132 lines
5.9 KiB
Python
132 lines
5.9 KiB
Python
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import pytest
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import numpy as np
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from skimage._shared.testing import assert_equal, assert_almost_equal
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from skimage.feature import ORB
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from skimage._shared import testing
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from skimage import data
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from skimage._shared.testing import test_parallel, xfail, arch32
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from skimage.util.dtype import _convert
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img = data.coins()
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@test_parallel()
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@pytest.mark.parametrize('dtype', ['float32', 'float64', 'uint8',
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'uint16', 'int64'])
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def test_keypoints_orb_desired_no_of_keypoints(dtype):
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_img = _convert(img, dtype)
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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([141., 108., 214.56, 131., 214.272, 67.,
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206., 177., 108., 141.])
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exp_cols = np.array([323., 328., 282.24, 292., 281.664, 85.,
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260., 284., 328.8, 267.])
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exp_scales = np.array([1, 1, 1.44, 1, 1.728, 1, 1, 1, 1.2, 1])
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exp_orientations = np.array([-53.97446153, 59.5055285, -96.01885186,
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-149.70789506, -94.70171899, -45.76429535,
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-51.49752849, 113.57081195, 63.30428063,
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-79.56091118])
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exp_response = np.array([1.01168357, 0.82934145, 0.67784179, 0.57176438,
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0.56637459, 0.52248355, 0.43696175, 0.42992376,
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0.37700486, 0.36126832])
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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, 5)
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assert_almost_equal(exp_orientations,
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np.rad2deg(detector_extractor.orientations), 4)
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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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@pytest.mark.parametrize('dtype', ['float32', 'float64', 'uint8',
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'uint16', 'int64'])
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def test_keypoints_orb_less_than_desired_no_of_keypoints(dtype):
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_img = _convert(img, dtype)
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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([108., 203., 140., 65., 58.])
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exp_cols = np.array([293., 267., 202., 130., 291.])
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exp_scales = np.array([1., 1., 1., 1., 1.])
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exp_orientations = np.array([151.93906, -56.90052, -79.46341,
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-59.42996, -158.26941])
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exp_response = np.array([-0.1764169, 0.2652126, -0.0324343,
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0.0400902, 0.2667641])
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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), 3)
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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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@xfail(condition=arch32,
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reason=('Known test failure on 32-bit platforms. See links for '
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'details: '
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'https://github.com/scikit-image/scikit-image/issues/3091 '
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'https://github.com/scikit-image/scikit-image/issues/2529'))
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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([[0, 0, 0, 1, 0, 0, 0, 1, 0, 1],
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[1, 1, 0, 1, 0, 0, 0, 1, 0, 1],
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[1, 1, 0, 0, 1, 0, 0, 0, 1, 1],
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[1, 1, 1, 0, 0, 0, 1, 1, 1, 0],
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[0, 0, 0, 1, 0, 1, 1, 1, 1, 1],
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[1, 0, 0, 1, 1, 0, 0, 0, 1, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
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[1, 1, 1, 0, 1, 1, 1, 1, 0, 0],
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[1, 1, 1, 1, 0, 0, 0, 1, 1, 1],
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[0, 1, 1, 0, 0, 1, 1, 0, 1, 1],
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[1, 1, 0, 0, 0, 0, 0, 0, 1, 1],
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[1, 0, 0, 0, 0, 1, 0, 1, 1, 1],
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[1, 0, 1, 1, 1, 0, 1, 0, 1, 0],
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[0, 0, 1, 1, 0, 0, 0, 0, 1, 1],
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[0, 1, 1, 0, 0, 0, 1, 0, 0, 1],
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[0, 1, 1, 0, 0, 0, 1, 1, 1, 1],
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[0, 1, 1, 1, 1, 1, 1, 1, 1, 1],
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[0, 0, 1, 1, 1, 1, 0, 1, 1, 0],
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[0, 0, 1, 1, 1, 0, 1, 0, 0, 1],
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[0, 1, 0, 0, 0, 0, 0, 0, 1, 0]], 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_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_equal(exp_descriptors,
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detector_extractor.descriptors[100:120, 10:20])
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keypoints_count = detector_extractor.keypoints.shape[0]
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assert keypoints_count == detector_extractor.descriptors.shape[0]
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assert keypoints_count == detector_extractor.orientations.shape[0]
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assert keypoints_count == detector_extractor.responses.shape[0]
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assert keypoints_count == detector_extractor.scales.shape[0]
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def test_no_descriptors_extracted_orb():
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img = np.ones((128, 128))
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detector_extractor = ORB()
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with testing.raises(RuntimeError):
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detector_extractor.detect_and_extract(img)
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