mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-14 11:18:06 +08:00
Tony S Yu
2a00e24b12
Template and image in test are converted to float32 before passing to `match_template`. This change is temporary: `match_template` should convert these variables internally.
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import numpy as np
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from skimage.feature import match_template
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from numpy.random import randn
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def test_template():
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size = 100
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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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found_positions = []
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# find the targets
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for i in range(50):
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index = np.argmax(result)
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y, x = np.unravel_index(index, result.shape)
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if not found_positions:
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found_positions.append((x, y))
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for position in found_positions:
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distance = np.sqrt((x - position[0]) ** 2 +
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(y - position[1]) ** 2)
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if distance > delta:
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found_positions.append((x, y))
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result[y, x] = 0
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if len(found_positions) == len(target_positions):
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break
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for x, y in target_positions:
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print x, y
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found = False
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for position in found_positions:
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distance = np.sqrt((x - position[0]) ** 2 +
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(y - position[1]) ** 2)
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if distance < delta:
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found = True
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assert found
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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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