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Reduce to one threshold paramater

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Johannes Schönberger
2012-11-01 15:01:14 +01:00
parent 5be7f62813
commit 531060ec20
1 changed files with 5 additions and 6 deletions
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skimage/transform/hough_transform.py
+5 -6
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@@ -139,7 +139,7 @@ def hough(img, theta=None):
def hough_peaks(hspace, angles, dists, min_distance=10, min_angle=10,
threshold_abs=0, threshold_rel=0.5, num_peaks=np.inf):
threshold=None, num_peaks=np.inf):
"""Return peaks in hough transform.
Identifies most prominent lines separated by a certain angle and distance in
@@ -162,10 +162,8 @@ def hough_peaks(hspace, angles, dists, min_distance=10, min_angle=10,
min_angle : int
Minimum angle separating lines (maximum filter size for second
dimension of hough space).
threshold_abs : float
Minimum intensity of peaks in hough space.
threshold_rel : float
Minimum intensity of peaks calculated as `max(hspace) * threshold_rel`.
threshold : float
Minimum intensity of peaks calculated as `0.5 * max(hspace)`.
num_peaks : int
Maximum number of peaks. When the number of peaks exceeds `num_peaks`,
return `num_peaks` coordinates based on peak intensity.
@@ -197,7 +195,8 @@ def hough_peaks(hspace, angles, dists, min_distance=10, min_angle=10,
hspace = hspace.copy()
rows, cols = hspace.shape
threshold = max(threshold_abs, threshold_rel * np.max(hspace))
if threshold is None:
threshold = 0.5 * np.max(hspace)
distance_size = 2 * min_distance + 1
angle_size = 2 * min_angle + 1