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Combine match indices in one array

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This commit is contained in:
Johannes Schönberger
2013-12-01 11:14:18 +01:00
parent e0e4f697de
commit ed33dbad6e
8 changed files with 69 additions and 66 deletions
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doc/examples/plot_brief.py
+5 -4
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@@ -45,16 +45,17 @@ keypoints1 = keypoints1[mask1]
keypoints2 = keypoints2[mask2]
keypoints3 = keypoints3[mask3]
matches12 = match_descriptors(descriptors1, descriptors2, cross_check=True)
matches13 = match_descriptors(descriptors1, descriptors3, cross_check=True)
fig, ax = plt.subplots(nrows=2, ncols=1)
plt.gray()
idxs1, idxs2 = match_descriptors(descriptors1, descriptors2, cross_check=True)
plot_matches(ax[0], img1, img2, keypoints1, keypoints2, idxs1, idxs2)
plot_matches(ax[0], img1, img2, keypoints1, keypoints2, matches12)
ax[0].axis('off')
idxs1, idxs3 = match_descriptors(descriptors1, descriptors3, cross_check=True)
plot_matches(ax[1], img1, img3, keypoints1, keypoints3, idxs1, idxs3)
plot_matches(ax[1], img1, img3, keypoints1, keypoints3, matches13)
ax[1].axis('off')
plt.show()
doc/examples/plot_orb.py
+5 -6
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@@ -31,18 +31,17 @@ keypoints1, descriptors1 = descriptor_extractor.detect_and_extract(img1)
keypoints2, descriptors2 = descriptor_extractor.detect_and_extract(img2)
keypoints3, descriptors3 = descriptor_extractor.detect_and_extract(img3)
matches12 = match_descriptors(descriptors1, descriptors2, cross_check=True)
matches13 = match_descriptors(descriptors1, descriptors3, cross_check=True)
fig, ax = plt.subplots(nrows=2, ncols=1)
plt.gray()
idxs1, idxs2 = match_descriptors(descriptors1, descriptors2, cross_check=True)
plot_matches(ax[0], img1, img2, keypoints1, keypoints2,
idxs1, idxs2)
plot_matches(ax[0], img1, img2, keypoints1, keypoints2, matches12)
ax[0].axis('off')
idxs1, idxs3 = match_descriptors(descriptors1, descriptors3, cross_check=True)
plot_matches(ax[1], img1, img3, keypoints1, keypoints3,
idxs1, idxs3)
plot_matches(ax[1], img1, img3, keypoints1, keypoints3, matches13)
ax[1].axis('off')
plt.show()
skimage/feature/brief.py
+8 -5
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@@ -77,15 +77,18 @@ class BRIEF(DescriptorExtractor):
>>> extractor = BRIEF(patch_size=5)
>>> descs1, _ = extractor.extract(square1, keypoints1)
>>> descs2, _ = extractor.extract(square2, keypoints2)
>>> idxs1, idxs2 = match_descriptors(descs1, descs2)
>>> idxs1, idxs2
(array([0, 1, 2, 3]), array([0, 1, 2, 3]))
>>> keypoints1[idxs1]
>>> matches = match_descriptors(descs1, descs2)
>>> matches
array([[0, 0],
[1, 1],
[2, 2],
[3, 3]])
>>> keypoints1[matches[:, 0]]
array([[2, 2],
[2, 5],
[5, 2],
[5, 5]])
>>> keypoints2[idxs2]
>>> keypoints2[matches[:, 1]]
array([[2, 2],
[2, 6],
[6, 2],
skimage/feature/match.py
+5 -5
View File
@@ -35,10 +35,10 @@ def match_descriptors(descriptors1, descriptors2, metric=None, p=2,
Returns
-------
indices1 : (Q, ) array
Indices of corresponding matches for first set of descriptors.
indices2 : (Q, ) array
Indices of corresponding matches for second set of descriptors.
matches : (Q, 2) array
Indices of corresponding matches in first and second set of
descriptors, where ``matches[:, 0]`` denote the indices in the first
and ``matches[:, 1]`` the indices in the second set of descriptors.
"""
@@ -62,4 +62,4 @@ def match_descriptors(descriptors1, descriptors2, metric=None, p=2,
indices1 = indices1[mask]
indices2 = indices2[mask]
return indices1, indices2
return np.column_stack((indices1, indices2))
skimage/feature/orb.py
+9 -5
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@@ -72,16 +72,20 @@ class ORB(FeatureDetector, DescriptorExtractor):
>>> detector_extractor = ORB(n_keypoints=5)
>>> keypoints1, descriptors1 = detector_extractor.detect_and_extract(img1)
>>> keypoints2, descriptors2 = detector_extractor.detect_and_extract(img2)
>>> idxs1, idxs2 = match_descriptors(descriptors1, descriptors2)
>>> idxs1, idxs2
(array([0, 1, 2, 3, 4]), array([0, 1, 2, 3, 4]))
>>> keypoints1[idxs1]
>>> matches = match_descriptors(descriptors1, descriptors2)
>>> matches
array([[0, 0],
[1, 1],
[2, 2],
[3, 3],
[4, 4]])
>>> keypoints1[matches[:, 0]]
array([[ 42., 40.],
[ 47., 58.],
[ 44., 40.],
[ 59., 42.],
[ 45., 44.]])
>>> keypoints2[idxs2]
>>> keypoints2[matches[:, 1]]
array([[ 55., 53.],
[ 60., 71.],
[ 57., 53.],
skimage/feature/tests/test_match.py
+23 -24
View File
@@ -9,21 +9,20 @@ from skimage.feature import (BRIEF, match_descriptors,
def test_binary_descriptors_unequal_descriptor_sizes_error():
"""Sizes of descriptors of keypoints to be matched should be equal."""
des1 = np.array([[True, True, False, True],
descs1 = np.array([[True, True, False, True],
[False, True, False, True]])
des2 = np.array([[True, False, False, True, False],
descs2 = np.array([[True, False, False, True, False],
[False, True, True, True, False]])
assert_raises(ValueError, match_descriptors, des1, des2)
assert_raises(ValueError, match_descriptors, descs1, descs2)
def test_binary_descriptors():
des1 = np.array([[True, True, False, True, True],
descs1 = np.array([[True, True, False, True, True],
[False, True, False, True, True]])
des2 = np.array([[True, False, False, True, False],
descs2 = np.array([[True, False, False, True, False],
[False, False, True, True, True]])
indices1, indices2 = match_descriptors(des1, des2)
assert_equal(indices1, [0, 1])
assert_equal(indices2, [0, 1])
matches = match_descriptors(descs1, descs2)
assert_equal(matches, [[0, 0], [1, 1]])
def test_binary_descriptors_lena_rotation_crosscheck_false():
@@ -45,19 +44,19 @@ def test_binary_descriptors_lena_rotation_crosscheck_false():
descriptors2, mask2 = descriptor.extract(rotated_img, keypoints2)
keypoints2 = keypoints1[mask2]
m1, m2 = match_descriptors(descriptors1, descriptors2, threshold=0.13,
matches = match_descriptors(descriptors1, descriptors2, threshold=0.13,
cross_check=False)
expected_mask1 = np.array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46])
expected_mask2 = np.array([33, 0, 35, 7, 1, 35, 3, 2, 3, 6, 4, 9,
11, 10, 28, 7, 8, 5, 31, 14, 13, 15, 21, 16,
16, 13, 17, 18, 19, 21, 22, 23, 0, 24, 1, 24,
23, 0, 26, 27, 25, 34, 28, 14, 29, 30, 21])
assert_equal(m1, expected_mask1)
assert_equal(m2, expected_mask2)
exp_matches1 = np.array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46])
exp_matches2 = np.array([33, 0, 35, 7, 1, 35, 3, 2, 3, 6, 4, 9,
11, 10, 28, 7, 8, 5, 31, 14, 13, 15, 21, 16,
16, 13, 17, 18, 19, 21, 22, 23, 0, 24, 1, 24,
23, 0, 26, 27, 25, 34, 28, 14, 29, 30, 21])
assert_equal(matches[:, 0], exp_matches1)
assert_equal(matches[:, 1], exp_matches2)
def test_binary_descriptors_lena_rotation_crosscheck_true():
@@ -79,17 +78,17 @@ def test_binary_descriptors_lena_rotation_crosscheck_true():
descriptors2, mask2 = descriptor.extract(rotated_img, keypoints2)
keypoints2 = keypoints1[mask2]
m1, m2 = match_descriptors(descriptors1, descriptors2, threshold=0.13,
matches = match_descriptors(descriptors1, descriptors2, threshold=0.13,
cross_check=True)
expected_mask1 = np.array([ 0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 15,
exp_matches1 = np.array([ 0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 15,
16, 17, 19, 20, 21, 24, 26, 27, 28, 29, 30, 35,
36, 38, 39, 40, 42, 44, 45])
expected_mask2 = np.array([33, 0, 35, 1, 3, 2, 6, 4, 9, 11, 10, 7,
exp_matches2 = np.array([33, 0, 35, 1, 3, 2, 6, 4, 9, 11, 10, 7,
8, 5, 14, 13, 15, 16, 17, 18, 19, 21, 22, 24,
23, 26, 27, 25, 28, 29, 30])
assert_equal(m1, expected_mask1)
assert_equal(m2, expected_mask2)
assert_equal(matches[:, 0], exp_matches1)
assert_equal(matches[:, 1], exp_matches2)
if __name__ == '__main__':
skimage/feature/tests/test_util.py
+5 -4
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@@ -54,16 +54,17 @@ def test_plot_matches():
keypoints2 = 10 * np.random.rand(10, 2)
idxs1 = np.random.randint(10, size=10)
idxs2 = np.random.randint(10, size=10)
matches = np.column_stack((idxs1, idxs2))
for shape1, shape2 in shapes:
img1 = np.zeros(shape1)
img2 = np.zeros(shape2)
plot_matches(ax, img1, img2, keypoints1, keypoints2, idxs1, idxs2)
plot_matches(ax, img1, img2, keypoints1, keypoints2, idxs1, idxs2,
plot_matches(ax, img1, img2, keypoints1, keypoints2, matches)
plot_matches(ax, img1, img2, keypoints1, keypoints2, matches,
only_matches=True)
plot_matches(ax, img1, img2, keypoints1, keypoints2, idxs1, idxs2,
plot_matches(ax, img1, img2, keypoints1, keypoints2, matches,
keypoints_color='r')
plot_matches(ax, img1, img2, keypoints1, keypoints2, idxs1, idxs2,
plot_matches(ax, img1, img2, keypoints1, keypoints2, matches,
matches_color='r')
skimage/feature/util.py
+9 -13
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@@ -33,9 +33,8 @@ class DescriptorExtractor(object):
raise NotImplementedError()
def plot_matches(ax, image1, image2, keypoints1, keypoints2,
indices1, indices2, keypoints_color='k', matches_color=None,
only_matches=False):
def plot_matches(ax, image1, image2, keypoints1, keypoints2, matches,
keypoints_color='k', matches_color=None, only_matches=False):
"""Plot matched features.
Parameters
@@ -50,10 +49,10 @@ def plot_matches(ax, image1, image2, keypoints1, keypoints2,
First keypoint coordinates as ``(row, col)``.
keypoints2 : (K2, 2) array
Second keypoint coordinates as ``(row, col)``.
indices1 : (Q, ) array
Indices of corresponding matches for first set of keypoints.
indices2 : (Q, ) array
Indices of corresponding matches for second set of keypoints.
matches : (Q, 2) array
Indices of corresponding matches in first and second set of
descriptors, where ``matches[:, 0]`` denote the indices in the first
and ``matches[:, 1]`` the indices in the second set of descriptors.
keypoints_color : matplotlib color
Color for keypoint locations.
matches_color : matplotlib color
@@ -67,9 +66,6 @@ def plot_matches(ax, image1, image2, keypoints1, keypoints2,
image1 = img_as_float(image1)
image2 = img_as_float(image2)
indices1 = np.squeeze(indices1)
indices2 = np.squeeze(indices2)
new_shape1 = list(image1.shape)
new_shape2 = list(image2.shape)
@@ -106,9 +102,9 @@ def plot_matches(ax, image1, image2, keypoints1, keypoints2,
ax.imshow(image)
ax.axis((0, 2 * offset[1], offset[0], 0))
for i in range(len(indices1)):
idx1 = indices1[i]
idx2 = indices2[i]
for i in range(matches.shape[0]):
idx1 = matches[i, 0]
idx2 = matches[i, 1]
if matches_color is None:
color = np.random.rand(3, 1)