def test_selem_overflow():
strel = np.ones((17, 17), dtype=np.uint8)
img = np.zeros((20, 20), dtype=bool)
img[2:19, 2:19] = True
binary_res = binary.binary_erosion(img, strel)
gray_res = img_as_bool(gray.erosion(img, strel))
testing.assert_array_equal(binary_res, gray_res)
def test_selem_overflow():
strel = np.ones((17, 17), dtype=np.uint8)
img = np.zeros((20, 20), dtype=bool)
img[2:19, 2:19] = True
binary_res = binary.binary_erosion(img, strel)
grey_res = img_as_bool(grey.erosion(img, strel))
testing.assert_array_equal(binary_res, grey_res)
def test_footprint_overflow():
footprint = np.ones((17, 17), dtype=np.uint8)
img = np.zeros((20, 20), dtype=bool)
img[2:19, 2:19] = True
binary_res = binary.binary_erosion(img, footprint)
gray_res = img_as_bool(gray.erosion(img, footprint))
assert_array_equal(binary_res, gray_res)
def test_selem_overflow():
strel = np.ones((17, 17), dtype=np.uint8)
img = np.zeros((20, 20))
img[2:19, 2:19] = 1
binary_res = binary.binary_erosion(img, strel)
with expected_warnings(['precision loss']):
grey_res = img_as_bool(grey.erosion(img, strel))
testing.assert_array_equal(binary_res, grey_res)
def mark_areas(image: np.ndarray) -> Tuple[np.ndarray, int]:
"""
Method to segment clustered areas
:param image: The image to segment
:return: The segmented area
"""
# Define mask
mask = create_circular_mask(40, 40)
# Fill image
fill = binary_fill_holes(image)
# Perform binary erosion on image
er = binary_erosion(fill, selem=mask)
# Label eroded map
lab, nums = label(er)
# Dilate eroded map
lab = dilation(lab, selem=mask)
return lab, nums
def test_binary_erosion():
strel = selem.square(3)
binary_res = binary.binary_erosion(bw_img, strel)
grey_res = img_as_bool(grey.erosion(bw_img, strel))
testing.assert_array_equal(binary_res, grey_res)
def test_non_square_image():
strel = selem.square(3)
binary_res = binary.binary_erosion(bw_img[:100, :200], strel)
grey_res = img_as_bool(grey.erosion(bw_img[:100, :200], strel))
testing.assert_array_equal(binary_res, grey_res)
def test_binary_erosion():
strel = selem.square(3)
binary_res = binary.binary_erosion(bw_img, strel)
gray_res = img_as_bool(gray.erosion(bw_img, strel))
testing.assert_array_equal(binary_res, gray_res)
def test_non_square_image():
strel = selem.square(3)
binary_res = binary.binary_erosion(bw_img[:100, :200], strel)
gray_res = img_as_bool(gray.erosion(bw_img[:100, :200], strel))
testing.assert_array_equal(binary_res, gray_res)
def test_binary_erosion():
footprint = morphology.square(3)
binary_res = binary.binary_erosion(bw_img, footprint)
gray_res = img_as_bool(gray.erosion(bw_img, footprint))
assert_array_equal(binary_res, gray_res)
def test_non_square_image():
footprint = morphology.square(3)
binary_res = binary.binary_erosion(bw_img[:100, :200], footprint)
gray_res = img_as_bool(gray.erosion(bw_img[:100, :200], footprint))
assert_array_equal(binary_res, gray_res)
def test_binary_erosion():
strel = selem.square(3)
binary_res = binary.binary_erosion(bw_img, strel)
with expected_warnings(['precision loss']):
grey_res = img_as_bool(grey.erosion(bw_img, strel))
testing.assert_array_equal(binary_res, grey_res)
def test_binary_erosion():
strel = selem.square(3)
binary_res = binary.binary_erosion(bw_lena, strel)
grey_res = grey.erosion(bw_lena, strel)
testing.assert_array_equal(binary_res, grey_res)