def test_keypoints_orb_less_than_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=15, fast_n=12,
fast_threshold=0.33, downscale=2, n_scales=2)
detector_extractor.detect(img)
exp_rows = np.array([ 67., 247., 269., 413., 435., 230., 264.,
330., 372.])
exp_cols = np.array([ 157., 146., 111., 70., 180., 136., 336.,
148., 156.])
exp_scales = np.array([ 1., 1., 1., 1., 1., 2., 2., 2., 2.])
exp_orientations = np.array([-105.76503839, -96.28973044, -53.08162354,
-173.4479964 , -175.64733392, -106.07927215,
-163.40016243, 75.80865813, -154.73195911])
exp_response = np.array([ 0.13197835, 0.24931321, 0.44351774,
0.39063076, 0.96770745, 0.04935129,
0.21431068, 0.15826555, 0.42403573])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_descriptor_orb():
detector_extractor = ORB(fast_n=12, fast_threshold=0.20)
exp_descriptors = np.array([[ True, False, True, True, False, False, False, False, False, False],
[False, False, True, True, False, True, True, False, True, True],
[ True, False, False, False, True, False, True, True, True, False],
[ True, False, False, True, False, True, True, False, False, False],
[False, True, True, True, False, False, False, True, True, False],
[False, False, False, False, False, True, False, True, True, True],
[False, True, True, True, True, False, False, True, False, True],
[ True, True, True, False, True, True, True, True, False, False],
[ True, True, False, True, True, True, True, False, False, False],
[ True, False, False, False, False, True, False, False, True, True],
[ True, False, False, False, True, True, True, False, False, False],
[False, False, True, False, True, False, False, True, False, False],
[False, False, True, True, False, False, False, False, False, True],
[ True, True, False, False, False, True, True, True, True, True],
[ True, True, True, False, False, True, False, True, True, False],
[False, True, True, False, False, True, True, True, True, True],
[ True, True, True, False, False, False, False, True, True, True],
[False, False, False, False, True, False, False, True, True, False],
[False, True, False, False, True, False, False, False, True, True],
[ True, False, True, False, False, False, True, True, False, False]], dtype=bool)
detector_extractor.detect(img)
detector_extractor.extract(img, detector_extractor.keypoints,
detector_extractor.scales,
detector_extractor.orientations)
assert_equal(exp_descriptors,
detector_extractor.descriptors[100:120, 10:20])
detector_extractor.detect_and_extract(img)
assert_equal(exp_descriptors,
detector_extractor.descriptors[100:120, 10:20])
def test_keypoints_orb_less_than_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=15, fast_n=12,
fast_threshold=0.33, downscale=2, n_scales=2)
detector_extractor.detect(img)
exp_rows = np.array([ 58., 65., 108., 140., 203.])
exp_cols = np.array([ 291., 130., 293., 202., 267.])
exp_scales = np.array([1., 1., 1., 1., 1.])
exp_orientations = np.array([-158.26941428, -59.42996346, 151.93905955,
-79.46341354, -56.90052451])
exp_response = np.array([ 0.2667641 , 0.04009017, -0.17641695, -0.03243431,
0.26521259])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_keypoints_orb_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=10, fast_n=12, fast_threshold=0.20)
detector_extractor.detect(img)
exp_rows = np.array([ 435. , 435.6 , 376. , 455. , 434.88, 269. ,
375.6 , 310.8 , 413. , 311.04])
exp_cols = np.array([ 180. , 180. , 156. , 176. , 180. , 111. ,
156. , 172.8, 70. , 172.8])
exp_scales = np.array([ 1. , 1.2 , 1. , 1. , 1.44 , 1. ,
1.2 , 1.2 , 1. , 1.728])
exp_orientations = np.array([-175.64733392, -167.94842949, -148.98350192,
-142.03599837, -176.08535837, -53.08162354,
-150.89208271, 97.7693776 , -173.4479964 ,
38.66312042])
exp_response = np.array([ 0.96770745, 0.81027306, 0.72376257,
0.5626413 , 0.5097993 , 0.44351774,
0.39154173, 0.39084861, 0.39063076,
0.37602487])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_keypoints_orb_less_than_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=15,
fast_n=12,
fast_threshold=0.33,
downscale=2,
n_scales=2)
detector_extractor.detect(img)
exp_rows = np.array([58., 65., 108., 140., 203.])
exp_cols = np.array([291., 130., 293., 202., 267.])
exp_scales = np.array([1., 1., 1., 1., 1.])
exp_orientations = np.array([
-158.26941428, -59.42996346, 151.93905955, -79.46341354, -56.90052451
])
exp_response = np.array(
[0.2667641, 0.04009017, -0.17641695, -0.03243431, 0.26521259])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_keypoints_orb_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=10, fast_n=12, fast_threshold=0.20)
detector_extractor.detect(img)
exp_rows = np.array([ 141. , 108. , 214.56 , 131. , 214.272,
67. , 206. , 177. , 108. , 141. ])
exp_cols = np.array([ 323. , 328. , 282.24 , 292. , 281.664,
85. , 260. , 284. , 328.8 , 267. ])
exp_scales = np.array([1, 1, 1.44, 1, 1.728, 1, 1, 1, 1.2, 1])
exp_orientations = np.array([ -53.97446153, 59.5055285 , -96.01885186,
-149.70789506, -94.70171899, -45.76429535,
-51.49752849, 113.57081195, 63.30428063,
-79.56091118])
exp_response = np.array([ 1.01168357, 0.82934145, 0.67784179, 0.57176438,
0.56637459, 0.52248355, 0.43696175, 0.42992376,
0.37700486, 0.36126832])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_keypoints_orb_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=10, fast_n=12, fast_threshold=0.20)
detector_extractor.detect(img)
exp_rows = np.array(
[141., 108., 214.56, 131., 214.272, 67., 206., 177., 108., 141.])
exp_cols = np.array(
[323., 328., 282.24, 292., 281.664, 85., 260., 284., 328.8, 267.])
exp_scales = np.array(
[323., 328., 282.24, 292., 281.664, 85., 260., 284., 328.8, 267.])
exp_orientations = np.array([
-53.97446153, 59.5055285, -96.01885186, -149.70789506, -94.70171899,
-45.76429535, -51.49752849, 113.57081195, 63.30428063, -79.56091118
])
exp_response = np.array([
1.01168357, 0.82934145, 0.67784179, 0.57176438, 0.56637459, 0.52248355,
0.43696175, 0.42992376, 0.37700486, 0.36126832
])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_descriptor_orb():
detector_extractor = ORB(fast_n=12, fast_threshold=0.20)
exp_descriptors = np.array(
[[0, 1, 1, 1, 0, 1, 0, 1, 0, 1], [1, 1, 1, 0, 0, 1, 0, 0, 1, 1],
[1, 0, 1, 1, 0, 0, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 0, 0, 0, 1, 0], [1, 1, 0, 1, 1, 1, 0, 0, 1, 1],
[1, 1, 0, 1, 0, 0, 1, 0, 1, 1], [0, 0, 1, 0, 1, 0, 0, 1, 1, 0],
[1, 0, 0, 0, 1, 0, 0, 0, 0, 1], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 0, 1, 0, 1, 0, 0, 1, 1], [1, 1, 1, 0, 0, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 0, 1, 1, 1, 1, 0, 0],
[1, 1, 0, 0, 1, 0, 0, 1, 0, 1], [1, 1, 0, 0, 0, 0, 1, 0, 0, 1],
[0, 0, 0, 0, 1, 1, 1, 0, 1, 0], [0, 0, 0, 0, 1, 1, 1, 0, 0, 1],
[0, 0, 0, 0, 0, 1, 1, 0, 1, 1], [0, 0, 0, 0, 1, 0, 1, 0, 1, 1]],
dtype=bool)
detector_extractor.detect(img)
detector_extractor.extract(img, detector_extractor.keypoints,
detector_extractor.scales,
detector_extractor.orientations)
assert_equal(exp_descriptors, detector_extractor.descriptors[100:120,
10:20])
detector_extractor.detect_and_extract(img)
assert_equal(exp_descriptors, detector_extractor.descriptors[100:120,
10:20])
def test_keypoints_orb_less_than_desired_no_of_keypoints(dtype):
_img = _convert(img, dtype)
detector_extractor = ORB(n_keypoints=15,
fast_n=12,
fast_threshold=0.33,
downscale=2,
n_scales=2)
detector_extractor.detect(_img)
exp_rows = np.array([108., 203., 140., 65., 58.])
exp_cols = np.array([293., 267., 202., 130., 291.])
exp_scales = np.array([1., 1., 1., 1., 1.])
exp_orientations = np.array(
[151.93906, -56.90052, -79.46341, -59.42996, -158.26941])
exp_response = np.array(
[-0.1764169, 0.2652126, -0.0324343, 0.0400902, 0.2667641])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 3)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_keypoints_orb_less_than_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=15, fast_n=12,
fast_threshold=0.33, downscale=2, n_scales=2)
detector_extractor.detect(img)
exp_rows = np.array([ 67., 247., 269., 413., 435., 230., 264.,
330., 372.])
exp_cols = np.array([ 157., 146., 111., 70., 180., 136., 336.,
148., 156.])
exp_scales = np.array([ 1., 1., 1., 1., 1., 2., 2., 2., 2.])
exp_orientations = np.array([-105.76503839, -96.28973044, -53.08162354,
-173.4479964 , -175.64733392, -106.07927215,
-163.40016243, 75.80865813, -154.73195911])
exp_response = np.array([ 0.13197835, 0.24931321, 0.44351774,
0.39063076, 0.96770745, 0.04935129,
0.21431068, 0.15826555, 0.42403573])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
def test_keypoints_orb_desired_no_of_keypoints():
detector_extractor = ORB(n_keypoints=10, fast_n=12, fast_threshold=0.20)
detector_extractor.detect(img)
exp_rows = np.array([ 435. , 435.6 , 376. , 455. , 434.88, 269. ,
375.6 , 310.8 , 413. , 311.04])
exp_cols = np.array([ 180. , 180. , 156. , 176. , 180. , 111. ,
156. , 172.8, 70. , 172.8])
exp_scales = np.array([ 1. , 1.2 , 1. , 1. , 1.44 , 1. ,
1.2 , 1.2 , 1. , 1.728])
exp_orientations = np.array([-175.64733392, -167.94842949, -148.98350192,
-142.03599837, -176.08535837, -53.08162354,
-150.89208271, 97.7693776 , -173.4479964 ,
38.66312042])
exp_response = np.array([ 0.96770745, 0.81027306, 0.72376257,
0.5626413 , 0.5097993 , 0.44351774,
0.39154173, 0.39084861, 0.39063076,
0.37602487])
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
assert_almost_equal(exp_scales, detector_extractor.scales)
assert_almost_equal(exp_response, detector_extractor.responses)
assert_almost_equal(exp_orientations,
np.rad2deg(detector_extractor.orientations), 5)
detector_extractor.detect_and_extract(img)
assert_almost_equal(exp_rows, detector_extractor.keypoints[:, 0])
assert_almost_equal(exp_cols, detector_extractor.keypoints[:, 1])
