def test_dtype(self):
"""Check that the same output is produced regardless of image dtype."""
image_uint8 = cp.asarray(data.camera())
image_float = img_as_float(image_uint8)
result_uint8 = F.canny(image_uint8)
result_float = F.canny(image_float)
assert_array_equal(result_uint8, result_float)
def test_use_quantiles(self):
image = img_as_float(cp.asarray(data.camera()[::50, ::50]))
# Correct output produced manually with quantiles
# of 0.8 and 0.6 for high and low respectively
correct_output = cp.asarray(
[
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
],
dtype=bool,
)
result = F.canny(image,
low_threshold=0.6,
high_threshold=0.8,
use_quantiles=True)
assert_array_equal(result, correct_output)
def test_01_01_circle(self):
"""Test that the Canny filter finds the outlines of a circle"""
i, j = cp.mgrid[-200:200, -200:200].astype(float) / 200
c = cp.abs(cp.sqrt(i * i + j * j) - 0.5) < 0.02
result = feature.canny(c.astype(float), 4, 0, 0,
cp.ones(c.shape, bool))
#
# erode and dilate the circle to get rings that should contain the
# outlines
#
# TODO: grlee77: only implemented brute_force=True, so added that to
# these tests
cd = binary_dilation(c, iterations=3, brute_force=True)
ce = binary_erosion(c, iterations=3, brute_force=True)
cde = cp.logical_and(cd, cp.logical_not(ce))
self.assertTrue(cp.all(cde[result]))
#
# The circle has a radius of 100. There are two rings here, one
# for the inside edge and one for the outside. So that's
# 100 * 2 * 2 * 3 for those places where pi is still 3.
# The edge contains both pixels if there's a tie, so we
# bump the count a little.
point_count = cp.sum(result)
self.assertTrue(point_count > 1200)
self.assertTrue(point_count < 1600)
def test_01_02_circle_with_noise(self):
"""Test that the Canny filter finds the circle outlines
in a noisy image"""
cp.random.seed(0)
i, j = cp.mgrid[-200:200, -200:200].astype(float) / 200
c = cp.abs(cp.sqrt(i * i + j * j) - 0.5) < 0.02
cf = c.astype(float) * 0.5 + cp.random.uniform(size=c.shape) * 0.5
result = F.canny(cf, 4, 0.1, 0.2, cp.ones(c.shape, bool))
#
# erode and dilate the circle to get rings that should contain the
# outlines
#
cd = binary_dilation(c, iterations=4, brute_force=True)
ce = binary_erosion(c, iterations=4, brute_force=True)
cde = cp.logical_and(cd, cp.logical_not(ce))
self.assertTrue(cp.all(cde[result]))
point_count = cp.sum(result)
self.assertTrue(point_count > 1200)
self.assertTrue(point_count < 1600)
def test_use_quantiles(self):
image = img_as_float(cp.asarray(data.camera()[::100, ::100]))
# Correct output produced manually with quantiles
# of 0.8 and 0.6 for high and low respectively
correct_output = cp.asarray([
[False, False, False, False, False, False],
[False, True, True, True, False, False],
[False, False, False, True, False, False],
[False, False, False, True, False, False],
[False, False, True, True, False, False],
[False, False, False, False, False, False],
], )
result = feature.canny(image,
low_threshold=0.6,
high_threshold=0.8,
use_quantiles=True)
assert_array_equal(result, correct_output)
def test_mask_none(self):
result1 = F.canny(cp.zeros((20, 20)), 4, 0, 0, cp.ones((20, 20), bool))
result2 = F.canny(cp.zeros((20, 20)), 4, 0, 0)
self.assertTrue(cp.all(result1 == result2))
def test_00_01_zeros_mask(self):
"""Test that the Canny filter finds no points in a masked image"""
result = F.canny(cp.random.uniform(size=(20, 20)), 4, 0, 0,
cp.zeros((20, 20), bool))
self.assertFalse(cp.any(result))
def test_00_00_zeros(self):
"""Test that the Canny filter finds no points for a blank field"""
result = F.canny(cp.zeros((20, 20)), 4, 0, 0, cp.ones((20, 20), bool))
self.assertFalse(cp.any(result))