mirror of
https://github.com/wassname/scikit-image.git
synced 2026-08-04 13:14:23 +08:00
Writing better Cython code
This commit is contained in:
Ankit Agrawal
committed by
Johannes Schönberger
Johannes Schönberger
parent
914ab05fb6
commit
0bbc1d7933
@@ -261,9 +261,9 @@ def corner_orientations(image, Py_ssize_t[:, :] corners, mask):
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for c in range(mcols):
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if cmask[r, c]:
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curr_pixel = cimage[r0 + r, c0 + c]
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m01 += curr_pixel * (c - mcols2)
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m10 += curr_pixel * (r - mrows2)
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m10 += curr_pixel * (c - mcols2)
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m01 += curr_pixel * (r - mrows2)
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orientations[i] = atan2(m10, m01)
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orientations[i] = atan2(m01, m10)
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return np.asarray(orientations)
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@@ -147,12 +147,6 @@ def descriptor_orb(image, keypoints, orientations, scales,
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pyramid = list(pyramid_gaussian(image, n_scales - 1, downscale))
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pos0 = binary_tests[:, :2].astype(np.int32)
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pos1 = binary_tests[:, 2:].astype(np.int32)
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pos0 = np.ascontiguousarray(pos0)
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pos1 = np.ascontiguousarray(pos1)
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descriptors = np.empty((0, 256), dtype=np.bool)
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for k in range(n_scales):
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@@ -166,10 +160,10 @@ def descriptor_orb(image, keypoints, orientations, scales,
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curr_scale_kpts = curr_scale_kpts[border_mask]
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curr_scale_kpts_orientation = curr_scale_kpts_orientation[border_mask]
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curr_scale_descriptors = np.zeros((curr_scale_kpts.shape[0], 256), dtype=np.bool, order='C')
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curr_scale_descriptors = np.zeros((curr_scale_kpts.shape[0], 256), dtype=np.bool)
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curr_scale_kpts = np.ascontiguousarray(curr_scale_kpts)
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curr_scale_kpts_orientation = np.ascontiguousarray(curr_scale_kpts_orientation)
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_orb_loop(curr_image, curr_scale_descriptors.view(np.uint8), curr_scale_kpts, curr_scale_kpts_orientation, pos0, pos1)
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_orb_loop(curr_image, curr_scale_descriptors.view(np.uint8), curr_scale_kpts, curr_scale_kpts_orientation)
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descriptors = np.vstack((descriptors, curr_scale_descriptors))
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filtered_keypoints = np.vstack((filtered_keypoints, curr_scale_kpts))
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+281
-14
@@ -4,30 +4,297 @@
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#cython: wraparound=False
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cimport numpy as cnp
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import numpy as np
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from libc.math cimport sin, cos, M_PI, round
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def _orb_loop(double[:, ::1] image, char[:, ::1] descriptors, Py_ssize_t[:, ::1] keypoints,
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double[:] orientations, int[:, ::1] pos0, int[:, ::1] pos1):
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double[:] orientations):
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cdef Py_ssize_t i, d, kr, kc, pr0, pr1, pc0, pc1
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cdef Py_ssize_t i, d, kr, kc, pr0, pr1, pc0, pc1, spr0, spc0, spr1, spc1
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cdef char[:, ::1] pos0 = binary_tests[:, :2]
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cdef char[:, ::1] pos1 = binary_tests[:, 2:]
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cdef int[:, ::1] steered_pos0, steered_pos1
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cdef double angle
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for i in range(keypoints.shape[0]):
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angle = orientations[i]
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a = np.sin(angle * np.pi / 180.)
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b = np.cos(angle * np.pi / 180.)
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rotation_matrix = np.asarray([[b, a], [-a, b]])
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steered_pos0 = np.dot(pos0, rotation_matrix).astype(np.int32)
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steered_pos1 = np.dot(pos1, rotation_matrix).astype(np.int32)
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sin_a = sin(angle * M_PI / 180.)
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cos_a = cos(angle * M_PI / 180.)
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kr = keypoints[i, 0]
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kc = keypoints[i, 1]
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for j in range(256):
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pr0 = steered_pos0[j][0]
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pc0 = steered_pos0[j][1]
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pr1 = steered_pos1[j][0]
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pc1 = steered_pos1[j][1]
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if image[kr + pr0, kc + pc0] < image[kr + pr1, kc + pc1]:
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for j in range(256):
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pr0 = pos0[j][0]
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pc0 = pos0[j][1]
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pr1 = pos1[j][0]
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pc1 = pos1[j][1]
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spr0 = <Py_ssize_t>round(sin_a * pr0 + cos_a * pc0)
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spc0 = <Py_ssize_t>round(cos_a * pr0 - sin_a * pc0)
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spr1 = <Py_ssize_t>round(sin_a * pr1 + cos_a * pc1)
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spc1 = <Py_ssize_t>round(cos_a * pr1 - sin_a * pc1)
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if image[kr + spr0, kc + spc0] < image[kr + spr1, kc + spc1]:
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descriptors[i, j] = True
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# Learned 256 decision pairs for binary tests in rBRIEF. Taken from OpenCV.
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cdef char[:, ::1] binary_tests = np.ascontiguousarray(np.asarray([[8,-3, 9,5],
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[4,2, 7,-12],
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[-11,9, -8,2],
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[7,-12, 12,-13],
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[2,-13, 2,12],
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[1,-7, 1,6],
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[-2,-10, -2,-4],
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[-13,-13, -11,-8],
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[-13,-3, -12,-9],
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[10,4, 11,9],
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[-13,-8, -8,-9],
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[-11,7, -9,12],
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[7,7, 12,6],
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[-4,-5, -3,0],
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[-13,2, -12,-3],
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[-9,0, -7,5],
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[12,-6, 12,-1],
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[-3,6, -2,12],
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[-6,-13, -4,-8],
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[11,-13, 12,-8],
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[4,7, 5,1],
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[5,-3, 10,-3],
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[3,-7, 6,12],
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[-8,-7, -6,-2],
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[-2,11, -1,-10],
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[-13,12, -8,10],
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[-7,3, -5,-3],
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[-4,2, -3,7],
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[-10,-12, -6,11],
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[5,-12, 6,-7],
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[5,-6, 7,-1],
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[1,0, 4,-5],
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[9,11, 11,-13],
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[4,7, 4,12],
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[2,-1, 4,4],
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[-4,-12, -2,7],
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[-8,-5, -7,-10],
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[4,11, 9,12],
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[0,-8, 1,-13],
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[-13,-2, -8,2],
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[-3,-2, -2,3],
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[-6,9, -4,-9],
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[8,12, 10,7],
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[0,9, 1,3],
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[7,-5, 11,-10],
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[-13,-6, -11,0],
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[10,7, 12,1],
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[-6,-3, -6,12],
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[10,-9, 12,-4],
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[-13,8, -8,-12],
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[-13,0, -8,-4],
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[3,3, 7,8],
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[5,7, 10,-7],
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[-1,7, 1,-12],
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[3,-10, 5,6],
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[2,-4, 3,-10],
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[-13,0, -13,5],
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[-13,-7, -12,12],
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[-13,3, -11,8],
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[-7,12, -4,7],
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[6,-10, 12,8],
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[-9,-1, -7,-6],
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[-2,-5, 0,12],
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[-12,5, -7,5],
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[3,-10, 8,-13],
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[-7,-7, -4,5],
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[-3,-2, -1,-7],
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[2,9, 5,-11],
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[-11,-13, -5,-13],
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[-1,6, 0,-1],
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[5,-3, 5,2],
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[-4,-13, -4,12],
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[-9,-6, -9,6],
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[-12,-10, -8,-4],
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[10,2, 12,-3],
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[7,12, 12,12],
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[-7,-13, -6,5],
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[-4,9, -3,4],
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[7,-1, 12,2],
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[-7,6, -5,1],
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[-13,11, -12,5],
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[-3,7, -2,-6],
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[7,-8, 12,-7],
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[-13,-7, -11,-12],
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[1,-3, 12,12],
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[2,-6, 3,0],
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[-4,3, -2,-13],
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[-1,-13, 1,9],
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[7,1, 8,-6],
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[1,-1, 3,12],
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[9,1, 12,6],
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[-1,-9, -1,3],
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[-13,-13, -10,5],
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[7,7, 10,12],
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[12,-5, 12,9],
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[6,3, 7,11],
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[5,-13, 6,10],
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[2,-12, 2,3],
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[3,8, 4,-6],
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[2,6, 12,-13],
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[9,-12, 10,3],
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[-8,4, -7,9],
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[-11,12, -4,-6],
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[1,12, 2,-8],
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[6,-9, 7,-4],
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[2,3, 3,-2],
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[6,3, 11,0],
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[3,-3, 8,-8],
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[7,8, 9,3],
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[-11,-5, -6,-4],
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[-10,11, -5,10],
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[-5,-8, -3,12],
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[-10,5, -9,0],
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[8,-1, 12,-6],
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[4,-6, 6,-11],
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[-10,12, -8,7],
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[4,-2, 6,7],
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[-2,0, -2,12],
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[-5,-8, -5,2],
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[7,-6, 10,12],
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[-9,-13, -8,-8],
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[-5,-13, -5,-2],
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[8,-8, 9,-13],
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[-9,-11, -9,0],
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[1,-8, 1,-2],
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[7,-4, 9,1],
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[-2,1, -1,-4],
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[11,-6, 12,-11],
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[-12,-9, -6,4],
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[3,7, 7,12],
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[5,5, 10,8],
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[0,-4, 2,8],
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[-9,12, -5,-13],
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[0,7, 2,12],
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[-1,2, 1,7],
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[5,11, 7,-9],
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[3,5, 6,-8],
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[-13,-4, -8,9],
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[-5,9, -3,-3],
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[-4,-7, -3,-12],
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[6,5, 8,0],
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[-7,6, -6,12],
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[-13,6, -5,-2],
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[1,-10, 3,10],
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[4,1, 8,-4],
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[-2,-2, 2,-13],
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[2,-12, 12,12],
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[-2,-13, 0,-6],
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[4,1, 9,3],
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[-6,-10, -3,-5],
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[-3,-13, -1,1],
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[7,5, 12,-11],
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[4,-2, 5,-7],
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[-13,9, -9,-5],
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[7,1, 8,6],
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[7,-8, 7,6],
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[-7,-4, -7,1],
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[-8,11, -7,-8],
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[-13,6, -12,-8],
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[2,4, 3,9],
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[10,-5, 12,3],
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[-6,-5, -6,7],
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[8,-3, 9,-8],
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[2,-12, 2,8],
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[-11,-2, -10,3],
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[-12,-13, -7,-9],
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[-11,0, -10,-5],
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[5,-3, 11,8],
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[-2,-13, -1,12],
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[-1,-8, 0,9],
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[-13,-11, -12,-5],
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[-10,-2, -10,11],
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[-3,9, -2,-13],
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[2,-3, 3,2],
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[-9,-13, -4,0],
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[-4,6, -3,-10],
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[-4,12, -2,-7],
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[-6,-11, -4,9],
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[6,-3, 6,11],
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[-13,11, -5,5],
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[11,11, 12,6],
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[7,-5, 12,-2],
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[-1,12, 0,7],
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[-4,-8, -3,-2],
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[-7,1, -6,7],
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[-13,-12, -8,-13],
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[-7,-2, -6,-8],
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[-8,5, -6,-9],
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[-5,-1, -4,5],
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[-13,7, -8,10],
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[1,5, 5,-13],
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[1,0, 10,-13],
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[9,12, 10,-1],
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[5,-8, 10,-9],
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[-1,11, 1,-13],
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[-9,-3, -6,2],
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[-1,-10, 1,12],
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[-13,1, -8,-10],
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[8,-11, 10,-6],
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[2,-13, 3,-6],
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[7,-13, 12,-9],
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[-10,-10, -5,-7],
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[-10,-8, -8,-13],
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[4,-6, 8,5],
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[3,12, 8,-13],
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[-4,2, -3,-3],
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[5,-13, 10,-12],
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[4,-13, 5,-1],
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[-9,9, -4,3],
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[0,3, 3,-9],
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[-12,1, -6,1],
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[3,2, 4,-8],
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[-10,-10, -10,9],
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[8,-13, 12,12],
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[-8,-12, -6,-5],
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[2,2, 3,7],
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[10,6, 11,-8],
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[6,8, 8,-12],
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[-7,10, -6,5],
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[-3,-9, -3,9],
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[-1,-13, -1,5],
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[-3,-7, -3,4],
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[-8,-2, -8,3],
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[4,2, 12,12],
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[2,-5, 3,11],
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[6,-9, 11,-13],
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[3,-1, 7,12],
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[11,-1, 12,4],
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[-3,0, -3,6],
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[4,-11, 4,12],
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[2,-4, 2,1],
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[-10,-6, -8,1],
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[-13,7, -11,1],
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[-13,12, -11,-13],
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[6,0, 11,-13],
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[0,-1, 1,4],
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[-13,3, -9,-2],
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[-9,8, -6,-3],
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[-13,-6, -8,-2],
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[5,-9, 8,10],
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[2,7, 3,-9],
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[-1,-6, -1,-1],
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[9,5, 11,-2],
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[11,-3, 12,-8],
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[3,0, 3,5],
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[-1,4, 0,10],
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[3,-6, 4,5],
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[-13,0, -10,5],
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[5,8, 12,11],
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[8,9, 9,-6],
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[7,-4, 8,-12],
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[-10,4, -10,9],
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[7,3, 12,4],
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[9,-7, 10,-2],
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[7,0, 12,-2],
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[-1,-6, 0,-11]], dtype=np.int8))
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