ENH using union find from morphology module

skimage/morphology/ccomp.pxd

@@ -0,0 +1,10 @@
+"""Export fast union find in Cython"""
+cimport numpy as np
+
+DTYPE = np.int
+ctypedef np.int_t DTYPE_t
+
+cdef DTYPE_t find_root(np.int_t *forest, np.int_t n)
+cdef set_root(np.int_t *forest, np.int_t n, np.int_t root)
+cdef join_trees(np.int_t *forest, np.int_t n, np.int_t m)
+cdef link_bg(np.int_t *forest, np.int_t n, np.int_t *background_node)

skimage/segmentation/felsenzwalb.pyx

@@ -1,4 +0,0 @@
-# Implements Felsenzwalb's efficient graph based image segmentation.
-# Author: Andreas Mueller
-
-def felsenzwalb(np.ndarray[dtype=

skimage/segmentation/felzenszwalb.pyx

@@ -1,10 +1,11 @@
 import numpy as np
+cimport numpy as np
 from collections import defaultdict
 import scipy
 
 #from ..util import img_as_float
 #from ..color import rgb2grey
-from .union_find import UnionFind
+from skimage.morphology.ccomp cimport find_root, join_trees
 
 from IPython.core.debugger import Tracer
 tracer = Tracer()
@@ -37,24 +38,23 @@ def felzenszwalb_segmentation(image, k, sigma=0.8):
     # initialize data structures for segment size
     # and inner cost, then start greedy iteration over edges.
     edge_queue = np.argsort(costs)
-    segments = UnionFind()
+    cdef np.ndarray[np.int_t, ndim=2] segments = indices.reshape(width, height)
+    cdef np.int_t *segments_p = <np.int_t*>segments.data
+    cdef np.int_t seg_new
     segment_size = defaultdict(lambda: 1)
     # inner cost of segments
     cint = defaultdict(lambda: 0)
     for edge, cost in zip(edges[edge_queue], costs[edge_queue]):
-        seg0 = segments[edge[0]]
-        seg1 = segments[edge[1]]
+        seg0 = find_root(segments_p, edge[0])
+        seg1 = find_root(segments_p, edge[1])
         if seg0 == seg1:
             continue
         inner_cost0 = cint[seg0] + k / segment_size[seg0]
         inner_cost1 = cint[seg1] + k / segment_size[seg1]
         if cost < min(inner_cost0, inner_cost1):
-            seg_new = segments.union(seg0, seg1)
             # update size and cost
+            join_trees(segments_p, seg0, seg1)
+            seg_new = find_root(segments_p, seg0)
             segment_size[seg_new] = segment_size[seg0] + segment_size[seg1]
             cint[seg_new] = cost
-    out = np.zeros(width * height, dtype=np.int)
-    for i in xrange(width * height):
-        out[i] = segments[i]
-    out = out.reshape(width, height)
-    return out
+    return segments

skimage/segmentation/setup.py

@@ -0,0 +1,27 @@
+#!/usr/bin/env python
+
+import os
+from skimage._build import cython
+
+base_path = os.path.abspath(os.path.dirname(__file__))
+
+def configuration(parent_package='', top_path=None):
+    from numpy.distutils.misc_util import Configuration, get_numpy_include_dirs
+
+    config = Configuration('segmentation', parent_package, top_path)
+
+    cython(['felzenszwalb.pyx'], working_path=base_path)
+    config.add_extension('felzenszwalb', sources=['felzenszwalb.c'],
+                         include_dirs=[get_numpy_include_dirs()])
+
+    return config
+
+if __name__ == '__main__':
+    from numpy.distutils.core import setup
+    setup(maintainer = 'scikits-image Developers',
+          maintainer_email = 'scikits-image@googlegroups.com',
+          description = 'Segmentation Algorithms',
+          url = 'https://github.com/scikits-image/scikits-image',
+          license = 'SciPy License (BSD Style)',
+          **(configuration(top_path='').todict())
+          )

skimage/setup.py

@@ -17,6 +17,7 @@ def configuration(parent_package='', top_path=None):
     config.add_subpackage('morphology')
     config.add_subpackage('transform')
     config.add_subpackage('util')
+    config.add_subpackage('segmentation')
 
     def add_test_directories(arg, dirname, fnames):
         if dirname.split(os.path.sep)[-1] == 'tests':