106 lines
3.9 KiB
Python
106 lines
3.9 KiB
Python
import numpy as np
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from skimage._shared.testing import assert_array_equal
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from skimage.data import moon
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from skimage.feature import CENSURE
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from skimage._shared.testing import test_parallel
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from skimage._shared import testing
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from skimage.transform import rescale
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img = moon()
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np.random.seed(0)
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def test_censure_on_rectangular_images():
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"""Censure feature detector should work on 2D image of any shape."""
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rect_image = np.random.rand(300, 200)
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square_image = np.random.rand(200, 200)
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CENSURE().detect((square_image))
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CENSURE().detect((rect_image))
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def test_keypoints_censure_color_image_unsupported_error():
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"""Censure keypoints can be extracted from gray-scale images only."""
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with testing.raises(ValueError):
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CENSURE().detect(np.zeros((20, 20, 3)))
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def test_keypoints_censure_mode_validity_error():
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"""Mode argument in keypoints_censure can be either DoB, Octagon or
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STAR."""
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with testing.raises(ValueError):
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CENSURE(mode='dummy')
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def test_keypoints_censure_scale_range_error():
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"""Difference between the the max_scale and min_scale parameters in
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keypoints_censure should be greater than or equal to two."""
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with testing.raises(ValueError):
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CENSURE(min_scale=1, max_scale=2)
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def test_keypoints_censure_moon_image_dob():
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"""Verify the actual Censure keypoints and their corresponding scale with
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the expected values for DoB filter."""
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detector = CENSURE()
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detector.detect(img)
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expected_keypoints = np.array([[ 21, 497],
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[ 36, 46],
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[119, 350],
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[185, 177],
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[287, 250],
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[357, 239],
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[463, 116],
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[464, 132],
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[467, 260]])
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expected_scales = np.array([3, 4, 4, 2, 2, 3, 2, 2, 2])
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assert_array_equal(expected_keypoints, detector.keypoints)
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assert_array_equal(expected_scales, detector.scales)
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@test_parallel()
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def test_keypoints_censure_moon_image_octagon():
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"""Verify the actual Censure keypoints and their corresponding scale with
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the expected values for Octagon filter."""
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detector = CENSURE(mode='octagon')
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# quarter scale image for speed
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detector.detect(rescale(img, 0.25,
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multichannel=False,
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anti_aliasing=False,
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mode='constant'))
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expected_keypoints = np.array([[ 23, 27],
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[ 29, 89],
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[ 31, 87],
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[106, 59],
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[111, 67]])
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expected_scales = np.array([3, 2, 5, 2, 4])
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assert_array_equal(expected_keypoints, detector.keypoints)
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assert_array_equal(expected_scales, detector.scales)
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def test_keypoints_censure_moon_image_star():
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"""Verify the actual Censure keypoints and their corresponding scale with
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the expected values for STAR filter."""
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detector = CENSURE(mode='star')
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# quarter scale image for speed
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detector.detect(rescale(img, 0.25,
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multichannel=False,
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anti_aliasing=False,
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mode='constant'))
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expected_keypoints = np.array([[ 23, 27],
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[ 29, 89],
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[ 30, 86],
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[107, 59],
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[109, 64],
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[111, 67],
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[113, 70]])
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expected_scales = np.array([3, 2, 4, 2, 5, 3, 2])
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assert_array_equal(expected_keypoints, detector.keypoints)
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assert_array_equal(expected_scales, detector.scales)
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