def __init__(self, node_name, sub_topic, pub_topic):
self.bridge = CvBridge()
self.img_proc = ImagePreprocessor()
# Publishers
#self.
rospy.init_node(node_name)
# Crop parameters
self.above = rospy.get_param("/asv_lane_track/lane_detection_node/above", 0.35)
self.below = rospy.get_param("/asv_lane_track/lane_detection_node/below", 0.1)
self.side = rospy.get_param("/asv_lane_track/lane_detection_node/side", 0)
# Lane tracking parameters
self.deviation = rospy.get_param("/asv_lane_track/lane_detection_node/deviation", 15)
self.border = rospy.get_param("/asv_lane_track/lane_detection_node/border", 0)
# Canny parameters
self.low_thresh = rospy.get_param("/asv_lane_track/lane_detection_node/low_threshold", 50)
self.high_thresh = rospy.get_param("/asv_lane_track/lane_detection_node/high_threshold", 150)
self.aperture = rospy.get_param("/asv_lane_track/lane_detection_node/aperture", 3)
self.image_sub = rospy.Subscriber(sub_topic, Image, self.img_callback)
self.image_pub = rospy.Publisher(pub_topic, Image, queue_size=5)
self.yellow_masked_pub = rospy.Publisher("/yellow_masked", Image, queue_size=5)
self.gray_pub = rospy.Publisher("/test", Image, queue_size=5)
self.blur_pub = rospy.Publisher("/blur", Image, queue_size=5)
self.left_lines = deque(maxlen=QUEUE_LENGTH)
self.right_lines = deque(maxlen=QUEUE_LENGTH)
rospy.spin()
def get_dataset(self, image_dir):
"""
:param image_dir:
:return:
"""
preporcessor = ImagePreprocessor(resize_ratio=.75)
dataset = Mot17Tracking(root=image_dir, transform=preporcessor)
return dataset
def get(self, images_dir):
# Market150 dataset size is 64 width, height is 128, so we maintain the aspect ratio
# NOTE: for some reason oly 224 / 224 works, any other shape results in NAN
dataset = Market1501TripletDataset(images_dir,
min_img_size_h=256,
min_img_size_w=128)
processor = ImagePreprocessor(min_img_size_h=dataset.min_img_size_h,
min_img_size_w=dataset.min_img_size_w,
original_height=dataset.original_height,
original_width=dataset.original_width)
dataset.preprocessor = processor
return dataset
def __init__(self):
self.preprocessor = ImagePreprocessor()
# each of these attributes that start with show_ will be
# turned into booleans
self.show_contours = (False, 'Show all found contours')
self.show_toosmall = (False, 'Show too small contours')
self.show_horizontal = (True, 'Show horizontal targets')
self.show_vertical = (True, 'Show vertical targets')
self.show_aspect = (False, 'Show aspect ratios')
self.show_rectangularity = (False, 'Show rectangularity')
self.show_hot = (True, 'Show hot targets')
self.show_hot_text = (True, 'Show hot text')
