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Outsource inner brief loop into cython file

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This commit is contained in:
Johannes Schönberger
2013-07-02 21:59:49 +02:00
parent f3b827d21b
commit bcacd06f9c
4 changed files with 80 additions and 29 deletions
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skimage/feature/__init__.py
+3 -1
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@@ -6,6 +6,7 @@ from .corner import (corner_kitchen_rosenfeld, corner_harris, corner_shi_tomasi,
corner_foerstner, corner_subpix, corner_peaks)
from .corner_cy import corner_moravec
from .template import match_template
from ._brief import brief
__all__ = ['daisy',
@@ -21,4 +22,5 @@ __all__ = ['daisy',
'corner_subpix',
'corner_peaks',
'corner_moravec',
'match_template']
'match_template',
'brief']
skimage/feature/_brief.py
+50 -28
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@@ -1,20 +1,28 @@
import numpy as np
from skimage.color import rgb2gray
from scipy.ndimage.filters import gaussian_filter
from scipy.spatial.distance import hamming
from ..color import rgb2gray
from ..util import img_as_float
from ._brief_cy import _brief_loop
def _remove_border_keypoints(image, keypoints, dist):
width = image.shape[0]
height = image.shape[1]
keypoints = keypoints[(dist < keypoints[:, 0]) & (keypoints[:, 0] < width - dist) &
(dist < keypoints[:, 1]) & (keypoints[:, 1] < height - dist)]
keypoints = keypoints[(dist < keypoints[:, 0])
& (keypoints[:, 0] < width - dist)
& (dist < keypoints[:, 1])
& (keypoints[:, 1] < height - dist)]
return keypoints
def brief(image, keypoints, descriptor_size=256, mode='normal', patch_size=49, sample_seed=1):
def brief(image, keypoints, descriptor_size=256, mode='normal', patch_size=49,
sample_seed=1):
"""Extract BRIEF Descriptor about given keypoints for a given image.
Parameters
@@ -49,41 +57,55 @@ def brief(image, keypoints, descriptor_size=256, mode='normal', patch_size=49, s
http://cvlabwww.epfl.ch/~lepetit/papers/calonder_eccv10.pdf
"""
if np.squeeze(image).ndim == 3:
image = rgb2gray(image)
keypoints = np.array(keypoints + 0.5, dtype=np.intp)
np.random.seed(sample_seed)
# Removing keypoints that are (patch_size / 2) distance from the image border
image = np.squeeze(image)
if image.ndim != 2:
raise ValueError("Only 2-D gray-scale images supported.")
image = img_as_float(image)
# Gaussian Low pass filtering with variance 2 to alleviate noise
# sensitivity
image = gaussian_filter(image, 2)
image = np.ascontiguousarray(image)
keypoints = np.array(keypoints + 0.5, dtype=np.intp, order='C')
# Removing keypoints that are (patch_size / 2) distance from the image
# border
keypoints = _remove_border_keypoints(image, keypoints, patch_size / 2)
descriptor = np.zeros((len(keypoints), descriptor_size), dtype=bool)
# Gaussian Low pass filtering with variance 2 to alleviate noise sensitivity
image = gaussian_filter(image, 2)
descriptors = np.zeros((keypoints.shape[0], descriptor_size),
dtype=bool, order='C')
# Sampling pairs of decision pixels in patch_size x patch_size window
if mode == 'normal':
np.random.seed(sample_seed)
samples = np.round((patch_size / 5) * np.random.randn(descriptor_size * 8))
samples = samples[(samples < (patch_size / 2)) & (samples > - (patch_size - 1) / 2)]
first = (samples[: descriptor_size * 2]).reshape(descriptor_size, 2)
second = (samples[descriptor_size * 2: descriptor_size * 4]).reshape(descriptor_size, 2)
samples = (patch_size / 5) * np.random.randn(descriptor_size * 8)
samples = np.array(samples, dtype=np.int32)
samples = samples[(samples < (patch_size / 2))
& (samples > - (patch_size - 1) / 2)]
pos1 = samples[:descriptor_size * 2]
pos1 = pos1.reshape(descriptor_size, 2)
pos2 = samples[descriptor_size * 2:descriptor_size * 4]
pos2 = pos2.reshape(descriptor_size, 2)
else:
np.random.seed(sample_seed)
samples = np.random.randint(-patch_size / 2, (patch_size / 2) + 1, (descriptor_size * 2, 2))
first, second = np.split(samples, 2)
# Intensity comparison tests for building the descriptor
for i in range(len(keypoints)):
set_1 = first + keypoints[i]
set_2 = second + keypoints[i]
samples = np.random.randint(-patch_size / 2, (patch_size / 2) + 1,
(descriptor_size * 2, 2))
pos1, pos2 = np.split(samples, 2)
for j in range(descriptor_size):
if image[set_1[j, 0]][set_1[j, 1]] < image[set_2[j, 0]][set_2[j, 0]]:
descriptor[i][j] = True
pos1 = np.ascontiguousarray(pos1)
pos2 = np.ascontiguousarray(pos2)
return descriptor
_brief_loop(image, descriptors.view(np.uint8), keypoints, pos1, pos2)
return descriptors
def hamming_distance(descriptor_1, descriptor_2):
skimage/feature/_brief_cy.pyx
+24
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@@ -0,0 +1,24 @@
#cython: cdivision=True
#cython: boundscheck=False
#cython: nonecheck=False
#cython: wraparound=False
cimport numpy as cnp
def _brief_loop(double[:, ::1] image, char[:, ::1] descriptors,
Py_ssize_t[:, ::1] keypoints,
int[:, ::1] pos0, int[:, ::1] pos1):
cdef Py_ssize_t k, d, kr, kc, pr0, pr1, pc0, pc1
for p in range(pos0.shape[0]):
pr0 = pos0[p, 0]
pc0 = pos0[p, 1]
pr1 = pos1[p, 0]
pc1 = pos1[p, 1]
for k in range(keypoints.shape[0]):
kr = keypoints[k, 0]
kc = keypoints[k, 1]
if image[kr + pr0, kc + pc0] < image[kr + pr1, kc + pc1]:
descriptors[k, p] = True
skimage/feature/setup.py
+3
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@@ -13,11 +13,14 @@ def configuration(parent_package='', top_path=None):
config.add_data_dir('tests')
cython(['corner_cy.pyx'], working_path=base_path)
cython(['_brief_cy.pyx'], working_path=base_path)
cython(['_texture.pyx'], working_path=base_path)
cython(['_template.pyx'], working_path=base_path)
config.add_extension('corner_cy', sources=['corner_cy.c'],
include_dirs=[get_numpy_include_dirs()])
config.add_extension('_brief_cy', sources=['_brief_cy.c'],
include_dirs=[get_numpy_include_dirs()])
config.add_extension('_texture', sources=['_texture.c'],
include_dirs=[get_numpy_include_dirs(), '../_shared'])
config.add_extension('_template', sources=['_template.c'],