178 lines
4.7 KiB
Python
178 lines
4.7 KiB
Python
import numpy as np
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import pytest
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from skimage._shared._dependency_checks import has_mpl
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from skimage.feature.util import (
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FeatureDetector,
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DescriptorExtractor,
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_prepare_grayscale_input_2D,
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_mask_border_keypoints,
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plot_matches,
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plot_matched_features,
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)
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def test_feature_detector():
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with pytest.raises(NotImplementedError):
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FeatureDetector().detect(None)
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def test_descriptor_extractor():
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with pytest.raises(NotImplementedError):
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DescriptorExtractor().extract(None, None)
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def test_prepare_grayscale_input_2D():
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with pytest.raises(ValueError):
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_prepare_grayscale_input_2D(np.zeros((3, 3, 3)))
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with pytest.raises(ValueError):
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_prepare_grayscale_input_2D(np.zeros((3, 1)))
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with pytest.raises(ValueError):
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_prepare_grayscale_input_2D(np.zeros((3, 1, 1)))
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_prepare_grayscale_input_2D(np.zeros((3, 3)))
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_prepare_grayscale_input_2D(np.zeros((3, 3, 1)))
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_prepare_grayscale_input_2D(np.zeros((1, 3, 3)))
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def test_mask_border_keypoints():
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keypoints = np.array([[0, 0], [1, 1], [2, 2], [3, 3], [4, 4]])
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np.testing.assert_equal(
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_mask_border_keypoints((10, 10), keypoints, 0), [1, 1, 1, 1, 1]
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)
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np.testing.assert_equal(
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_mask_border_keypoints((10, 10), keypoints, 2), [0, 0, 1, 1, 1]
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)
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np.testing.assert_equal(
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_mask_border_keypoints((4, 4), keypoints, 2), [0, 0, 1, 0, 0]
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)
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np.testing.assert_equal(
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_mask_border_keypoints((10, 10), keypoints, 5), [0, 0, 0, 0, 0]
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)
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np.testing.assert_equal(
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_mask_border_keypoints((10, 10), keypoints, 4), [0, 0, 0, 0, 1]
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)
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@pytest.mark.skipif(not has_mpl, reason="Matplotlib not installed")
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@pytest.mark.parametrize(
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"shapes",
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[
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((10, 10), (10, 10)),
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((10, 10), (12, 10)),
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((10, 10), (10, 12)),
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((10, 10), (12, 12)),
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((12, 10), (10, 10)),
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((10, 12), (10, 10)),
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((12, 12), (10, 10)),
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],
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)
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def test_plot_matches(shapes):
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from matplotlib import pyplot as plt
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from matplotlib import use
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use('Agg')
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fig, ax = plt.subplots(nrows=1, ncols=1)
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keypoints1 = 10 * np.random.rand(10, 2)
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keypoints2 = 10 * np.random.rand(10, 2)
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idxs1 = np.random.randint(10, size=10)
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idxs2 = np.random.randint(10, size=10)
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matches = np.column_stack((idxs1, idxs2))
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shape1, shape2 = shapes
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img1 = np.zeros(shape1)
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img2 = np.zeros(shape2)
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with pytest.warns(FutureWarning):
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plot_matches(ax, img1, img2, keypoints1, keypoints2, matches)
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with pytest.warns(FutureWarning):
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plot_matches(ax, img1, img2, keypoints1, keypoints2, matches, only_matches=True)
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with pytest.warns(FutureWarning):
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plot_matches(
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ax, img1, img2, keypoints1, keypoints2, matches, keypoints_color='r'
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)
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with pytest.warns(FutureWarning):
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plot_matches(ax, img1, img2, keypoints1, keypoints2, matches, matches_color='r')
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with pytest.warns(FutureWarning):
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plot_matches(
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ax, img1, img2, keypoints1, keypoints2, matches, alignment='vertical'
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)
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plt.close()
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@pytest.mark.skipif(not has_mpl, reason="Matplotlib not installed")
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@pytest.mark.parametrize(
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"shapes",
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[
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((10, 10), (10, 10)),
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((10, 10), (12, 10)),
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((10, 10), (10, 12)),
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((10, 10), (12, 12)),
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((12, 10), (10, 10)),
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((10, 12), (10, 10)),
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((12, 12), (10, 10)),
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],
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)
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def test_plot_matched_features(shapes):
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from matplotlib import pyplot as plt
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from matplotlib import use
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use('Agg')
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fig, ax = plt.subplots()
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keypoints0 = 10 * np.random.rand(10, 2)
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keypoints1 = 10 * np.random.rand(10, 2)
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idxs0 = np.random.randint(10, size=10)
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idxs1 = np.random.randint(10, size=10)
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matches = np.column_stack((idxs0, idxs1))
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shape0, shape1 = shapes
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img0 = np.zeros(shape0)
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img1 = np.zeros(shape1)
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plot_matched_features(
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img0,
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img1,
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keypoints0=keypoints0,
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keypoints1=keypoints1,
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matches=matches,
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ax=ax,
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)
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plot_matched_features(
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img0,
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img1,
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ax=ax,
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keypoints0=keypoints0,
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keypoints1=keypoints1,
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matches=matches,
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only_matches=True,
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)
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plot_matched_features(
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img0,
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img1,
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ax=ax,
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keypoints0=keypoints0,
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keypoints1=keypoints1,
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matches=matches,
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keypoints_color='r',
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)
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plot_matched_features(
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img0,
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img1,
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ax=ax,
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keypoints0=keypoints0,
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keypoints1=keypoints1,
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matches=matches,
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matches_color='r',
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)
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plot_matched_features(
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img0,
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img1,
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ax=ax,
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keypoints0=keypoints0,
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keypoints1=keypoints1,
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matches=matches,
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alignment='vertical',
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)
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plt.close()
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