class ObjectDetectionNode:
def __init__(self):
self.node_name = "Object Detection"
self.active = True
# Detector Configuration
rospack = rospkg.RosPack()
self.configuration = rospy.get_param(
'~object_detector') # TODO: On-the-fly reconfiguration
# TODO: Fix after a place for inference models is established
self.object_detector = ObjectDetector(
path.join(rospack.get_path('object_detection'),
self.configuration['inference_graph_path']),
float(self.configuration['score_threshold']),
bool(self.configuration['denormalize_boundingbox']))
# Subscribers
self.sub_image = rospy.Subscriber("~image_compressed",
CompressedImage,
self.on_image_received,
queue_size=1)
# Publishers
self.pub_detection = rospy.Publisher("~detections",
ObjectDetectionList,
queue_size=1)
# timer for updating the params
# self.timer = rospy.Timer(rospy.Duration.from_sec(1.0), self.updateParams)
def on_image_received(self, compressed_image):
detections = self.object_detector.detect(
rgb_from_ros(compressed_image))
if len(detections) > 0:
detection_list_msg = ObjectDetectionList()
for detection in detections:
detection_list_msg.detections.append(
Detection(class_label=detection['class_label'],
class_id=detection['class_id'],
xmin=detection['xmin'],
xmax=detection['xmax'],
ymin=detection['ymin'],
ymax=detection['ymax'],
score=detection['score']))
self.pub_detection.publish(detection_list_msg)
def onShutdown(self):
self.object_detector.finalize()
rospy.loginfo("[ObjectDetectionNode] Shutdown.")
def loginfo(self, s):
rospy.loginfo('[%s] %s' % (self.node_name, s))
