def __init__(self, node_name):
ROS2OpenCV.__init__(self, node_name)
self.node_name = node_name
self.auto_face_tracking = rospy.get_param("~auto_face_tracking", True)
self.use_haar_only = rospy.get_param("~use_haar_only", False)
self.use_depth_for_detection = rospy.get_param(
"~use_depth_for_detection", False)
self.fov_width = rospy.get_param("~fov_width", 1.094)
self.fov_height = rospy.get_param("~fov_height", 1.094)
self.max_face_size = rospy.get_param("~max_face_size", 0.28)
self.use_depth_for_tracking = rospy.get_param(
"~use_depth_for_tracking", False)
self.auto_min_features = rospy.get_param("~auto_min_features", True)
self.min_features = rospy.get_param(
"~min_features", 50) # Used only if auto_min_features is False
self.abs_min_features = rospy.get_param("~abs_min_features", 6)
self.std_err_xy = rospy.get_param("~std_err_xy", 2.5)
self.pct_err_z = rospy.get_param("~pct_err_z", 0.42)
self.max_mse = rospy.get_param("~max_mse", 10000)
self.good_feature_distance = rospy.get_param("~good_feature_distance",
5)
self.add_feature_distance = rospy.get_param("~add_feature_distance",
10)
self.flip_image = rospy.get_param("~flip_image", False)
self.feature_type = rospy.get_param(
"~feature_type", 0) # 0 = Good Features to Track, 1 = SURF
self.expand_roi_init = rospy.get_param("~expand_roi", 1.02)
self.expand_roi = self.expand_roi_init
self.camera_frame_id = "kinect_depth_optical_frame"
self.cog_x = self.cog_y = 0
self.cog_z = -1
self.detect_box = None
self.track_box = None
self.features = []
self.grey = None
self.pyramid = None
self.small_image = None
""" Set up the face detection parameters """
self.cascade_frontal_alt = rospy.get_param("~cascade_frontal_alt", "")
self.cascade_frontal_alt2 = rospy.get_param("~cascade_frontal_alt2",
"")
self.cascade_profile = rospy.get_param("~cascade_profile", "")
self.cascade_frontal_alt = cv.Load(self.cascade_frontal_alt)
self.cascade_frontal_alt2 = cv.Load(self.cascade_frontal_alt2)
self.cascade_profile = cv.Load(self.cascade_profile)
self.min_size = (20, 20)
self.image_scale = 2
self.haar_scale = 1.5
self.min_neighbors = 1
self.haar_flags = cv.CV_HAAR_DO_CANNY_PRUNING
self.grey = None
self.pyramid = None
""" Set the Good Features to Track and Lucas-Kanade parameters """
self.night_mode = False
self.quality = 0.01
self.win_size = 10
self.max_count = 200
self.block_size = 3
self.use_harris = False
self.flags = 0
self.frame_count = 0
""" Set the SURF parameters """
self.surf_hessian_quality = rospy.get_param("~surf_hessian_quality",
100)
""" A service to handle 'keystroke' commands sent from other nodes """
self.key_command = None
rospy.Service('~key_command', KeyCommand, self.key_command_callback)
""" A service to allow setting the ROI to track """
rospy.Service('~set_roi', SetROI, self.set_roi_callback)
""" Wait until the image topics are ready before starting """
rospy.wait_for_message(self.input_rgb_image, Image)
if self.use_depth_for_detection or self.use_depth_for_tracking:
rospy.wait_for_message(self.input_depth_image, Image)
def __init__(self, node_name):
ROS2OpenCV.__init__(self, node_name)
self.node_name = node_name
self.auto_face_tracking = rospy.get_param("~auto_face_tracking", True)
self.use_haar_only = rospy.get_param("~use_haar_only", False)
self.use_depth_for_detection = rospy.get_param("~use_depth_for_detection", False)
# Classic Kinnect FOV is 57.8° = 1.008 radians
self.fov_width = rospy.get_param("~fov_width", 1.094)
self.fov_height = rospy.get_param("~fov_height", 1.094)
self.max_face_size = rospy.get_param("~max_face_size", 0.28)
self.use_depth_for_tracking = rospy.get_param("~use_depth_for_tracking", False)
self.auto_min_features = rospy.get_param("~auto_min_features", True)
self.min_features = rospy.get_param("~min_features", 50) # Used only if auto_min_features is False
self.abs_min_features = rospy.get_param("~abs_min_features", 6)
self.std_err_xy = rospy.get_param("~std_err_xy", 2.5)
self.pct_err_z = rospy.get_param("~pct_err_z", 0.42)
self.max_mse = rospy.get_param("~max_mse", 10000)
self.good_feature_distance = rospy.get_param("~good_feature_distance", 5)
self.add_feature_distance = rospy.get_param("~add_feature_distance", 10)
self.flip_image = rospy.get_param("~flip_image", False)
self.feature_type = rospy.get_param("~feature_type", 0) # 0 = Good Features to Track, 1 = SURF
self.expand_roi_init = rospy.get_param("~expand_roi", 1.02)
self.expand_roi = self.expand_roi_init
self.camera_frame_id = "kinect_depth_optical_frame"
self.cog_x = self.cog_y = 0
self.cog_z = -1
self.detect_box = FacesRegistry()
self.track_box = None
self.features = []
self.grey = None
self.pyramid = None
self.small_image = None
self.frame_count = 0
""" Set up the face detection parameters """
self.cascade_frontal_alt = rospy.get_param("~cascade_frontal_alt", "")
# optional for Face detection
self.cascade_frontal_alt2 = rospy.get_param("~cascade_frontal_alt2", False)
self.cascade_profile = rospy.get_param("~cascade_profile", False)
self.cascade_frontal_alt = cv.Load(self.cascade_frontal_alt)
if self.cascade_frontal_alt2:
self.cascade_frontal_alt2 = cv.Load(self.cascade_frontal_alt2)
if self.cascade_profile:
self.cascade_profile = cv.Load(self.cascade_profile)
self.min_size = (20, 20)
self.image_scale = 2
self.haar_scale = 1.2
self.min_neighbors = 1
self.haar_flags = cv.CV_HAAR_DO_CANNY_PRUNING
self.grey = None
self.pyramid = None
""" Set the Good Features to Track and Lucas-Kanade parameters """
self.night_mode = False
self.quality = 0.01
self.win_size = 10
self.max_count = 200
self.block_size = 3
self.use_harris = False
self.flags = 0
""" Set the SURF parameters """
self.surf_hessian_quality = rospy.get_param("~surf_hessian_quality", 100)
""" A service to handle 'keystroke' commands sent from other nodes """
self.key_command = None
rospy.Service('~key_command', KeyCommand, self.key_command_callback)
""" Wait until the image topics are ready before starting """
rospy.wait_for_message(self.input_rgb_image, Image)
if self.use_depth_for_detection or self.use_depth_for_tracking:
rospy.wait_for_message(self.input_depth_image, Image)
def __init__(self, node_name):
ROS2OpenCV.__init__(self, node_name)
self.node_name = node_name
self.auto_face_tracking = rospy.get_param("~auto_face_tracking", True)
self.use_haar_only = rospy.get_param("~use_haar_only", False)
self.use_depth_for_detection = rospy.get_param("~use_depth_for_detection", False)
self.fov_width = rospy.get_param("~fov_width", 1.094)
self.fov_height = rospy.get_param("~fov_height", 1.094)
self.max_face_size = rospy.get_param("~max_face_size", 0.28)
self.use_depth_for_tracking = rospy.get_param("~use_depth_for_tracking", False)
self.auto_min_features = rospy.get_param("~auto_min_features", True)
self.min_features = rospy.get_param("~min_features", 50) # Used only if auto_min_features is False
self.abs_min_features = rospy.get_param("~abs_min_features", 6)
self.std_err_xy = rospy.get_param("~std_err_xy", 2.5)
self.max_mse = rospy.get_param("~max_mse", 10000)
self.good_feature_distance = rospy.get_param("~good_feature_distance", 5)
self.add_feature_distance = rospy.get_param("~add_feature_distance", 10)
self.flip_image = rospy.get_param("~flip_image", False)
self.feature_type = rospy.get_param("~feature_type", 0) # 0 = Good Features to Track, 1 = SURF
self.expand_scale = 1.1
self.detect_box = None
self.track_box = None
self.features = []
self.grey = None
self.pyramid = None
""" Set up the face detection parameters """
self.cascade_frontal_alt = rospy.get_param("~cascade_frontal_alt", "")
self.cascade_frontal_alt2 = rospy.get_param("~cascade_frontal_alt2", "")
self.cascade_profile = rospy.get_param("~cascade_profile", "")
self.cascade_frontal_alt = cv.Load(self.cascade_frontal_alt)
self.cascade_frontal_alt2 = cv.Load(self.cascade_frontal_alt2)
self.cascade_profile = cv.Load(self.cascade_profile)
self.min_size = (20, 20)
self.image_scale = 2
self.haar_scale = 1.5
self.min_neighbors = 1
self.haar_flags = cv.CV_HAAR_DO_CANNY_PRUNING
self.grey = None
self.pyramid = None
""" Set the Good Features to Track and Lucas-Kanade parameters """
self.night_mode = False
self.quality = 0.01
self.win_size = 10
self.max_count = 200
self.flags = 0
self.frame_count = 0
""" Set the SURF parameters """
self.surf_hessian_quality = rospy.get_param("~surf_hessian_quality", 100)
""" Wait until the image topics are ready before starting """
rospy.wait_for_message(self.input_rgb_image, Image)
if self.use_depth_for_detection or self.use_depth_for_tracking:
rospy.wait_for_message(self.input_depth_image, Image)
