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Replacing censure_keypoints by keypoints_censure, n_scales by max_scale

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Ankit Agrawal
2013-08-12 16:37:09 +05:30
parent 7665281c4a
commit 229910efe7
3 changed files with 23 additions and 23 deletions
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skimage/feature/__init__.py
+2 -2
View File
@@ -9,7 +9,7 @@ from .corner_cy import corner_moravec
from .template import match_template
from ._brief import brief, match_keypoints_brief
from .util import pairwise_hamming_distance
from .censure import censure_keypoints
from .censure import keypoints_censure
__all__ = ['daisy',
'hog',
@@ -28,4 +28,4 @@ __all__ = ['daisy',
'brief',
'pairwise_hamming_distance',
'match_keypoints_brief',
'censure_keypoints']
'keypoints_censure']
skimage/feature/censure.py
+12 -12
View File
@@ -19,9 +19,9 @@ STAR_FILTER_SHAPE = [(1, 0), (3, 1), (4, 2), (5, 3), (7, 4), (8, 5),
(9, 6),(11, 8), (13, 10), (14, 11), (15, 12), (16, 14)]
def _get_filtered_image(image, n_scales, mode):
def _get_filtered_image(image, max_scale, mode):
scales = np.zeros((image.shape[0], image.shape[1], n_scales),
scales = np.zeros((image.shape[0], image.shape[1], max_scale),
dtype=np.double)
if mode == 'dob':
@@ -34,7 +34,7 @@ def _get_filtered_image(image, n_scales, mode):
integral_img = integral_image(image)
for i in range(n_scales):
for i in range(max_scale):
n = i + 1
# Constant multipliers for the outer region and the inner region
@@ -54,14 +54,14 @@ def _get_filtered_image(image, n_scales, mode):
elif mode == 'octagon':
# TODO : Decide the shapes of Octagon filters for scales > 7
for i in range(n_scales):
for i in range(max_scale):
mo, no = OCTAGON_OUTER_SHAPE[i]
mi, ni = OCTAGON_INNER_SHAPE[i]
scales[:, :, i] = convolve(image,
_octagon_filter_kernel(mo, no, mi, ni))
elif mode == 'star':
for i in range(n_scales):
for i in range(max_scale):
m = STAR_SHAPE[STAR_FILTER_SHAPE[i][0]]
n = STAR_SHAPE[STAR_FILTER_SHAPE[i][1]]
scales[:, :, i] = convolve(image,
@@ -135,7 +135,7 @@ def _suppress_lines(feature_mask, image, sigma, line_threshold):
> line_threshold * (Axx * Ayy - Axy * Axy)] = False
def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
def keypoints_censure(image, max_scale=7, mode='DoB', non_max_threshold=0.15,
line_threshold=10):
"""
Extracts Censure keypoints along with the corresponding scale using
@@ -145,7 +145,7 @@ def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
----------
image : 2D ndarray
Input image.
n_scales : positive integer
max_scale : positive integer
Number of scales to extract keypoints from. The keypoints will be
extracted from all the scales except the first and the last.
mode : ('DoB', 'Octagon', 'STAR')
@@ -192,7 +192,7 @@ def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
raise ValueError('Mode must be one of "DoB", "Octagon", "STAR".')
# Generating all the scales
filter_response = _get_filtered_image(image, n_scales, mode)
filter_response = _get_filtered_image(image, max_scale, mode)
# Suppressing points that are neither minima or maxima in their 3 x 3 x 3
# neighbourhood to zero
@@ -202,7 +202,7 @@ def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
feature_mask = minimas | maximas
feature_mask[filter_response < non_max_threshold] = False
for i in range(1, n_scales - 1):
for i in range(1, max_scale - 1):
# sigma = (window_size - 1) / 6.0, so the window covers > 99% of the
# kernel's distribution
# window_size = 7 + 2 * i
@@ -210,7 +210,7 @@ def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
_suppress_lines(feature_mask[:, :, i], image,
(1 + i / 3.0), line_threshold)
rows, cols, scales = np.nonzero(feature_mask[..., 1:n_scales - 1])
rows, cols, scales = np.nonzero(feature_mask[..., 1:max_scale - 1])
keypoints = np.column_stack([rows, cols])
scales = scales + 2
@@ -220,13 +220,13 @@ def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
cumulative_mask = np.zeros(keypoints.shape[0], dtype=np.bool)
if mode == 'octagon':
for i in range(2, n_scales):
for i in range(2, max_scale):
c = (OCTAGON_OUTER_SHAPE[i - 1][0] - 1) // 2 \
+ OCTAGON_OUTER_SHAPE[i - 1][1]
cumulative_mask |= _mask_border_keypoints(image, keypoints, c) \
& (scales == i)
elif mode == 'star':
for i in range(2, n_scales):
for i in range(2, max_scale):
c = STAR_SHAPE[STAR_FILTER_SHAPE[i - 1][0]] \
+ STAR_SHAPE[STAR_FILTER_SHAPE[i - 1][0]] // 2
cumulative_mask |= _mask_border_keypoints(image, keypoints, c) \
skimage/feature/tests/test_censure.py
+9 -9
View File
@@ -1,20 +1,20 @@
import numpy as np
from numpy.testing import assert_array_equal, assert_raises
from skimage.data import moon
from skimage.feature import censure_keypoints
from skimage.feature import keypoints_censure
def test_censure_keypoints_color_image_unsupported_error():
def test_keypoints_censure_color_image_unsupported_error():
"""Censure keypoints can be extracted from gray-scale images only."""
img = np.zeros((20, 20, 3))
assert_raises(ValueError, censure_keypoints, img)
assert_raises(ValueError, keypoints_censure, img)
def test_censure_keypoints_moon_image_dob():
def test_keypoints_censure_moon_image_dob():
"""Verify the actual Censure keypoints and their corresponding scale with
the expected values for DoB filter."""
img = moon()
actual_kp_dob, actual_scale = censure_keypoints(img, 7, 'DoB', 0.15)
actual_kp_dob, actual_scale = keypoints_censure(img, 7, 'DoB', 0.15)
expected_kp_dob = np.array([[ 21, 497],
[ 36, 46],
[119, 350],
@@ -30,11 +30,11 @@ def test_censure_keypoints_moon_image_dob():
assert_array_equal(expected_scale, actual_scale)
def test_censure_keypoints_moon_image_Octagon():
def test_keypoints_censure_moon_image_Octagon():
"""Verify the actual Censure keypoints and their corresponding scale with
the expected values for Octagon filter."""
img = moon()
actual_kp_octagon, actual_scale = censure_keypoints(img, 7, 'Octagon',
actual_kp_octagon, actual_scale = keypoints_censure(img, 7, 'Octagon',
0.15)
expected_kp_octagon = np.array([[ 21, 496],
[ 35, 46],
@@ -48,11 +48,11 @@ def test_censure_keypoints_moon_image_Octagon():
assert_array_equal(expected_scale, actual_scale)
def test_censure_keypoints_moon_image_STAR():
def test_keypoints_censure_moon_image_STAR():
"""Verify the actual Censure keypoints and their corresponding scale with
the expected values for STAR filter."""
img = moon()
actual_kp_star, actual_scale = censure_keypoints(img, 7, 'STAR', 0.15)
actual_kp_star, actual_scale = keypoints_censure(img, 7, 'STAR', 0.15)
expected_kp_star = np.array([[ 21, 497],
[ 36, 46],
[117, 356],