self.model_path = self.get_parameter("model_path").value
         self.model_config_path = self.get_parameter("model_config_path").value
         self.lidar_data = self.get_parameter("lidar_topic").value
-        self.publish_detection = self.get_parameter('detection_options.enable_detection').get_parameter_value().bool_value
+        self.publish_detection = self.get_parameter(
+            'detection_options.enable_detection').get_parameter_value().bool_value
 
         self.viz_publisher = self.create_publisher(MarkerArray, "/lidar_detections_viz", 10)
         self.detections_publisher = self.create_publisher(Detection3DArray, "/lidar_detections", 10)

                 detected_object.hypothesis.score = float(pred_dicts[0]["pred_scores"][idx])
                 detection.results.append(detected_object)
                 detections.detections.append(detection)
-        
+
         if self.publish_detection:
             self.viz_publisher.publish(marker_array)
         self.detections_publisher.publish(detections)

         cfg_from_yaml_file(args.cfg_file, cfg)
         return args, cfg
 
+
 class LidarDatalodaer(DatasetTemplate):
     def __init__(self, dataset_cfg, class_names, training=True, logger=None, ext=".bin"):
         super().__init__(
             dataset_cfg=dataset_cfg, class_names=class_names, training=training, logger=logger
         )
+
 
 def main(args=None):
     rclpy.init(args=args)