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Minor optimizations; Renaming variables; Docstring corrections

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This commit is contained in:
Ankit Agrawal
2013-11-29 20:46:30 +01:00
committed by Johannes Schönberger
parent 9e8979fe4d
commit 607d90cedf
3 changed files with 30 additions and 23 deletions
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skimage/feature/corner_cy.pyx
+4 -4
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@@ -31,8 +31,8 @@ def corner_moravec(image, Py_ssize_t window_size=1):
References
----------
..[1] http://kiwi.cs.dal.ca/~dparks/CornerDetection/moravec.htm
..[2] http://en.wikipedia.org/wiki/Corner_detection
.. [1] http://kiwi.cs.dal.ca/~dparks/CornerDetection/moravec.htm
.. [2] http://en.wikipedia.org/wiki/Corner_detection
Examples
--------
@@ -193,10 +193,10 @@ def corner_orientations(image, Py_ssize_t[:, :] corners, mask):
References
----------
..[1] Ethan Rublee, Vincent Rabaud, Kurt Konolige and Gary Bradski
.. [1] Ethan Rublee, Vincent Rabaud, Kurt Konolige and Gary Bradski
"ORB : An efficient alternative to SIFT and SURF"
http://www.vision.cs.chubu.ac.jp/CV-R/pdf/Rublee_iccv2011.pdf
..[2] Paul L. Rosin, "Measuring Corner Properties"
.. [2] Paul L. Rosin, "Measuring Corner Properties"
http://users.cs.cf.ac.uk/Paul.Rosin/corner2.pdf
Examples
skimage/feature/orb.py
+20 -14
View File
@@ -13,7 +13,7 @@ from .orb_cy import _orb_loop
def keypoints_orb(image, n_keypoints=200, fast_n=9, fast_threshold=0.20,
harris_k=0.05, downscale=np.sqrt(2), n_scales=5):
"""Compute Oriented Fast keypoints.
"""Detect Oriented Fast keypoints.
Parameters
----------
@@ -57,7 +57,7 @@ def keypoints_orb(image, n_keypoints=200, fast_n=9, fast_threshold=0.20,
References
----------
..[1] Ethan Rublee, Vincent Rabaud, Kurt Konolige and Gary Bradski
.. [1] Ethan Rublee, Vincent Rabaud, Kurt Konolige and Gary Bradski
"ORB : An efficient alternative to SIFT and SURF"
http://www.vision.cs.chubu.ac.jp/CV-R/pdf/Rublee_iccv2011.pdf
@@ -83,11 +83,14 @@ def keypoints_orb(image, n_keypoints=200, fast_n=9, fast_threshold=0.20,
for i in range(n_scales):
harris_response = corner_harris(pyramid[i], method='k', k=harris_k)
corners = corner_peaks(corner_fast(pyramid[i], fast_n, fast_threshold), min_distance=1)
corners = corner_peaks(corner_fast(pyramid[i], fast_n, fast_threshold),
min_distance=1)
keypoints_list.append(corners)
orientations_list.append(corner_orientations(pyramid[i], corners, ofast_mask))
scales_list.append(i * np.ones((corners.shape[0]), dtype=np.intp))
harris_measure_list.append(harris_response[corners[:, 0], corners[:, 1]])
orientations_list.append(corner_orientations(pyramid[i], corners,
ofast_mask))
scales_list.append(i * np.ones(corners.shape[0], dtype=np.intp))
harris_measure_list.append(harris_response[corners[:, 0],
corners[:, 1]])
keypoints = np.vstack(keypoints_list)
orientations = np.hstack(orientations_list)
@@ -98,7 +101,8 @@ def keypoints_orb(image, n_keypoints=200, fast_n=9, fast_threshold=0.20,
return keypoints, orientations, scales
else:
best_indices = harris_measure.argsort()[::-1][:n_keypoints]
return keypoints[best_indices], orientations[best_indices], scales[best_indices]
return keypoints[best_indices], orientations[best_indices], \
scales[best_indices]
def descriptor_orb(image, keypoints, orientations, scales,
@@ -134,7 +138,7 @@ def descriptor_orb(image, keypoints, orientations, scales,
References
----------
..[1] Ethan Rublee, Vincent Rabaud, Kurt Konolige and Gary Bradski
.. [1] Ethan Rublee, Vincent Rabaud, Kurt Konolige and Gary Bradski
"ORB : An efficient alternative to SIFT and SURF"
http://www.vision.cs.chubu.ac.jp/CV-R/pdf/Rublee_iccv2011.pdf
@@ -171,19 +175,21 @@ def descriptor_orb(image, keypoints, orientations, scales,
curr_scale_mask = scales == k
curr_scale_kpts = keypoints[curr_scale_mask]
curr_scale_kpts_orientation = orientations[curr_scale_mask]
curr_scale_orientation = orientations[curr_scale_mask]
border_mask = _mask_border_keypoints(curr_image, curr_scale_kpts, dist=13)
border_mask = _mask_border_keypoints(curr_image, curr_scale_kpts,
dist=13)
curr_scale_kpts = curr_scale_kpts[border_mask]
curr_scale_kpts_orientation = curr_scale_kpts_orientation[border_mask]
curr_scale_orientation = curr_scale_orientation[border_mask]
curr_scale_kpts = np.ascontiguousarray(curr_scale_kpts)
curr_scale_kpts_orientation = np.ascontiguousarray(curr_scale_kpts_orientation)
curr_scale_descriptors = _orb_loop(curr_image, curr_scale_kpts, curr_scale_kpts_orientation)
curr_scale_orientation = np.ascontiguousarray(curr_scale_orientation)
curr_scale_descriptors = _orb_loop(curr_image, curr_scale_kpts,
curr_scale_orientation)
descriptors_list.append(curr_scale_descriptors)
filtered_keypoints_list.append(curr_scale_kpts)
descriptors = np.vstack(descriptors_list).astype(np.bool)
descriptors = np.vstack(descriptors_list).view(np.bool)
filtered_keypoints = np.vstack(filtered_keypoints_list)
return descriptors, filtered_keypoints
skimage/feature/orb_cy.pyx
+6 -5
View File
@@ -17,7 +17,8 @@ def _orb_loop(double[:, ::1] image, Py_ssize_t[:, ::1] keypoints,
cdef char[:, ::1] pos1 = binary_tests[:, 2:]
cdef int[:, ::1] steered_pos0, steered_pos1
cdef double angle
cdef char[:, ::1] descriptors = np.zeros((keypoints.shape[0], 256), dtype=np.uint8)
cdef char[:, ::1] descriptors = np.zeros((keypoints.shape[0], 256),
dtype=np.uint8)
for i in range(keypoints.shape[0]):
angle = orientations[i]
@@ -28,10 +29,10 @@ def _orb_loop(double[:, ::1] image, Py_ssize_t[:, ::1] keypoints,
kc = keypoints[i, 1]
for j in range(256):
pr0 = pos0[j][0]
pc0 = pos0[j][1]
pr1 = pos1[j][0]
pc1 = pos1[j][1]
pr0 = pos0[j, 0]
pc0 = pos0[j, 1]
pr1 = pos1[j, 0]
pc1 = pos1[j, 1]
spr0 = <Py_ssize_t>round(sin_a * pr0 + cos_a * pc0)
spc0 = <Py_ssize_t>round(cos_a * pr0 - sin_a * pc0)