Vehicle-Anti-Theft-Face-Rec.../venv/Lib/site-packages/skimage/morphology/tests/test_misc.py

191 lines
8.1 KiB
Python

import numpy as np
from skimage.morphology import remove_small_objects, remove_small_holes
from skimage._shared import testing
from skimage._shared.testing import assert_array_equal, assert_equal
from skimage._shared._warnings import expected_warnings
test_image = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 1]], bool)
def test_one_connectivity():
expected = np.array([[0, 0, 0, 0, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], bool)
observed = remove_small_objects(test_image, min_size=6)
assert_array_equal(observed, expected)
def test_two_connectivity():
expected = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], bool)
observed = remove_small_objects(test_image, min_size=7, connectivity=2)
assert_array_equal(observed, expected)
def test_in_place():
image = test_image.copy()
observed = remove_small_objects(image, min_size=6, in_place=True)
assert_equal(observed is image, True,
"remove_small_objects in_place argument failed.")
def test_labeled_image():
labeled_image = np.array([[2, 2, 2, 0, 1],
[2, 2, 2, 0, 1],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=int)
expected = np.array([[2, 2, 2, 0, 0],
[2, 2, 2, 0, 0],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=int)
observed = remove_small_objects(labeled_image, min_size=3)
assert_array_equal(observed, expected)
def test_uint_image():
labeled_image = np.array([[2, 2, 2, 0, 1],
[2, 2, 2, 0, 1],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=np.uint8)
expected = np.array([[2, 2, 2, 0, 0],
[2, 2, 2, 0, 0],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=np.uint8)
observed = remove_small_objects(labeled_image, min_size=3)
assert_array_equal(observed, expected)
def test_single_label_warning():
image = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], int)
with expected_warnings(['use a boolean array?']):
remove_small_objects(image, min_size=6)
def test_float_input():
float_test = np.random.rand(5, 5)
with testing.raises(TypeError):
remove_small_objects(float_test)
def test_negative_input():
negative_int = np.random.randint(-4, -1, size=(5, 5))
with testing.raises(ValueError):
remove_small_objects(negative_int)
test_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], np.bool_)
def test_one_connectivity_holes():
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], np.bool_)
observed = remove_small_holes(test_holes_image, area_threshold=3)
assert_array_equal(observed, expected)
def test_two_connectivity_holes():
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], np.bool_)
observed = remove_small_holes(test_holes_image, area_threshold=3,
connectivity=2)
assert_array_equal(observed, expected)
def test_in_place_holes():
image = test_holes_image.copy()
observed = remove_small_holes(image, area_threshold=3, in_place=True)
assert_equal(observed is image, True,
"remove_small_holes in_place argument failed.")
def test_labeled_image_holes():
labeled_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]],
dtype=np.int_)
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], dtype=np.bool_)
with expected_warnings(['returned as a boolean array']):
observed = remove_small_holes(labeled_holes_image, area_threshold=3)
assert_array_equal(observed, expected)
def test_uint_image_holes():
labeled_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]],
dtype=np.uint8)
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], dtype=np.bool_)
with expected_warnings(['returned as a boolean array']):
observed = remove_small_holes(labeled_holes_image, area_threshold=3)
assert_array_equal(observed, expected)
def test_label_warning_holes():
labeled_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]],
dtype=np.int_)
with expected_warnings(['use a boolean array?']):
remove_small_holes(labeled_holes_image, area_threshold=3)
remove_small_holes(labeled_holes_image.astype(bool), area_threshold=3)
def test_float_input_holes():
float_test = np.random.rand(5, 5)
with testing.raises(TypeError):
remove_small_holes(float_test)