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Merge pull request #1 from emmanuelle/active-contour

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Some minor PEP8 issues
This commit is contained in:
Julius Bier Kirkegaard
2015-12-12 01:01:04 +00:00
parent 320977c8b9 a16c530322
commit d8c7160eb2
2 changed files with 19 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/examples/plot_active_contours.py
+2 -2
View File
@@ -40,7 +40,7 @@ y = 100 + 100*np.sin(s)
init = np.array([x, y]).T
snake = active_contour(gaussian_filter(img, 3),
init, alpha=0.015, beta=10, gamma=0.001)
init, alpha=0.015, beta=10, gamma=0.001)
fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot(111)
@@ -67,7 +67,7 @@ y = np.linspace(136, 50, 100)
init = np.array([x, y]).T
snake = active_contour(gaussian_filter(img, 1), init, bc='fixed',
alpha=0.1, beta=1.0, w_line=-5, w_edge=0, gamma=0.1)
alpha=0.1, beta=1.0, w_line=-5, w_edge=0, gamma=0.1)
fig = plt.figure(figsize=(9, 5))
ax = fig.add_subplot(111)
skimage/segmentation/active_contour_model.py
+17 -16
View File
@@ -1,4 +1,3 @@
import warnings
import numpy as np
from skimage import img_as_float
import scipy
@@ -6,6 +5,7 @@ import scipy.linalg
from scipy.interpolate import RectBivariateSpline, interp2d
from skimage.filters import sobel
def active_contour(image, snake, alpha=0.01, beta=0.1,
w_line=0, w_edge=1, gamma=0.01,
bc='periodic', max_px_move=1.0,
@@ -100,7 +100,7 @@ def active_contour(image, snake, alpha=0.01, beta=0.1,
valid_bcs = ['periodic', 'free', 'fixed', 'free-fixed',
'fixed-free', 'fixed-fixed', 'free-free']
if bc not in valid_bcs:
raise ValueError("Invalid boundary condition.\n"+
raise ValueError("Invalid boundary condition.\n" +
"Should be one of: "+", ".join(valid_bcs)+'.')
img = img_as_float(image)
RGB = img.ndim == 3
@@ -130,11 +130,12 @@ def active_contour(image, snake, alpha=0.01, beta=0.1,
# Interpolate for smoothness:
if new_scipy:
intp = RectBivariateSpline(np.arange(img.shape[1]),
np.arange(img.shape[0]), img.T, kx=2, ky=2, s=0)
np.arange(img.shape[0]),
img.T, kx=2, ky=2, s=0)
else:
intp = np.vectorize(interp2d(np.arange(img.shape[1]),
np.arange(img.shape[0]), img, kind='cubic', copy=False,
bounds_error=False, fill_value=0))
np.arange(img.shape[0]), img, kind='cubic',
copy=False, bounds_error=False, fill_value=0))
x, y = snake[:, 0].copy(), snake[:, 1].copy()
xsave = np.empty((convergence_order, len(x)))
@@ -142,14 +143,14 @@ def active_contour(image, snake, alpha=0.01, beta=0.1,
# Build snake shape matrix for Euler equation
n = len(x)
a = np.roll(np.eye(n), -1, axis=0) \
+ np.roll(np.eye(n), -1, axis=1) \
- 2*np.eye(n) # second order derivative, central difference
b = np.roll(np.eye(n), -2, axis=0) \
+ np.roll(np.eye(n), -2, axis=1) \
- 4*np.roll(np.eye(n), -1, axis=0) \
- 4*np.roll(np.eye(n), -1, axis=1) \
+ 6*np.eye(n) # fourth order derivative, central difference
a = np.roll(np.eye(n), -1, axis=0) + \
np.roll(np.eye(n), -1, axis=1) - \
2*np.eye(n) # second order derivative, central difference
b = np.roll(np.eye(n), -2, axis=0) + \
np.roll(np.eye(n), -2, axis=1) - \
4*np.roll(np.eye(n), -1, axis=0) - \
4*np.roll(np.eye(n), -1, axis=1) + \
6*np.eye(n) # fourth order derivative, central difference
A = -alpha*a + beta*b
# Impose boundary conditions different from periodic:
@@ -220,13 +221,13 @@ def active_contour(image, snake, alpha=0.01, beta=0.1,
# Convergence criteria needs to compare to a number of previous
# configurations since oscillations can occur.
j = i%(convergence_order+1)
j = i % (convergence_order+1)
if j < convergence_order:
xsave[j, :] = x
ysave[j, :] = y
else:
dist = np.min(np.max(np.abs(xsave-x[None, :])
+ np.abs(ysave-y[None, :]), 1))
dist = np.min(np.max(np.abs(xsave-x[None, :]) +
np.abs(ysave-y[None, :]), 1))
if dist < convergence:
break