138 lines
5.3 KiB
Python
138 lines
5.3 KiB
Python
import numpy as np
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import pytest
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from numpy.testing import assert_array_equal, assert_allclose
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from skimage._shared.utils import _supported_float_type
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from skimage.segmentation import find_boundaries, mark_boundaries
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white = (1, 1, 1)
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def test_find_boundaries():
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image = np.zeros((10, 10), dtype=np.uint8)
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image[2:7, 2:7] = 1
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ref = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
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result = find_boundaries(image)
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assert_array_equal(result, ref)
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def test_find_boundaries_bool():
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image = np.zeros((5, 5), dtype=bool)
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image[2:5, 2:5] = True
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ref = np.array([[False, False, False, False, False],
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[False, False, True, True, True],
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[False, True, True, True, True],
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[False, True, True, False, False],
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[False, True, True, False, False]], dtype=bool)
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result = find_boundaries(image)
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assert_array_equal(result, ref)
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@pytest.mark.parametrize(
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'dtype', [np.uint8, np.float16, np.float32, np.float64]
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)
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def test_mark_boundaries(dtype):
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image = np.zeros((10, 10), dtype=dtype)
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label_image = np.zeros((10, 10), dtype=np.uint8)
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label_image[2:7, 2:7] = 1
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ref = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
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marked = mark_boundaries(image, label_image, color=white, mode='thick')
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assert marked.dtype == _supported_float_type(dtype)
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result = np.mean(marked, axis=-1)
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assert_array_equal(result, ref)
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ref = np.array([[0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
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[2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
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[2, 1, 1, 1, 1, 1, 1, 1, 2, 0],
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[2, 1, 1, 2, 2, 2, 1, 1, 2, 0],
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[2, 1, 1, 2, 0, 2, 1, 1, 2, 0],
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[2, 1, 1, 2, 2, 2, 1, 1, 2, 0],
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[2, 1, 1, 1, 1, 1, 1, 1, 2, 0],
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[2, 2, 1, 1, 1, 1, 1, 2, 2, 0],
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[0, 2, 2, 2, 2, 2, 2, 2, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
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marked = mark_boundaries(image, label_image, color=white,
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outline_color=(2, 2, 2), mode='thick')
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result = np.mean(marked, axis=-1)
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assert_array_equal(result, ref)
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def test_mark_boundaries_bool():
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image = np.zeros((10, 10), dtype=bool)
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label_image = np.zeros((10, 10), dtype=np.uint8)
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label_image[2:7, 2:7] = 1
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ref = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 0, 0, 0, 1, 1, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
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marked = mark_boundaries(image, label_image, color=white, mode='thick')
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result = np.mean(marked, axis=-1)
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assert_array_equal(result, ref)
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@pytest.mark.parametrize('dtype', [np.float16, np.float32, np.float64])
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def test_mark_boundaries_subpixel(dtype):
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labels = np.array([[0, 0, 0, 0],
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[0, 0, 5, 0],
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[0, 1, 5, 0],
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[0, 0, 5, 0],
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[0, 0, 0, 0]], dtype=np.uint8)
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np.random.seed(0)
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image = np.round(np.random.rand(*labels.shape), 2)
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image = image.astype(dtype, copy=False)
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marked = mark_boundaries(image, labels, color=white, mode='subpixel')
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assert marked.dtype == _supported_float_type(dtype)
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marked_proj = np.round(np.mean(marked, axis=-1), 2)
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ref_result = np.array(
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[[ 0.55, 0.63, 0.72, 0.69, 0.6 , 0.55, 0.54],
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[ 0.45, 0.58, 0.72, 1. , 1. , 1. , 0.69],
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[ 0.42, 0.54, 0.65, 1. , 0.44, 1. , 0.89],
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[ 0.69, 1. , 1. , 1. , 0.69, 1. , 0.83],
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[ 0.96, 1. , 0.38, 1. , 0.79, 1. , 0.53],
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[ 0.89, 1. , 1. , 1. , 0.38, 1. , 0.16],
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[ 0.57, 0.78, 0.93, 1. , 0.07, 1. , 0.09],
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[ 0.2 , 0.52, 0.92, 1. , 1. , 1. , 0.54],
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[ 0.02, 0.35, 0.83, 0.9 , 0.78, 0.81, 0.87]])
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assert_allclose(marked_proj, ref_result, atol=0.01)
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@pytest.mark.parametrize('mode', ['thick', 'inner', 'outer', 'subpixel'])
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def test_boundaries_constant_image(mode):
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"""A constant-valued image has not boundaries."""
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ones = np.ones((8, 8), dtype=int)
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b = find_boundaries(ones, mode=mode)
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assert np.all(b == 0)
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