mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 14:56:02 +08:00
Johannes Schönberger
94 lines
2.4 KiB
Python
94 lines
2.4 KiB
Python
import numpy as np
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from skimage import data
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from skimage import img_as_float
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from skimage.feature import moravec, harris, shi_tomasi, peak_local_max
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def test_square_image():
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im = np.zeros((50, 50)).astype(float)
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im[:25, :25] = 1.
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# Moravec
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results = peak_local_max(moravec(im))
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# interest points along edge
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assert len(results) == 57
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# Harris
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results = peak_local_max(harris(im))
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# interest at corner
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assert len(results) == 1
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# Shi-Tomasi
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results = peak_local_max(shi_tomasi(im))
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# interest at corner
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assert len(results) == 1
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def test_noisy_square_image():
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im = np.zeros((50, 50)).astype(float)
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im[:25, :25] = 1.
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im = im + np.random.uniform(size=im.shape) * .2
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# Moravec
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results = peak_local_max(moravec(im))
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# undefined number of interest points
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assert results.any()
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# Harris
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results = peak_local_max(harris(im, sigma=1.5))
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assert len(results) == 1
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# Shi-Tomasi
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results = peak_local_max(shi_tomasi(im, sigma=1.5))
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assert len(results) == 1
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def test_squared_dot():
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im = np.zeros((50, 50))
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im[4:8, 4:8] = 1
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im = img_as_float(im)
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# Moravec fails
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# Harris
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results = peak_local_max(harris(im))
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assert (results == np.array([[6, 6]])).all()
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# Shi-Tomasi
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results = peak_local_max(shi_tomasi(im))
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assert (results == np.array([[6, 6]])).all()
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def test_rotated_lena():
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"""
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The harris filter should yield the same results with an image and it's
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rotation.
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"""
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im = img_as_float(data.lena().mean(axis=2))
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im_rotated = im.T
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# Moravec
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results = peak_local_max(moravec(im))
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results_rotated = peak_local_max(moravec(im_rotated))
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assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
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assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
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# Harris
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results = peak_local_max(harris(im))
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results_rotated = peak_local_max(harris(im_rotated))
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assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
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assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
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# Shi-Tomasi
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results = peak_local_max(shi_tomasi(im))
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results_rotated = peak_local_max(shi_tomasi(im_rotated))
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assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
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assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
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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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