mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-27 19:48:43 +08:00
Stefan van der Walt
125 lines
5.2 KiB
Python
125 lines
5.2 KiB
Python
import numpy as np
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from numpy.testing import assert_equal, assert_raises
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from skimage import data
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from skimage import transform as tf
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from skimage.color import rgb2gray
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from skimage.feature import (BRIEF, match_descriptors,
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corner_peaks, corner_harris)
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def test_binary_descriptors_unequal_descriptor_sizes_error():
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"""Sizes of descriptors of keypoints to be matched should be equal."""
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descs1 = np.array([[True, True, False, True],
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[False, True, False, True]])
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descs2 = np.array([[True, False, False, True, False],
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[False, True, True, True, False]])
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assert_raises(ValueError, match_descriptors, descs1, descs2)
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def test_binary_descriptors():
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descs1 = np.array([[True, True, False, True, True],
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[False, True, False, True, True]])
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descs2 = np.array([[True, False, False, True, False],
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[False, False, True, True, True]])
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matches = match_descriptors(descs1, descs2)
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assert_equal(matches, [[0, 0], [1, 1]])
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def test_binary_descriptors_rotation_crosscheck_false():
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"""Verify matched keypoints and their corresponding masks results between
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image and its rotated version with the expected keypoint pairs with
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cross_check disabled."""
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img = data.astronaut()
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img = rgb2gray(img)
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tform = tf.SimilarityTransform(scale=1, rotation=0.15, translation=(0, 0))
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rotated_img = tf.warp(img, tform, clip=False)
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extractor = BRIEF(descriptor_size=512)
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keypoints1 = corner_peaks(corner_harris(img), min_distance=5,
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threshold_abs=0, threshold_rel=0.1)
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extractor.extract(img, keypoints1)
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descriptors1 = extractor.descriptors
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keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5,
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threshold_abs=0, threshold_rel=0.1)
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extractor.extract(rotated_img, keypoints2)
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descriptors2 = extractor.descriptors
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matches = match_descriptors(descriptors1, descriptors2, cross_check=False)
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exp_matches1 = np.array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
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12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
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24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
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36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46])
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exp_matches2 = np.array([ 0, 31, 2, 3, 1, 4, 6, 4, 38, 5, 27, 7,
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13, 10, 9, 27, 7, 11, 15, 8, 23, 14, 12, 16,
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10, 25, 18, 19, 21, 20, 41, 24, 25, 26, 28, 27,
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22, 23, 29, 30, 31, 32, 35, 33, 34, 30, 36])
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assert_equal(matches[:, 0], exp_matches1)
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assert_equal(matches[:, 1], exp_matches2)
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def test_binary_descriptors_rotation_crosscheck_true():
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"""Verify matched keypoints and their corresponding masks results between
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image and its rotated version with the expected keypoint pairs with
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cross_check enabled."""
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img = data.astronaut()
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img = rgb2gray(img)
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tform = tf.SimilarityTransform(scale=1, rotation=0.15, translation=(0, 0))
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rotated_img = tf.warp(img, tform, clip=False)
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extractor = BRIEF(descriptor_size=512)
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keypoints1 = corner_peaks(corner_harris(img), min_distance=5,
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threshold_abs=0, threshold_rel=0.1)
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extractor.extract(img, keypoints1)
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descriptors1 = extractor.descriptors
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keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5,
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threshold_abs=0, threshold_rel=0.1)
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extractor.extract(rotated_img, keypoints2)
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descriptors2 = extractor.descriptors
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matches = match_descriptors(descriptors1, descriptors2, cross_check=True)
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exp_matches1 = np.array([ 0, 2, 3, 4, 5, 6, 9, 11, 12, 13, 14, 17,
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18, 19, 21, 22, 23, 26, 27, 28, 29, 31, 32, 33,
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34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46])
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exp_matches2 = np.array([ 0, 2, 3, 1, 4, 6, 5, 7, 13, 10, 9, 11,
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15, 8, 14, 12, 16, 18, 19, 21, 20, 24, 25, 26,
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28, 27, 22, 23, 29, 30, 31, 32, 35, 33, 34, 36])
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assert_equal(matches[:, 0], exp_matches1)
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assert_equal(matches[:, 1], exp_matches2)
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def test_max_distance():
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descs1 = np.zeros((10, 128))
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descs2 = np.zeros((15, 128))
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descs1[0, :] = 1
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matches = match_descriptors(descs1, descs2, metric='euclidean',
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max_distance=0.1, cross_check=False)
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assert len(matches) == 9
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matches = match_descriptors(descs1, descs2, metric='euclidean',
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max_distance=np.sqrt(128.1),
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cross_check=False)
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assert len(matches) == 10
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matches = match_descriptors(descs1, descs2, metric='euclidean',
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max_distance=0.1,
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cross_check=True)
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assert_equal(matches, [[1, 0]])
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matches = match_descriptors(descs1, descs2, metric='euclidean',
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max_distance=np.sqrt(128.1),
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cross_check=True)
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assert_equal(matches, [[1, 0]])
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if __name__ == '__main__':
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from numpy import testing
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testing.run_module_suite()
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