generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Merge pull request #1430 from nzjrs:add-brisk-to-demos

Browse Source
This commit is contained in:
Alexander Smorkalov 2013-09-23 16:34:14 +04:00 committed by OpenCV Buildbot
commit c8b97271cc
2 changed files with 9 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
samples/python2/asift.py
View File

@ -11,10 +11,10 @@ is used to reject outliers. Threading is used for faster affine sampling.
[1] http://www.ipol.im/pub/algo/my_affine_sift/ [1] http://www.ipol.im/pub/algo/my_affine_sift/
USAGE USAGE
asift.py [--feature=<sift|surf|orb>[-flann]] [ <image1> <image2> ] asift.py [--feature=<sift|surf|orb|brisk>[-flann]] [ <image1> <image2> ]
--feature - Feature to use. Can be sift, surf of orb. Append '-flann' to feature name --feature - Feature to use. Can be sift, surf, orb or brisk. Append '-flann'
to use Flann-based matcher instead bruteforce. to feature name to use Flann-based matcher instead bruteforce.
Press left mouse button on a feature point to see its mathcing point. Press left mouse button on a feature point to see its mathcing point.
''' '''

9
samples/python2/find_obj.py
View File

@ -4,10 +4,10 @@
Feature-based image matching sample. Feature-based image matching sample.
USAGE USAGE
find_obj.py [--feature=<sift|surf|orb>[-flann]] [ <image1> <image2> ] find_obj.py [--feature=<sift|surf|orb|brisk>[-flann]] [ <image1> <image2> ]
--feature - Feature to use. Can be sift, surf of orb. Append '-flann' to feature name --feature - Feature to use. Can be sift, surf, orb or brisk. Append '-flann'
to use Flann-based matcher instead bruteforce. to feature name to use Flann-based matcher instead bruteforce.
Press left mouse button on a feature point to see its matching point. Press left mouse button on a feature point to see its matching point.
''' '''
@ -31,6 +31,9 @@ def init_feature(name):
elif chunks[0] == 'orb': elif chunks[0] == 'orb':
detector = cv2.ORB(400) detector = cv2.ORB(400)
norm = cv2.NORM_HAMMING norm = cv2.NORM_HAMMING
elif chunks[0] == 'brisk':
detector = cv2.BRISK()
norm = cv2.NORM_HAMMING
else: else:
return None, None return None, None
if 'flann' in chunks: if 'flann' in chunks: