本文整理汇总了Python中cv2.SimpleBlobDetector_Params方法的典型用法代码示例。如果您正苦于以下问题:Python cv2.SimpleBlobDetector_Params方法的具体用法?Python cv2.SimpleBlobDetector_Params怎么用?Python cv2.SimpleBlobDetector_Params使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cv2
的用法示例。
在下文中一共展示了cv2.SimpleBlobDetector_Params方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: init_blob_detector
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import SimpleBlobDetector_Params [as 别名]
def init_blob_detector():
params = cv2.SimpleBlobDetector_Params()
params.minThreshold = 1
params.maxThreshold = 255
params.filterByArea = True
params.minArea = 1
params.filterByCircularity = False
params.filterByConvexity = False
params.filterByInertia = False
#detector = cv2.SimpleBlobDetector(params)
detector = cv2.SimpleBlobDetector_create(params)
return detector
示例2: init_blob_detector
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import SimpleBlobDetector_Params [as 别名]
def init_blob_detector():
params = cv2.SimpleBlobDetector_Params()
params.minThreshold = 1
params.maxThreshold = 255
params.filterByArea = True
params.minArea = 1
params.filterByCircularity = False
params.filterByConvexity = False
params.filterByInertia = False
# detector = cv2.SimpleBlobDetector(params)
detector = cv2.SimpleBlobDetector_create(params)
return detector
示例3: __init__
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import SimpleBlobDetector_Params [as 别名]
def __init__(self, args):
self.node_name = "cvBridge"
rospy.init_node(self.node_name)
# What we do during shutdown
rospy.on_shutdown(self.cleanup)
# Create the cv_bridge object
self.bridge = CvBridge()
# Subscribe to the camera image topics and set
# the appropriate callbacks
self.image_sub = rospy.Subscriber(args[1], Image, self.image_callback)
self.image_pub = rospy.Publisher(
"%s/BlobDetector" % (args[1]), Image, queue_size=10)
# Detector
# Set up the detector with parameters.
# Setup SimpleBlobDetector parameters.
params = cv2.SimpleBlobDetector_Params()
# Filter by Color.
params.filterByColor = rospy.get_param('~FilterByColor')
params.blobColor = rospy.get_param('~BlobColor')
# Filter by Area.
params.filterByArea = rospy.get_param('~FilterByArea')
params.minArea = rospy.get_param('~BlobMinArea')
params.maxArea = rospy.get_param('~BlobMaxArea')
# Filter by Circularity
params.filterByCircularity = rospy.get_param('~FilterByCircularity')
params.minCircularity = rospy.get_param('~BlobMinCircularity')
params.maxCircularity = rospy.get_param('~BlobMaxCircularity')
# Filter by Convexity
params.filterByConvexity = rospy.get_param('~FilterByConvexity')
params.minConvexity = rospy.get_param('~BlobMinConvexity')
params.maxConvexity = rospy.get_param('~BlobMaxConvexity')
# Filter by Inertia
params.filterByInertia = rospy.get_param('~FilterByInertia')
params.minInertiaRatio = rospy.get_param('~BlobMinInertia')
params.maxInertiaRatio = rospy.get_param('~BlobMaxInertia')
self.MaxLeavesSocketA = [0]
self.MaxLeavesSocketB = [0]
self.MaxLeavesSocketC = [0]
self.MaxLeavesSocketD = [0]
self.MaxLeavesSocketE = [0]
self.MaxLeavesSocketF = [0]
self.detector = cv2.SimpleBlobDetector(params)
rospy.loginfo("Waiting for image topics...")
示例4: __init__
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import SimpleBlobDetector_Params [as 别名]
def __init__(self,
pattern_type,
pattern_rows,
pattern_columns,
distance_in_world_units = 1.0,
figsize = (8,8),
debug_dir = None,
term_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.001)
):
pattern_types = ["chessboard","symmetric_circles","asymmetric_circles","custom"]
assert pattern_type in pattern_types, "pattern type must be one of {}".format(pattern_types)
self.pattern_type = pattern_type
self.pattern_rows = pattern_rows
self.pattern_columns = pattern_columns
self.distance_in_world_units = distance_in_world_units
self.figsize = figsize
self.debug_dir = debug_dir
self.term_criteria = term_criteria
self.subpixel_refinement = True #turn on or off subpixel refinement
# on for chessboard
# off for circular objects
# set accordingly for custom pattern
# NOTE: turining on subpixel refinement for circles gives a very high
# reprojection error.
if self.pattern_type in ["asymmetric_circles","symmetric_circles"]:
self.subpixel_refinement = False
self.use_clustering = True
# Setup Default SimpleBlobDetector parameters.
self.blobParams = cv2.SimpleBlobDetector_Params()
# Change thresholds
self.blobParams.minThreshold = 8
self.blobParams.maxThreshold = 255
# Filter by Area.
self.blobParams.filterByArea = True
self.blobParams.minArea = 50 # minArea may be adjusted to suit for your experiment
self.blobParams.maxArea = 10e5 # maxArea may be adjusted to suit for your experiment
# Filter by Circularity
self.blobParams.filterByCircularity = True
self.blobParams.minCircularity = 0.8
# Filter by Convexity
self.blobParams.filterByConvexity = True
self.blobParams.minConvexity = 0.87
# Filter by Inertia
self.blobParams.filterByInertia = True
self.blobParams.minInertiaRatio = 0.01
if self.pattern_type == "asymmetric_circles":
self.double_count_in_column = True # count the double circles in asymmetrical circular grid along the column
if self.debug_dir and not os.path.isdir(self.debug_dir):
os.mkdir(self.debug_dir)
print("The Camera Calibration API is initialized and ready for calibration...")
示例5: analyse_frame
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import SimpleBlobDetector_Params [as 别名]
def analyse_frame(self,frame):
balloon_found = False
balloon_x = 0
balloon_y = 0
balloon_radius = 0
# Convert BGR to HSV
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Threshold the HSV image
mask = cv2.inRange(hsv, self.filter_low, self.filter_high)
# Erode
erode_kernel = numpy.ones((3,3),numpy.uint8);
eroded_img = cv2.erode(mask,erode_kernel,iterations = 1)
# dilate
dilate_kernel = numpy.ones((10,10),numpy.uint8);
dilate_img = cv2.dilate(eroded_img,dilate_kernel,iterations = 1)
# blog detector
blob_params = cv2.SimpleBlobDetector_Params()
blob_params.minDistBetweenBlobs = 50
blob_params.filterByInertia = False
blob_params.filterByConvexity = False
blob_params.filterByColor = True
blob_params.blobColor = 255
blob_params.filterByCircularity = False
blob_params.filterByArea = False
#blob_params.minArea = 20
#blob_params.maxArea = 500
blob_detector = cv2.SimpleBlobDetector_create(blob_params)
keypts = blob_detector.detect(dilate_img)
# draw centers of all keypoints in new image
#blob_img = cv2.drawKeypoints(frame, keypts, color=(0,255,0), flags=0)
# find largest blob
if len(keypts) > 0:
kp_max = keypts[0]
for kp in keypts:
if kp.size > kp_max.size:
kp_max = kp
# draw circle around the largest blob
cv2.circle(frame,(int(kp_max.pt[0]),int(kp_max.pt[1])),int(kp_max.size),(0,255,0),2)
# set the balloon location
balloon_found = True
balloon_x = kp_max.pt[0]
balloon_y = kp_max.pt[1]
balloon_radius = kp_max.size
# return results
return balloon_found, balloon_x, balloon_y, balloon_radius
# add_artificial_horizon - adds artificial horizon to an image using the vehicle's attitude