def test_vprewitt_horizontal():
"""Vertical prewitt on a horizontal edge should be zero"""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = F.vprewitt(image)
eps = .000001
assert (np.all(np.abs(result) < eps))
def test_vprewitt_horizontal():
"""Vertical prewitt on a horizontal edge should be zero"""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = F.vprewitt(image)
eps = .000001
assert (np.all(np.abs(result) < eps))
def test_vprewitt_vertical():
"""Vertical prewitt on an edge should be a vertical line."""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = F.vprewitt(image)
# Fudge the eroded points
j[np.abs(i) == 5] = 10000
assert (np.all(result[j == 0] == 1))
assert_allclose(result[np.abs(j) > 1], 0, atol=1e-10)
def test_vprewitt_vertical():
"""Vertical prewitt on an edge should be a vertical line"""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = F.vprewitt(image)
# Fudge the eroded points
j[np.abs(i) == 5] = 10000
assert (np.all(result[j == 0] == 1))
eps = .000001
assert (np.all(np.abs(result[np.abs(j) > 1]) < eps))
def test_vprewitt_vertical():
"""Vertical prewitt on an edge should be a vertical line"""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = F.vprewitt(image)
# Fudge the eroded points
j[np.abs(i) == 5] = 10000
assert (np.all(result[j == 0] == 1))
eps = .000001
assert (np.all(np.abs(result[np.abs(j) > 1]) < eps))
def test_vprewitt_horizontal():
"""Vertical prewitt on a horizontal edge should be zero."""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = F.vprewitt(image)
assert_allclose(result, 0)
def test_vprewitt_mask():
"""Vertical prewitt on a masked array should be zero."""
np.random.seed(0)
result = F.vprewitt(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
assert_allclose(result, 0)
def test_vprewitt_zeros():
"""Vertical prewitt on an array of all zeros."""
result = F.vprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert_allclose(result, 0)
def test_vprewitt_zeros():
"""Vertical prewitt on an array of all zeros"""
result = F.vprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))
def vedges(self):
"""x=vedges(): returns a parameterization of the number of vertical edges versus total edges in an RGB image"""
hprew=filter.hprewitt(self.gray)
vprew=filter.vprewitt(self.gray)
vfrac=vprew.sum()/(vprew.sum()+hprew.sum())
return vfrac
import scipy.misc
from skimage import filter
from scipy.misc.pilutil import Image
# opening the image and converting it to grayscale
a = Image.open('../Figures/steps1.png').convert('L')
# performing vertical Prewitt
b = filter.vprewitt(a)
# b is converted from an ndarray to an image
b = scipy.misc.toimage(b)
b.save('../Figures/vprewitt_output.png')
def test_vprewitt_mask():
"""Vertical prewitt on a masked array should be zero"""
np.random.seed(0)
result = F.vprewitt(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
assert (np.all(result == 0))
def test_vprewitt_zeros():
"""Vertical prewitt on an array of all zeros"""
result = F.vprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))
def test_00_01_mask(self):
"""Vertical prewitt on a masked array should be zero"""
np.random.seed(0)
result = F.vprewitt(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
assert (np.all(result == 0))