several fixes and 3 new tests for Histograms of Oriented Gradients

CONTRIBUTORS.txt

@@ -108,3 +108,6 @@
   Adaptive thresholding
   Implementation of Matlab's `regionprops`
   Estimation of geometric transformation parameters
+  
+- Pavel Campr
+  Fixes and tests for Histograms of Oriented Gradients.

skimage/feature/_hog.py

@@ -181,4 +181,4 @@ def hog(image, orientations=9, pixels_per_cell=(8, 8),
     if visualise:
         return normalised_blocks.ravel(), hog_image
     else:
-        return normalised_blocks.ravel()
+        return normalised_blocks.ravel()

skimage/feature/tests/test_hog.py

@@ -32,8 +32,6 @@ def test_hog_basic_orientations_and_data_types():
     #  4) verify that all results are equal where expected
     #  5) verify that computed feature vector is as expected
     #  6) repeat the scenario for 90, 180 and 270 degrees rotated images
-    #
-    # author: Pavel Campr
 
     # size of testing image
     width = height = 35
@@ -99,8 +97,6 @@ def test_hog_orientations_circle():
     #  3) verify that the resulting feature vector contains uniformly distributed values for all orientations,
     #     i.e. no orientation is lost or emphasized
     #  4) repeat the scenario for other 'orientations' option
-    #
-    # author: Pavel Campr
 
     # size of testing image
     width = height = 100