mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-03 20:40:03 +08:00
Tony S Yu
42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
import numpy as np
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from numpy.random import randn
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from numpy.testing import assert_array_almost_equal as assert_close
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from skimage.feature import match_template, peak_local_max
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def test_template():
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size = 100
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# Type conversion of image and target not required but prevents warnings.
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image = np.zeros((400, 400), dtype=np.float32)
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target = np.tri(size) + np.tri(size)[::-1]
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target = target.astype(np.float32)
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target_positions = [(50, 50), (200, 200)]
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for x, y in target_positions:
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image[x:x + size, y:y + size] = target
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image += randn(400, 400) * 2
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for method in ["norm-corr", "norm-coeff"]:
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result = match_template(image, target, method=method)
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delta = 5
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positions = peak_local_max(result, min_distance=delta)
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if len(positions) > 2:
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# Keep the two maximum peaks.
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intensities = result[tuple(positions.T)]
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i_maxsort = np.argsort(intensities)[::-1]
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positions = positions[i_maxsort][:2]
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# Sort so that order matches `target_positions`.
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positions = positions[np.argsort(positions[:, 0])]
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for xy_target, xy in zip(target_positions, positions):
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yield assert_close, xy, xy_target
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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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