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Actively filtering border keypoints for all the scales part 2

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This commit is contained in:
Ankit Agrawal
2013-08-15 15:00:00 +05:30
parent 963f681e48
commit 1227507c9e
3 changed files with 49 additions and 37 deletions
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skimage/feature/censure.py
+22 -17
View File
@@ -5,6 +5,7 @@ from skimage.transform import integral_image
from skimage.feature.corner import _compute_auto_correlation
from skimage.util import img_as_float
from skimage.morphology import convex_hull_image
from skimage.feature.util import _remove_border_keypoints
from skimage.feature.censure_cy import _censure_dob_loop
@@ -204,24 +205,28 @@ def censure_keypoints(image, n_scales=7, mode='DoB', non_max_threshold=0.15,
feature_mask[:, :, i] = _suppress_lines(feature_mask[:, :, i], image,
(1 + i / 3.0), line_threshold)
if mode == 'Octagon':
for i in range(1, n_scales - 1):
c = (OCTAGON_OUTER_SHAPE[i][0] - 1) // 2 + OCTAGON_OUTER_SHAPE[i][1]
feature_mask[:c, :, i] = False
feature_mask[:, :c, i] = False
feature_mask[-c:, :, i] = False
feature_mask[:, -c:, i] = False
elif mode == 'STAR':
for i in range(1, n_scales - 1):
c = STAR_SHAPE[STAR_FILTER_SHAPE[i][0]] + STAR_SHAPE[STAR_FILTER_SHAPE[i][0]] // 2
feature_mask[:c, :, i] = False
feature_mask[:, :c, i] = False
feature_mask[-c:, :, i] = False
feature_mask[:, -c:, i] = False
rows, cols, scales = np.nonzero(feature_mask[..., 1:n_scales - 1])
keypoints = np.column_stack([rows, cols])
scales = scales + 2
return keypoints, scales
if mode == 'DoB':
return keypoints, scales
filtered_keypoints = np.empty((0, 2), dtype=np.int32)
filtered_scales = np.empty((0), dtype=np.int32)
if mode == 'Octagon':
for i in range(2, n_scales):
c = (OCTAGON_OUTER_SHAPE[i - 1][0] - 1) // 2 + OCTAGON_OUTER_SHAPE[i - 1][1]
filtered_keypoints_for_scale = _remove_border_keypoints(image, keypoints[scales == i], c)
filtered_keypoints = np.vstack((filtered_keypoints, filtered_keypoints_for_scale))
filtered_scales = np.hstack((filtered_scales, np.asarray(len(filtered_keypoints_for_scale) * [i], dtype=np.int32)))
elif mode == 'STAR':
for i in range(2, n_scales):
c = STAR_SHAPE[STAR_FILTER_SHAPE[i - 1][0]] + STAR_SHAPE[STAR_FILTER_SHAPE[i - 1][0]] // 2
filtered_keypoints_for_scale = _remove_border_keypoints(image, keypoints[scales == i], c)
filtered_keypoints = np.vstack((filtered_keypoints, filtered_keypoints_for_scale))
filtered_scales = np.hstack((filtered_scales, np.asarray(len(filtered_keypoints_for_scale) * [i], dtype=np.int32)))
return filtered_keypoints, filtered_scales
skimage/feature/tests/test_censure.py
+19 -15
View File
@@ -28,7 +28,8 @@ def test_censure_keypoints_moon_image_DoB():
[464, 132],
[467, 260]])
expected_scale = np.array([2, 4, 6, 3, 4, 4, 2, 2, 3, 2, 2, 2])
print actual_scale
print actual_kp_DoB
assert_array_equal(expected_kp_DoB, actual_kp_DoB)
assert_array_equal(expected_scale, actual_scale)
@@ -38,13 +39,15 @@ def test_censure_keypoints_moon_image_Octagon():
the expected values for Octagon filter."""
img = moon()
actual_kp_Octagon, actual_scale = censure_keypoints(img, 7, 'Octagon', 0.15)
expected_kp_Octagon = np.array([[ 21, 496],
[ 35, 46],
[287, 250],
expected_kp_Octagon = np.array([[287, 250],
[356, 239],
[463, 116]])
expected_scale = np.array([3, 4, 2, 2, 2])
[463, 116],
[ 21, 496],
[ 35, 46]])
expected_scale = np.array([2, 2, 2, 3, 4], dtype=np.int32)
print actual_scale
print actual_kp_Octagon
assert_array_equal(expected_kp_Octagon, actual_kp_Octagon)
assert_array_equal(expected_scale, actual_scale)
@@ -54,18 +57,19 @@ def test_censure_keypoints_moon_image_STAR():
the expected values for STAR filter."""
img = moon()
actual_kp_STAR, actual_scale = censure_keypoints(img, 7, 'STAR', 0.15)
expected_kp_STAR = np.array([[ 21, 497],
[ 36, 46],
[117, 356],
[185, 177],
[260, 227],
expected_kp_STAR = np.array([[185, 177],
[287, 250],
[463, 116],
[467, 260],
[ 21, 497],
[ 36, 46],
[260, 227],
[357, 239],
[451, 281],
[463, 116],
[467, 260]])
expected_scale = np.array([3, 3, 6, 2, 3, 2, 3, 5, 2, 2])
[117, 356]])
expected_scale = np.array([2, 2, 2, 2, 3, 3, 3, 3, 5, 6], dtype=np.int32)
print actual_scale
print actual_kp_STAR
assert_array_equal(expected_kp_STAR, actual_kp_STAR)
assert_array_equal(expected_scale, actual_scale)
skimage/feature/util.py
+8 -5
View File
@@ -1,3 +1,4 @@
import numpy as np
def _remove_border_keypoints(image, keypoints, dist):
@@ -5,11 +6,13 @@ def _remove_border_keypoints(image, keypoints, dist):
width = image.shape[0]
height = image.shape[1]
keypoints = keypoints[(dist - 1 < keypoints[:, 0])
& (keypoints[:, 0] < width - dist + 1)
& (dist - 1 < keypoints[:, 1])
& (keypoints[:, 1] < height - dist + 1)]
try:
keypoints = keypoints[(dist - 1 < keypoints[:, 0])
& (keypoints[:, 0] < width - dist + 1)
& (dist - 1 < keypoints[:, 1])
& (keypoints[:, 1] < height - dist + 1)]
except IndexError:
return np.empty((0, 2), dtype=np.int32)
return keypoints