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ENH much faster.

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This commit is contained in:
Andreas Mueller
2012-08-03 11:37:10 +01:00
parent 58237a558a
commit 888d176034
1 changed files with 4 additions and 2 deletions
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skimage/segmentation/felzenszwalb.pyx
+4 -2
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@@ -78,10 +78,11 @@ def felzenszwalb_segmentation(image, k, sigma=0.8):
# and inner cost, then start greedy iteration over edges.
edge_queue = np.argsort(costs)
cdef np.int_t *segments_p = <np.int_t*>segments.data
cdef np.int_t seg_new
cdef np.ndarray[np.int_t, ndim=1] segment_size = np.ones(width * height, dtype=np.int)
# inner cost of segments
cint = defaultdict(lambda: 0)
cdef np.ndarray[np.float_t, ndim=1] cint = np.zeros(width * height)
cdef int seg0, seg1, seg_new
cdef float cost, inner_cost0, inner_cost1
for edge, cost in zip(edges[edge_queue], costs[edge_queue]):
seg0 = find_root(segments_p, edge[0])
seg1 = find_root(segments_p, edge[1])
@@ -100,3 +101,4 @@ def felzenszwalb_segmentation(image, k, sigma=0.8):
while (old != flat).any():
old = flat
flat = flat[flat]
return flat.reshape((width, height))