Rename corner operators and file

skimage/feature/__init__.py

@@ -1,6 +1,6 @@
 from ._hog import hog
 from .texture import greycomatrix, greycoprops, local_binary_pattern
 from .peak import peak_local_max
-from .interest import harris, shi_tomasi
-from .interest_cy import moravec
+from .corner import corner_harris, corner_shi_tomasi
+from .corner_cy import corner_moravec
 from .template import match_template

skimage/feature/corner.py

@@ -40,7 +40,7 @@ def _compute_auto_correlation(image, sigma):
     return Axx, Axy, Ayy
 
 
-def harris(image, method='k', k=0.05, eps=1e-6, sigma=1):
+def corner_harris(image, method='k', k=0.05, eps=1e-6, sigma=1):
     """Compute Harris response image.
 
     This corner detector uses information in the auto-correlation matrix
@@ -110,7 +110,7 @@ def harris(image, method='k', k=0.05, eps=1e-6, sigma=1):
     return response
 
 
-def shi_tomasi(image, sigma=1):
+def corner_shi_tomasi(image, sigma=1):
     """Compute Shi-Tomasi (Kanade-Tomasi) response image.
 
     This corner detector uses information in the auto-correlation matrix

skimage/feature/corner_cy.pyx

@@ -10,7 +10,7 @@ from skimage.color import rgb2grey
 from skimage.util import img_as_float
 
 
-def moravec(image, int window_size=1):
+def corner_moravec(image, int window_size=1):
     """Compute Moravec response image.
 
     This interest operator is comparatively fast but not rotation invariant.

skimage/feature/setup.py

@@ -12,11 +12,11 @@ def configuration(parent_package='', top_path=None):
     config = Configuration('feature', parent_package, top_path)
     config.add_data_dir('tests')
 
-    cython(['interest_cy.pyx'], working_path=base_path)
+    cython(['corner_cy.pyx'], working_path=base_path)
     cython(['_texture.pyx'], working_path=base_path)
     cython(['_template.pyx'], working_path=base_path)
 
-    config.add_extension('interest_cy', sources=['interest_cy.c'],
+    config.add_extension('corner_cy', sources=['corner_cy.c'],
                          include_dirs=[get_numpy_include_dirs()])
     config.add_extension('_texture', sources=['_texture.c'],
                          include_dirs=[get_numpy_include_dirs(), '../_shared'])

skimage/feature/tests/test_corner.py

@@ -3,7 +3,8 @@ import numpy as np
 from skimage import data
 from skimage import img_as_float
 
-from skimage.feature import moravec, harris, shi_tomasi, peak_local_max
+from skimage.feature import (corner_moravec, corner_harris, corner_shi_tomasi,
+                             peak_local_max)
 
 
 def test_square_image():
@@ -11,17 +12,17 @@ def test_square_image():
     im[:25, :25] = 1.
 
     # Moravec
-    results = peak_local_max(moravec(im))
+    results = peak_local_max(corner_moravec(im))
     # interest points along edge
     assert len(results) == 57
 
     # Harris
-    results = peak_local_max(harris(im))
+    results = peak_local_max(corner_harris(im))
     # interest at corner
     assert len(results) == 1
 
     # Shi-Tomasi
-    results = peak_local_max(shi_tomasi(im))
+    results = peak_local_max(corner_shi_tomasi(im))
     # interest at corner
     assert len(results) == 1
 
@@ -32,16 +33,16 @@ def test_noisy_square_image():
     im = im + np.random.uniform(size=im.shape) * .2
 
     # Moravec
-    results = peak_local_max(moravec(im))
+    results = peak_local_max(corner_moravec(im))
     # undefined number of interest points
     assert results.any()
 
     # Harris
-    results = peak_local_max(harris(im, sigma=1.5))
+    results = peak_local_max(corner_harris(im, sigma=1.5))
     assert len(results) == 1
 
     # Shi-Tomasi
-    results = peak_local_max(shi_tomasi(im, sigma=1.5))
+    results = peak_local_max(corner_shi_tomasi(im, sigma=1.5))
     assert len(results) == 1
 
 
@@ -53,11 +54,11 @@ def test_squared_dot():
     # Moravec fails
 
     # Harris
-    results = peak_local_max(harris(im))
+    results = peak_local_max(corner_harris(im))
     assert (results == np.array([[6, 6]])).all()
 
     # Shi-Tomasi
-    results = peak_local_max(shi_tomasi(im))
+    results = peak_local_max(corner_shi_tomasi(im))
     assert (results == np.array([[6, 6]])).all()
 
 
@@ -70,20 +71,20 @@ def test_rotated_lena():
     im_rotated = im.T
 
     # Moravec
-    results = peak_local_max(moravec(im))
-    results_rotated = peak_local_max(moravec(im_rotated))
+    results = peak_local_max(corner_moravec(im))
+    results_rotated = peak_local_max(corner_moravec(im_rotated))
     assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
     assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
 
     # Harris
-    results = peak_local_max(harris(im))
-    results_rotated = peak_local_max(harris(im_rotated))
+    results = peak_local_max(corner_harris(im))
+    results_rotated = peak_local_max(corner_harris(im_rotated))
     assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
     assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()
 
     # Shi-Tomasi
-    results = peak_local_max(shi_tomasi(im))
-    results_rotated = peak_local_max(shi_tomasi(im_rotated))
+    results = peak_local_max(corner_shi_tomasi(im))
+    results_rotated = peak_local_max(corner_shi_tomasi(im_rotated))
     assert (np.sort(results[:, 0]) == np.sort(results_rotated[:, 1])).all()
     assert (np.sort(results[:, 1]) == np.sort(results_rotated[:, 0])).all()