def extract_all(self, image):
sift = cv2.xfeatures2d.SIFT_create()
features, descriptors = sift.detectAndCompute(image, None)
features, descriptors = fu.filter_by_kpt_response(
MAX_CV_KPTS, features, descriptors)
return (features, descriptors)
def extract_all(self, image):
kaze = cv2.KAZE_create()
features, descriptors = kaze.detectAndCompute(image,None)
pts, descriptors = fu.filter_by_kpt_response(MAX_CV_KPTS, features, descriptors)
return (pts, descriptors)
def detect_feature(self, image):
kaze = cv2.KAZE_create()
features = kaze.detect(image,None)
pts = fu.filter_by_kpt_response(MAX_CV_KPTS, features)
return pts
def detect_feature(self, image):
harLap = cv2.xfeatures2d.HarrisLaplaceFeatureDetector_create()
features = harLap.detect(image, None)
pts = fu.filter_by_kpt_response(MAX_CV_KPTS, features)
return pts
def detect_feature(self, image):
surf = cv2.xfeatures2d.SURF_create()
features = surf.detect(image, None)
pts = fu.filter_by_kpt_response(MAX_CV_KPTS, features)
return pts
def extract_descriptor(self, image, feature):
sift = cv2.xfeatures2d.SIFT_create()
features, descriptors = sift.compute(image, feature)
_, descriptors = fu.filter_by_kpt_response(MAX_CV_KPTS, features,
descriptors)
return descriptors