def test_skeletonize_num_neighbours(self):
# an empty image
image = np.zeros((300, 300))
# foreground object 1
image[10:-10, 10:100] = 1
image[-100:-10, 10:-10] = 1
image[10:-10, -100:-10] = 1
# foreground object 2
rs, cs = draw.bresenham(250, 150, 10, 280)
for i in range(10):
image[rs + i, cs] = 1
rs, cs = draw.bresenham(10, 150, 250, 280)
for i in range(20):
image[rs + i, cs] = 1
# foreground object 3
ir, ic = np.indices(image.shape)
circle1 = (ic - 135)**2 + (ir - 150)**2 < 30**2
circle2 = (ic - 135)**2 + (ir - 150)**2 < 20**2
image[circle1] = 1
image[circle2] = 0
result = skeletonize(image)
# there should never be a 2x2 block of foreground pixels in a skeleton
mask = np.array([[1, 1],
[1, 1]], np.uint8)
blocks = correlate(result, mask, mode='constant')
assert not numpy.any(blocks == 4)
def test_skeletonize_num_neighbours(self):
# an empty image
image = np.zeros((300, 300))
# foreground object 1
image[10:-10, 10:100] = 1
image[-100:-10, 10:-10] = 1
image[10:-10, -100:-10] = 1
# foreground object 2
rs, cs = draw.bresenham(250, 150, 10, 280)
for i in range(10):
image[rs + i, cs] = 1
rs, cs = draw.bresenham(10, 150, 250, 280)
for i in range(20):
image[rs + i, cs] = 1
# foreground object 3
ir, ic = np.indices(image.shape)
circle1 = (ic - 135)**2 + (ir - 150)**2 < 30**2
circle2 = (ic - 135)**2 + (ir - 150)**2 < 20**2
image[circle1] = 1
image[circle2] = 0
result = skeletonize(image)
# there should never be a 2x2 block of foreground pixels in a skeleton
mask = np.array([[1, 1], [1, 1]], np.uint8)
blocks = correlate(result, mask, mode='constant')
assert not numpy.any(blocks == 4)
""" from skimage.morphology import skeletonize from skimage.draw import draw import numpy as np import matplotlib.pyplot as plt # an empty image image = np.zeros((400, 400)) # foreground object 1 image[10:-10, 10:100] = 1 image[-100:-10, 10:-10] = 1 image[10:-10, -100:-10] = 1 # foreground object 2 rs, cs = draw.bresenham(250, 150, 10, 280) for i in range(10): image[rs+i, cs] = 1 rs, cs = draw.bresenham(10, 150, 250, 280) for i in range(20): image[rs+i, cs] = 1 # foreground object 3 ir, ic = np.indices(image.shape) circle1 = (ic - 135)**2 + (ir - 150)**2 < 30**2 circle2 = (ic - 135)**2 + (ir - 150)**2 < 20**2 image[circle1] = 1 image[circle2] = 0 # perform skeletonization skeleton = skeletonize(image) # display results
"""
from skimage.morphology import skeletonize
from skimage.draw import draw
import numpy as np
import matplotlib.pyplot as plt
# an empty image
image = np.zeros((400, 400))
# foreground object 1
image[10:-10, 10:100] = 1
image[-100:-10, 10:-10] = 1
image[10:-10, -100:-10] = 1
# foreground object 2
rs, cs = draw.bresenham(250, 150, 10, 280)
for i in range(10):
image[rs + i, cs] = 1
rs, cs = draw.bresenham(10, 150, 250, 280)
for i in range(20):
image[rs + i, cs] = 1
# foreground object 3
ir, ic = np.indices(image.shape)
circle1 = (ic - 135)**2 + (ir - 150)**2 < 30**2
circle2 = (ic - 135)**2 + (ir - 150)**2 < 20**2
image[circle1] = 1
image[circle2] = 0
# perform skeletonization
skeleton = skeletonize(image)