image, bg_label=2, bg_color=(0, 0, 0),
kind='avg')
expected_out_bg = expected_out.copy()
expected_out_bg[label_field == 2] = 0
assert_array_equal(out_bg, expected_out_bg)
if __name__ == '__main__':
testing.run_module_suite()