def __init__(self, videoSource, featurePtMask=None, verbosity=0):
# cap the length of optical flow tracks
self.maxTrackLength = 10
# detect feature points in intervals of frames; adds robustness for
# when feature points disappear.
self.detectionInterval = 5
# Params for Shi-Tomasi corner (feature point) detection
self.featureParams = dict(
maxCorners=500,
qualityLevel=0.3,
minDistance=7,
blockSize=7
)
# Params for Lucas-Kanade optical flow
self.lkParams = dict(
winSize=(15, 15),
maxLevel=2,
criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03)
)
# # Alternatively use a fast feature detector
# self.fast = cv2.FastFeatureDetector_create(500)
self.verbosity = verbosity
(self.videoStream,
self.width,
self.height,
self.featurePtMask) = self._initializeCamera(videoSource)
python类FastFeatureDetector_create()的实例源码
def __init__(self, fx, cx, cy):
self.last_frame = None
self.R = None
self.t = None
self.px_ref = None
self.px_cur = None
self.focal = fx
self.pp = (cx, cy)
self.detector = cv2.FastFeatureDetector_create(threshold=25,
nonmaxSuppression=True)
def __init__(self, **kwargs):
self.detector = cv2.FastFeatureDetector_create(
threshold=kwargs.get("threshold", 25),
nonmaxSuppression=kwargs.get("nonmax_suppression", True)
)
def __init__(self):
self.fast = cv2.FastFeatureDetector_create()
self.mask = SkyCamera.getMask()
featuredetect.py 文件源码
项目：Compare-OpenCV-SIFT-SURF-FAST-ORB
作者: chengtaow
项目源码
文件源码
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def fast_thread():
fast = cv2.FastFeatureDetector_create()
kps3 = fast.detect(gray, None)
cv2.drawKeypoints(gray, kps3, img3, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imshow('FAST Algorithm', img3)
def __init__(self, image_topic, feature_detector='FAST'):
super(OpticalFlowMatcher, self).__init__()
rospy.init_node('optical_flow_matcher')
self.cv_bridge = CvBridge()
self.rectified_image_topic = rospy.Subscriber(
image_topic,
Image,
self.new_image_callback
)
self.pub_keypoint_motion = rospy.Publisher(
'keypoint_motion',
KeypointMotion,
queue_size=10
)
self.feature_params = None
if feature_detector == 'FAST':
self.get_features = self.get_features_fast
# Initiate FAST detector with default values
self.fast = cv2.FastFeatureDetector_create()
self.fast.setThreshold(20)
elif feature_detector == 'GOOD':
self.get_features = self.get_features_good
# params for ShiTomasi 'GOOD' corner detection
self.feature_params = dict(
maxCorners=200,
qualityLevel=0.3,
minDistance=7,
blockSize=7
)
else:
raise Exception(
'{} feature detector not implemented'.format(feature_detector)
)
# Parameters for lucas kanade optical flow
self.lk_params = dict(
winSize=(15, 15),
maxLevel=2,
criteria=(
cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT,
10,
0.03
)
)
self.last_frame_gray = None
self.good_old = None
self.good_new = None
def __init__(self, image_topic, feature_detector='SIFT'):
super(SIFTMatcher, self).__init__()
rospy.init_node('sift_matcher')
self.cv_bridge = CvBridge()
self.rectified_image_topic = rospy.Subscriber(
image_topic,
Image,
self.new_image_callback
)
self.pub_keypoint_motion = rospy.Publisher(
'keypoint_motion',
KeypointMotion,
queue_size=10
)
self.feature_params = None
if feature_detector == 'FAST':
self.get_features = self.get_features_fast
# Initiate FAST detector with default values
self.fast = cv2.FastFeatureDetector_create()
self.fast.setThreshold(20)
elif feature_detector == 'GOOD':
self.get_features = self.get_features_good
# params for ShiTomasi 'GOOD' corner detection
self.feature_params = dict(
maxCorners=200,
qualityLevel=0.3,
minDistance=7,
blockSize=7
)
elif feature_detector == 'SIFT':
# OpenCV 3+
self.sift = cv2.xfeatures2d.SIFT_create()
else:
raise Exception(
'{} feature detector not implemented'.format(feature_detector)
)
self.last_frame_gray = None
self.good_old = None
self.good_new = None
