def test_sobel_vertical():
"""Sobel on a vertical edge should be a vertical line."""
i, j = cp.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = filters.sobel(image) * np.sqrt(2)
assert_allclose(result[j == 0], 1)
assert cp.all(result[cp.abs(j) > 1] == 0)
def test_hsv_value_with_non_float_output():
# Since `rgb2hsv` returns a float image and the result of the filtered
# result is inserted into the HSV image, we want to make sure there isn't
# a dtype mismatch.
filtered = edges_hsv_uint(COLOR_IMAGE)
filtered_value = color.rgb2hsv(filtered)[:, :, 2]
value = color.rgb2hsv(COLOR_IMAGE)[:, :, 2]
# Reduce tolerance because dtype conversion.
assert_allclose(filtered_value, filters.sobel(value), rtol=1e-5, atol=1e-5)
def test_sobel_horizontal():
"""Sobel on a horizontal edge should be a horizontal line."""
i, j = cp.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = filters.sobel(image) * np.sqrt(2)
# Check if result match transform direction
assert_allclose(result[i == 0], 1)
assert_allclose(result[cp.abs(i) > 1], 0)
def _singlescale_basic_features_singlechannel(img,
sigma,
intensity=True,
edges=True,
texture=True):
results = ()
gaussian_filtered = filters.gaussian(img, sigma)
if intensity:
results += (gaussian_filtered, )
if edges:
results += (filters.sobel(gaussian_filtered), )
if texture:
results += (*_texture_filter(gaussian_filtered), )
return results
def test_sobel_mask():
"""Sobel on a masked array should be zero."""
result = filters.sobel(cp.random.uniform(size=(10, 10)),
cp.zeros((10, 10), dtype=bool))
assert cp.all(result == 0)
def test_sobel_zeros():
"""Sobel on an array of all zeros."""
result = filters.sobel(cp.zeros((10, 10)), cp.ones((10, 10), bool))
assert cp.all(result == 0)
def test_hsv_value():
filtered = edges_hsv(COLOR_IMAGE)
value = color.rgb2hsv(COLOR_IMAGE)[:, :, 2]
assert_allclose(color.rgb2hsv(filtered)[:, :, 2], filters.sobel(value))
def test_each_channel():
filtered = edges_each(COLOR_IMAGE)
for i, channel in enumerate(cp.rollaxis(filtered, axis=-1)):
expected = img_as_float(filters.sobel(COLOR_IMAGE[:, :, i]))
assert_allclose(channel, expected)
def test_gray_scale_image():
# We don't need to test both `hsv_value` and `each_channel` since
# `adapt_rgb` is handling gray-scale inputs.
assert_allclose(edges_each(GRAY_IMAGE), filters.sobel(GRAY_IMAGE))
def edges_hsv_uint(image):
return img_as_uint(filters.sobel(image))
def edges_hsv(image):
return filters.sobel(image)
def edges_each(image):
return filters.sobel(image)