Introducing the _prepare_grayscale_input_2D function in feature.util

skimage/feature/_brief.py

@@ -1,8 +1,8 @@
 import numpy as np
 from scipy.ndimage.filters import gaussian_filter
 
-from ..util import img_as_float
-from .util import _mask_border_keypoints, pairwise_hamming_distance
+from .util import (_mask_border_keypoints, pairwise_hamming_distance,
+                _prepare_grayscale_input_2D)
 
 from ._brief_cy import _brief_loop
 
@@ -129,11 +129,7 @@ def brief(image, keypoints, descriptor_size=256, mode='normal', patch_size=49,
 
     np.random.seed(sample_seed)
 
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
-
-    image = img_as_float(image)
+    image = _prepare_grayscale_input_2D(image)
 
     # Gaussian Low pass filtering to alleviate noise
     # sensitivity

skimage/feature/censure.py

@@ -1,9 +1,10 @@
 import numpy as np
 from scipy.ndimage.filters import maximum_filter, minimum_filter, convolve
 
+from .util import _prepare_grayscale_input_2D
+
 from skimage.transform import integral_image
 from skimage.feature import structure_tensor
-from skimage.util import img_as_float
 from skimage.morphology import octagon, star
 from skimage.feature.util import _mask_border_keypoints
 
@@ -175,9 +176,7 @@ def keypoints_censure(image, min_scale=1, max_scale=7, mode='DoB',
     # (4) Finally, we remove the border keypoints and return the keypoints
     # along with its corresponding scale.
 
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
     mode = mode.lower()
     if mode not in ('dob', 'octagon', 'star'):
@@ -187,7 +186,6 @@ def keypoints_censure(image, min_scale=1, max_scale=7, mode='DoB',
         raise ValueError('The scales must be >= 1 and the number of scales '
                          'should be >= 3.')
 
-    image = img_as_float(image)
     image = np.ascontiguousarray(image)
 
     # Generating all the scales

skimage/feature/corner.py

@@ -5,6 +5,8 @@ from skimage.color import rgb2grey
 from skimage.util import img_as_float, pad
 from skimage.feature import peak_local_max
 
+from .util import _prepare_grayscale_input_2D
+
 from corner_cy import _corner_fast
 
 
@@ -84,9 +86,7 @@ def structure_tensor(image, sigma=1, mode='constant', cval=0):
 
     """
 
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
     imx, imy = _compute_derivatives(image, mode=mode, cval=cval)
 
@@ -146,9 +146,7 @@ def hessian_matrix(image, sigma=1, mode='constant', cval=0):
 
     """
 
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
     # window extent to the left and right, which covers > 99% of the normal
     # distribution
@@ -576,11 +574,8 @@ def corner_fast(image, n=12, threshold=0.15):
            [8, 8]])
 
     """
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
-    image = img_as_float(image)
     image = np.ascontiguousarray(image)
     response = _corner_fast(image, n, threshold)
     return response

skimage/feature/corner_cy.pyx

@@ -8,7 +8,8 @@ from libc.float cimport DBL_MAX
 from libc.math cimport atan2
 
 from skimage.color import rgb2grey
-from skimage.util import img_as_float
+
+from .util import _prepare_grayscale_input_2D
 
 
 def corner_moravec(image, Py_ssize_t window_size=1):
@@ -231,14 +232,12 @@ def corner_orientations(image, Py_ssize_t[:, :] corners, mask):
 
     """
 
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
     if mask.shape[0] % 2 != 1 or mask.shape[1] % 2 != 1:
         raise ValueError("Size of mask must be uneven.")
 
-    cdef double[:, :] cimage = img_as_float(image)
+    cdef double[:, :] cimage = image
     cdef char[:, ::1] cmask = np.ascontiguousarray(mask != 0, dtype=np.uint8)
 
     cdef Py_ssize_t i, r, c, r0, c0

skimage/feature/orb.py

@@ -1,7 +1,6 @@
 import numpy as np
 
-from ..util import img_as_float
-from .util import _mask_border_keypoints
+from .util import _mask_border_keypoints, _prepare_grayscale_input_2D
 
 from skimage.feature import (corner_fast, corner_orientations, corner_peaks,
                              corner_harris)
@@ -85,9 +84,7 @@ def keypoints_orb(image, n_keypoints=200, fast_n=9, fast_threshold=0.20,
     array([0, 0, 0, 0, 1, 1, 1, 1])
 
     """
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
     pyramid = list(pyramid_gaussian(image, n_scales - 1, downscale))
 
@@ -184,9 +181,7 @@ def descriptor_orb(image, keypoints, orientations, scales,
     (8, 256)
 
     """
-    image = np.squeeze(image)
-    if image.ndim != 2:
-        raise ValueError("Only 2-D gray-scale images supported.")
+    image = _prepare_grayscale_input_2D(image)
 
     image = img_as_float(image)
 

skimage/feature/util.py

@@ -1,3 +1,14 @@
+import numpy as np
+
+from ..util import img_as_float
+
+
+def _prepare_grayscale_input_2D(image):
+    image = np.squeeze(image)
+    if image.ndim != 2:
+        raise ValueError("Only 2-D gray-scale images supported.")
+
+    return img_as_float(image)
 
 
 def _mask_border_keypoints(image, keypoints, dist):