scikit-image

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import pytest
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import copy
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import numpy as np
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from skimage._shared.testing import assert_array_equal
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from skimage import data
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from skimage.feature import BRIEF, corner_peaks, corner_harris
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from skimage._shared import testing
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def test_color_image_unsupported_error():
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    """Brief descriptors can be evaluated on gray-scale images only."""
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    img = np.zeros((20, 20, 3))
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    keypoints = np.asarray([[7, 5], [11, 13]])
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    with testing.raises(ValueError):
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        BRIEF().extract(img, keypoints)
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@pytest.mark.parametrize('dtype', ['float32', 'float64', 'uint8', 'int'])
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def test_normal_mode(dtype):
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    """Verify the computed BRIEF descriptors with expected for normal mode."""
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    img = data.coins().astype(dtype)
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    keypoints = corner_peaks(
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        corner_harris(img), min_distance=5, threshold_abs=0, threshold_rel=0.1
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    )
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    extractor = BRIEF(descriptor_size=8, sigma=2)
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    extractor.extract(img, keypoints[:8])
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    expected = np.array(
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        [
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            [1, 1, 1, 0, 1, 1, 0, 1],
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            [0, 1, 1, 0, 1, 1, 0, 0],
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            [1, 1, 1, 0, 1, 1, 0, 1],
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            [0, 0, 0, 1, 0, 0, 1, 0],
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            [0, 1, 1, 0, 1, 1, 0, 0],
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            [0, 1, 1, 0, 1, 1, 1, 0],
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            [1, 1, 1, 0, 1, 1, 0, 1],
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            [1, 0, 1, 0, 0, 1, 1, 0],
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        ],
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        dtype=bool,
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    )
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    assert_array_equal(extractor.descriptors, expected)
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@pytest.mark.parametrize('dtype', ['float32', 'float64', 'uint8', 'int'])
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def test_uniform_mode(dtype):
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    """Verify the computed BRIEF descriptors with expected for uniform mode."""
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    img = data.coins().astype(dtype)
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    keypoints = corner_peaks(
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        corner_harris(img), min_distance=5, threshold_abs=0, threshold_rel=0.1
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    )
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    extractor = BRIEF(descriptor_size=8, sigma=2, mode='uniform', rng=1)
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    BRIEF(descriptor_size=8, sigma=2, mode='uniform', rng=1)
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    extractor.extract(img, keypoints[:8])
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    expected = np.array(
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        [
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            [0, 1, 0, 1, 0, 1, 1, 0],
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            [0, 1, 0, 0, 0, 1, 0, 1],
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            [0, 1, 0, 0, 0, 1, 1, 1],
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            [1, 0, 1, 0, 1, 0, 1, 1],
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            [0, 0, 1, 0, 0, 1, 0, 1],
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            [0, 1, 0, 1, 0, 1, 0, 1],
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            [0, 1, 0, 0, 0, 1, 1, 1],
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            [1, 0, 1, 1, 1, 0, 0, 1],
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        ],
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        dtype=bool,
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    )
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    assert_array_equal(extractor.descriptors, expected)
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def test_unsupported_mode():
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    with testing.raises(ValueError):
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        BRIEF(mode='foobar')
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@pytest.mark.parametrize('dtype', ['float32', 'float64', 'uint8', 'int'])
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def test_border(dtype):
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    img = np.zeros((100, 100), dtype=dtype)
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    keypoints = np.array([[1, 1], [20, 20], [50, 50], [80, 80]])
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    extractor = BRIEF(patch_size=41, rng=1)
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    extractor.extract(img, keypoints)
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    assert extractor.descriptors.shape[0] == 3
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    assert_array_equal(extractor.mask, (False, True, True, True))
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def test_independent_rng():
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    img = np.zeros((100, 100), dtype=int)
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    keypoints = np.array([[1, 1], [20, 20], [50, 50], [80, 80]])
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    rng = np.random.default_rng()
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    extractor = BRIEF(patch_size=41, rng=rng)
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    x = copy.deepcopy(extractor.rng).random()
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    rng.random()
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    extractor.extract(img, keypoints)
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    z = copy.deepcopy(extractor.rng).random()
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    assert x == z
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