wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-08 18:08:47 +08:00
Code Issues Packages Projects Releases Wiki Activity

Incorporating recarray changes to match.py

Browse Source
This commit is contained in:
Ankit Agrawal
2013-11-12 03:08:09 +05:30
committed by Johannes Schönberger
parent 1a2efa7e37
commit 0d79b3963e
2 changed files with 34 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/feature/match.py
+12 -8
View File
@@ -11,12 +11,14 @@ def match_binary_descriptors(keypoints1, descriptors1, keypoints2,
Parameters
----------
keypoints1 : (M, 2) ndarray
M Keypoints from the first image described using skimage.feature.brief
keypoints1 : record array with M rows
Record array with fields row, col, octave, orientation, response.
Octave, orientation and response can be None.
descriptors1 : (M, P) ndarray
Binary descriptors of size P about M keypoints in the first image.
keypoints2 : (N, 2) ndarray
N Keypoints from the second image described using skimage.feature.brief
keypoints2 : record array with N rows
Record array with fields row, col, octave, orientation, response.
Octave, orientation and response can be None.
descriptors2 : (N, P) ndarray
Binary descriptors of size P about N keypoints in the second image.
threshold : float in range [0, 1]
@@ -49,6 +51,8 @@ def match_binary_descriptors(keypoints1, descriptors1, keypoints2,
# Get hamming distances between keypoints1 and keypoints2
distance = pairwise_hamming_distance(descriptors1, descriptors2)
kp1 = np.squeeze(np.dstack((keypoints1.row, keypoints1.col)))
kp2 = np.squeeze(np.dstack((keypoints2.row, keypoints2.col)))
if cross_check:
matched_keypoints1_index = np.argmin(distance, axis=1)
@@ -62,16 +66,16 @@ def match_binary_descriptors(keypoints1, descriptors1, keypoints2,
dtype=np.intp)
mask1 = matched_index[:, 0]
mask2 = matched_index[:, 1]
matches[:, 0, :] = keypoints1[mask1]
matches[:, 1, :] = keypoints2[mask2]
matches[:, 0, :] = kp1[mask1]
matches[:, 1, :] = kp2[mask2]
else:
temp = distance > threshold
row_check = np.any(~temp, axis=1)
matched_keypoints2 = keypoints2[np.argmin(distance, axis=1)]
matched_keypoints2 = kp2[np.argmin(distance, axis=1)]
matches = np.zeros((np.sum(row_check), 2, 2),
dtype=np.intp)
matches[:, 0, :] = keypoints1[row_check]
matches[:, 0, :] = kp1[row_check]
matches[:, 1, :] = matched_keypoints2[row_check]
mask1 = np.where(row_check == True)[0]
mask2 = np.argmin(distance, axis=1)[row_check]
skimage/feature/tests/test_match.py
+22 -10
View File
@@ -4,7 +4,8 @@ from skimage import data
from skimage import transform as tf
from skimage.color import rgb2gray
from skimage.feature import (descriptor_brief, match_binary_descriptors,
corner_peaks, corner_harris)
corner_peaks, corner_harris,
create_keypoint_recarray)
def test_match_binary_descriptors_unequal_descriptor_keypoints_error():
@@ -12,26 +13,30 @@ def test_match_binary_descriptors_unequal_descriptor_keypoints_error():
kp1 = np.array([[40, 50],
[60, 40],
[30, 70]])
keypoints1 = create_keypoint_recarray(kp1[:, 0], kp1[:, 1])
des1 = np.array([[True, True, False, True],
[False, True, False, True]])
kp2 = np.array([[60, 50],
[50, 80]])
keypoints2 = create_keypoint_recarray(kp2[:, 0], kp2[:, 1])
des2 = np.array([[True, False, False, True],
[False, True, True, True]])
assert_raises(ValueError, match_binary_descriptors, kp1, des1, kp2, des2)
assert_raises(ValueError, match_binary_descriptors, keypoints1, des1, keypoints2, des2)
def test_match_binary_descriptors_unequal_descriptor_sizes_error():
"""Sizes of descriptors of keypoints to be matched should be equal."""
kp1 = np.array([[40, 50],
[60, 40]])
keypoints1 = create_keypoint_recarray(kp1[:, 0], kp1[:, 1])
des1 = np.array([[True, True, False, True],
[False, True, False, True]])
kp2 = np.array([[60, 50],
[50, 80]])
keypoints2 = create_keypoint_recarray(kp2[:, 0], kp2[:, 1])
des2 = np.array([[True, False, False, True, False],
[False, True, True, True, False]])
assert_raises(ValueError, match_binary_descriptors, kp1, des1, kp2, des2)
assert_raises(ValueError, match_binary_descriptors, keypoints1, des1, keypoints2, des2)
def test_match_binary_descriptors_lena_rotation_crosscheck_false():
@@ -43,10 +48,13 @@ def test_match_binary_descriptors_lena_rotation_crosscheck_false():
tform = tf.SimilarityTransform(scale=1, rotation=0.15, translation=(0, 0))
rotated_img = tf.warp(img, tform)
keypoints1 = corner_peaks(corner_harris(img), min_distance=5)
descriptors1, keypoints1 = descriptor_brief(img, keypoints1, descriptor_size=512)
kp1 = corner_peaks(corner_harris(img), min_distance=5)
keypoints1 = create_keypoint_recarray(kp1[:, 0], kp1[:, 1])
descriptors1, keypoints1 = descriptor_brief(img, keypoints1,
descriptor_size=512)
keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5)
kp2 = corner_peaks(corner_harris(rotated_img), min_distance=5)
keypoints2 = create_keypoint_recarray(kp2[:, 0], kp2[:, 1])
descriptors2, keypoints2 = descriptor_brief(rotated_img, keypoints2,
descriptor_size=512)
@@ -57,8 +65,10 @@ def test_match_binary_descriptors_lena_rotation_crosscheck_false():
threshold=0.13,
cross_check=False)
expected_mask1 = np.array([11, 12, 16, 20, 24, 26, 27, 29, 35, 39, 40, 42, 45])
expected_mask2 = np.array([ 1, 3, 0, 4, 6, 7, 8, 9, 10, 10, 11, 12, 13])
expected_mask1 = np.array([11, 12, 16, 20, 24, 26, 27, 29, 35, 39, 40,
42, 45])
expected_mask2 = np.array([ 1, 3, 0, 4, 6, 7, 8, 9, 10, 10, 11,
12, 13])
expected = np.array([[[245, 141],
[221, 176]],
@@ -112,10 +122,12 @@ def test_match_binary_descriptors_lena_rotation_crosscheck_true():
tform = tf.SimilarityTransform(scale=1, rotation=0.15, translation=(0, 0))
rotated_img = tf.warp(img, tform)
keypoints1 = corner_peaks(corner_harris(img), min_distance=5)
kp1 = corner_peaks(corner_harris(img), min_distance=5)
keypoints1 = create_keypoint_recarray(kp1[:, 0], kp1[:, 1])
descriptors1, keypoints1 = descriptor_brief(img, keypoints1, descriptor_size=512)
keypoints2 = corner_peaks(corner_harris(rotated_img), min_distance=5)
kp2 = corner_peaks(corner_harris(rotated_img), min_distance=5)
keypoints2 = create_keypoint_recarray(kp2[:, 0], kp2[:, 1])
descriptors2, keypoints2 = descriptor_brief(rotated_img, keypoints2,
descriptor_size=512)