mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 03:37:34 +08:00
Johannes Schönberger
116 lines
6.1 KiB
Python
116 lines
6.1 KiB
Python
import numpy as np
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from numpy.testing import assert_array_equal, assert_almost_equal
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from skimage.feature import ORB
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from skimage.data import lena
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from skimage.color import rgb2gray
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img = rgb2gray(lena())
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def test_keypoints_orb_desired_no_of_keypoints():
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detector_extractor = ORB(n_keypoints=10, fast_n=12, fast_threshold=0.20)
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detector_extractor.detect(img)
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exp_rows = np.array([ 435. , 435.6 , 376. , 455. , 434.88, 269. ,
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375.6 , 310.8 , 413. , 311.04])
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exp_cols = np.array([ 180. , 180. , 156. , 176. , 180. , 111. ,
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156. , 172.8, 70. , 172.8])
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exp_scales = np.array([ 1. , 1.2 , 1. , 1. , 1.44 , 1. ,
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1.2 , 1.2 , 1. , 1.728])
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exp_orientations = np.array([-175.64733392, -167.94842949, -148.98350192,
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-142.03599837, -176.08535837, -53.08162354,
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-150.89208271, 97.7693776 , -173.4479964 ,
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38.66312042])
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exp_response = np.array([ 0.96770745, 0.81027306, 0.72376257,
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0.5626413 , 0.5097993 , 0.44351774,
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0.39154173, 0.39084861, 0.39063076,
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0.37602487])
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assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
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assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
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assert_almost_equal(exp_scales, detector_extractor.scales)
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assert_almost_equal(exp_response, detector_extractor.responses)
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assert_almost_equal(exp_orientations,
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np.rad2deg(detector_extractor.orientations), 5)
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detector_extractor.detect_and_extract(img)
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assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
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assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
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def test_keypoints_orb_less_than_desired_no_of_keypoints():
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img = rgb2gray(lena())
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detector_extractor = ORB(n_keypoints=15, fast_n=12,
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fast_threshold=0.33, downscale=2, n_scales=2)
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detector_extractor.detect(img)
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exp_rows = np.array([ 67., 247., 269., 413., 435., 230., 264.,
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330., 372.])
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exp_cols = np.array([ 157., 146., 111., 70., 180., 136., 336.,
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148., 156.])
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exp_scales = np.array([ 1., 1., 1., 1., 1., 2., 2., 2., 2.])
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exp_orientations = np.array([-105.76503839, -96.28973044, -53.08162354,
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-173.4479964 , -175.64733392, -106.07927215,
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-163.40016243, 75.80865813, -154.73195911])
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exp_response = np.array([ 0.13197835, 0.24931321, 0.44351774,
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0.39063076, 0.96770745, 0.04935129,
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0.21431068, 0.15826555, 0.42403573])
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assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
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assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
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assert_almost_equal(exp_scales, detector_extractor.scales)
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assert_almost_equal(exp_response, detector_extractor.responses)
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assert_almost_equal(exp_orientations,
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np.rad2deg(detector_extractor.orientations), 5)
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detector_extractor.detect_and_extract(img)
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assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
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assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
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def test_descriptor_orb():
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detector_extractor = ORB(fast_n=12, fast_threshold=0.20)
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exp_descriptors = np.array([[ True, False, True, True, False, False, False, False, False, False],
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[False, False, True, True, False, True, True, False, True, True],
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[ True, False, False, False, True, False, True, True, True, False],
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[ True, False, False, True, False, True, True, False, False, False],
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[False, True, True, True, False, False, False, True, True, False],
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[False, False, False, False, False, True, False, True, True, True],
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[False, True, True, True, True, False, False, True, False, True],
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[ True, True, True, False, True, True, True, True, False, False],
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[ True, True, False, True, True, True, True, False, False, False],
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[ True, False, False, False, False, True, False, False, True, True],
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[ True, False, False, False, True, True, True, False, False, False],
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[False, False, True, False, True, False, False, True, False, False],
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[False, False, True, True, False, False, False, False, False, True],
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[ True, True, False, False, False, True, True, True, True, True],
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[ True, True, True, False, False, True, False, True, True, False],
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[False, True, True, False, False, True, True, True, True, True],
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[ True, True, True, False, False, False, False, True, True, True],
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[False, False, False, False, True, False, False, True, True, False],
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[False, True, False, False, True, False, False, False, True, True],
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[ True, False, True, False, False, False, True, True, False, False]], dtype=bool)
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detector_extractor.detect(img)
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detector_extractor.extract(img, detector_extractor.keypoints,
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detector_extractor.scales,
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detector_extractor.orientations)
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assert_array_equal(exp_descriptors,
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detector_extractor.descriptors[100:120, 10:20])
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detector_extractor.detect_and_extract(img)
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assert_array_equal(exp_descriptors,
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detector_extractor.descriptors[100:120, 10:20])
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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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