wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-30 12:31:08 +08:00
Code Issues Packages Projects Releases Wiki Activity

DOC: minor example clean up.

Browse Source
This commit is contained in:
Tony S Yu
2012-02-20 09:45:17 -05:00
parent cb93ebbf61
commit 520c961a0c
3 changed files with 11 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/examples/plot_watershed.py
+6 -5
View File
@@ -19,9 +19,10 @@ opposite of the distance) are chosen as markers, and the flooding of
basins from such markers separates the two circles along a watershed
line.
See `Wikipedia
<http://en.wikipedia.org/wiki/Watershed_(image_processing)>`__ for
more details on the algorithm.
See Wikipedia_ for more details on the algorithm.
.. _Wikipedia: <http://en.wikipedia.org/wiki/Watershed_(image_processing)>
"""
import numpy as np
@@ -36,9 +37,9 @@ r1, r2 = 16, 20
mask_circle1 = (x - x1)**2 + (y - y1)**2 < r1**2
mask_circle2 = (x - x2)**2 + (y - y2)**2 < r2**2
image = np.logical_or(mask_circle1, mask_circle2)
# Now we want to separate the two objects in image
# Generate the markers as local maxima of the distance
# to the background
# Generate the markers as local maxima of the distance to the background
from scipy import ndimage
distance = ndimage.distance_transform_edt(image)
local_maxi = is_local_maximum(distance, image, np.ones((3, 3)))