Final changes

skimage/feature/_brief.py

@@ -111,17 +111,17 @@ def brief(image, keypoints, descriptor_size=256, mode='normal', patch_size=49,
            [ 0.375    ,  0.6328125,  0.0390625,  0.328125 ],
            [ 0.625    ,  0.3671875,  0.34375  ,  0.0234375]])
     >>> match_keypoints_brief(keypoints1, descriptors1, keypoints2, descriptors2)
-    array([[[ 2.,  2.],
-            [ 2.,  2.]],
+    array([[[ 2,  2],
+            [ 2,  2]],
 
-           [[ 2.,  5.],
-            [ 2.,  6.]],
+           [[ 2,  5],
+            [ 2,  6]],
 
-           [[ 5.,  2.],
-            [ 6.,  2.]],
+           [[ 5,  2],
+            [ 6,  2]],
 
-           [[ 5.,  5.],
-            [ 6.,  6.]]])
+           [[ 5,  5],
+            [ 6,  6]]])
 
     """
     np.random.seed(sample_seed)
@@ -216,7 +216,7 @@ def match_keypoints_brief(keypoints1, descriptors1, keypoints2,
     temp = distance > threshold
     row_check = ~ np.all(temp, axis = 1)
     matched_keypoints2 = keypoints2[np.argmin(distance, axis=1)]
-    matched_keypoint_pairs = np.zeros((np.sum(row_check), 2, 2))
+    matched_keypoint_pairs = np.zeros((np.sum(row_check), 2, 2), dtype=np.intp)
     matched_keypoint_pairs[:, 0, :] = keypoints1[row_check]
     matched_keypoint_pairs[:, 1, :] = matched_keypoints2[row_check]
 

skimage/feature/tests/test_brief.py

@@ -8,10 +8,10 @@ from skimage.feature import brief, match_keypoints_brief
 
 
 def test_brief_color_image_unsupported_error():
-	"""Brief descriptors can be evaluated on gray-scale images only."""
-	img = np.zeros((20, 20, 3))
-	keypoints = [[7, 5], [11, 13]]
-	assert_raises(ValueError, brief, img, keypoints)
+    """Brief descriptors can be evaluated on gray-scale images only."""
+    img = np.zeros((20, 20, 3))
+    keypoints = [[7, 5], [11, 13]]
+    assert_raises(ValueError, brief, img, keypoints)
 
 
 def test_match_keypoints_brief_lena_translation():
@@ -56,22 +56,23 @@ def test_match_keypoints_brief_lena_rotation():
 	matched_keypoints = match_keypoints_brief(keypoints1, descriptors1,
 		                                      keypoints2, descriptors2,
 		                                      threshold=0.07)
-	expected = np.array([[[ 263.,  272.],
-                          [ 234.,  298.]],
+	expected = np.array([[[263, 272],
+                          [234, 298]],
 
-                         [[ 271.,  120.],
-                          [ 258.,  146.]],
+                         [[271, 120],
+                          [258, 146]],
 
-                         [[ 323.,  164.],
-                          [ 305.,  195.]],
+                         [[323, 164],
+                          [305, 195]],
 
-                         [[ 414.,   70.],
-                          [ 405.,  111.]],
+                         [[414,  70],
+                          [405, 111]],
 
-                         [[ 435.,  181.],
-                          [ 415.,  223.]],
+                         [[435, 181],
+                          [415, 223]],
+
+                         [[454, 176],
+                          [435, 221]]])
 
-                         [[ 454.,  176.],
-                          [ 435.,  221.]]])
 
 	assert_array_equal(matched_keypoints, expected)

skimage/feature/util.py

@@ -14,14 +14,14 @@ def _remove_border_keypoints(image, keypoints, dist):
 
 def pairwise_hamming_distance(array1, array2):
     """Calculate hamming dissimilarity measure between two sets of
-    boolean vectors.
+    vectors.
 
     Parameters
     ----------
-    array1 : (P1, D) array of dtype bool
-        P1 vectors of size D with boolean elements.
-    array2 : (P2, D) array of dtype bool
-        P2 vectors of size D with boolean elements.
+    array1 : (P1, D) array
+        P1 vectors of size D.
+    array2 : (P2, D) array
+        P2 vectors of size D.
 
     Returns
     -------