star = cv2.xfeatures2d.StarDetector_create()
# Initiate BRIEF extractor
-brief = cv2.BriefDescriptorExtractor_create()
+brief = cv2.xfeatures2d.BriefDescriptorExtractor_create()
# find the keypoints with STAR
kp = star.detect(img,None)
# compute the descriptors with BRIEF
kp, des = brief.compute(img, kp)
-print brief.getInt('bytes')
+print brief.descriptorSize()
print des.shape
@endcode
-The function brief.getInt('bytes') gives the \f$n_d\f$ size used in bytes. By default it is 32. Next one
+The function brief.getDescriptorSize() gives the \f$n_d\f$ size used in bytes. By default it is 32. Next one
is matching, which will be done in another chapter.
Additional Resources
img2 = cv2.drawKeypoints(img, kp, None, color=(255,0,0))
# Print all default params
-print "Threshold: ", fast.getInt('threshold')
-print "nonmaxSuppression: ", fast.getBool('nonmaxSuppression')
-print "neighborhood: ", fast.getInt('type')
+print "Threshold: ", fast.getThreshold()
+print "nonmaxSuppression: ", fast.getNonmaxSuppression()
+print "neighborhood: ", fast.getType()
print "Total Keypoints with nonmaxSuppression: ", len(kp)
cv2.imwrite('fast_true.png',img2)
# Disable nonmaxSuppression
-fast.setBool('nonmaxSuppression',0)
+fast.setNonmaxSuppression(0)
kp = fast.detect(img,None)
print "Total Keypoints without nonmaxSuppression: ", len(kp)