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Fixed database typo and removed unnecessary class identifier.

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Batuhan Berk Başoğlu 2020-10-14 10:10:37 -04:00
parent 00ad49a143
commit 45fb349a7d
5098 changed files with 952558 additions and 85 deletions
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venv/Lib/site-packages/skimage/segmentation/tests/test_boundaries.py Normal file
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import numpy as np
from skimage.segmentation import find_boundaries, mark_boundaries
from skimage._shared.testing import assert_array_equal, assert_allclose
white = (1, 1, 1)
def test_find_boundaries():
image = np.zeros((10, 10), dtype=np.uint8)
image[2:7, 2:7] = 1
ref = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
result = find_boundaries(image)
assert_array_equal(result, ref)
def test_find_boundaries_bool():
image = np.zeros((5, 5), dtype=np.bool)
image[2:5, 2:5] = True
ref = np.array([[False, False, False, False, False],
[False, False, True, True, True],
[False, True, True, True, True],
[False, True, True, False, False],
[False, True, True, False, False]], dtype=np.bool)
result = find_boundaries(image)
assert_array_equal(result, ref)
def test_mark_boundaries():
image = np.zeros((10, 10))
label_image = np.zeros((10, 10), dtype=np.uint8)
label_image[2:7, 2:7] = 1
ref = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
marked = mark_boundaries(image, label_image, color=white, mode='thick')
result = np.mean(marked, axis=-1)
assert_array_equal(result, ref)
ref = np.array([[0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
[2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
[2, 1, 1, 1, 1, 1, 1, 1, 2, 0],
[2, 1, 1, 2, 2, 2, 1, 1, 2, 0],
[2, 1, 1, 2, 0, 2, 1, 1, 2, 0],
[2, 1, 1, 2, 2, 2, 1, 1, 2, 0],
[2, 1, 1, 1, 1, 1, 1, 1, 2, 0],
[2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
[0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
marked = mark_boundaries(image, label_image, color=white,
outline_color=(2, 2, 2), mode='thick')
result = np.mean(marked, axis=-1)
assert_array_equal(result, ref)
def test_mark_boundaries_bool():
image = np.zeros((10, 10), dtype=np.bool)
label_image = np.zeros((10, 10), dtype=np.uint8)
label_image[2:7, 2:7] = 1
ref = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
marked = mark_boundaries(image, label_image, color=white, mode='thick')
result = np.mean(marked, axis=-1)
assert_array_equal(result, ref)
def test_mark_boundaries_subpixel():
labels = np.array([[0, 0, 0, 0],
[0, 0, 5, 0],
[0, 1, 5, 0],
[0, 0, 5, 0],
[0, 0, 0, 0]], dtype=np.uint8)
np.random.seed(0)
image = np.round(np.random.rand(*labels.shape), 2)
marked = mark_boundaries(image, labels, color=white, mode='subpixel')
marked_proj = np.round(np.mean(marked, axis=-1), 2)
ref_result = np.array(
[[ 0.55, 0.63, 0.72, 0.69, 0.6 , 0.55, 0.54],
[ 0.45, 0.58, 0.72, 1. , 1. , 1. , 0.69],
[ 0.42, 0.54, 0.65, 1. , 0.44, 1. , 0.89],
[ 0.69, 1. , 1. , 1. , 0.69, 1. , 0.83],
[ 0.96, 1. , 0.38, 1. , 0.79, 1. , 0.53],
[ 0.89, 1. , 1. , 1. , 0.38, 1. , 0.16],
[ 0.57, 0.78, 0.93, 1. , 0.07, 1. , 0.09],
[ 0.2 , 0.52, 0.92, 1. , 1. , 1. , 0.54],
[ 0.02, 0.35, 0.83, 0.9 , 0.78, 0.81, 0.87]])
assert_allclose(marked_proj, ref_result, atol=0.01)