perception/autoware_bytetrack/lib/include/byte_tracker.h

@@ -40,6 +40,7 @@
 
 #include "strack.h"
 
+#include <limits>
 #include <vector>
 
 struct ByteTrackObject
@@ -83,8 +84,8 @@ class ByteTracker
 
   double lapjv(
     const std::vector<std::vector<float>> & cost, std::vector<int> & rowsol,
-    std::vector<int> & colsol, bool extend_cost = false, float cost_limit = LONG_MAX,
-    bool return_cost = true);
+    std::vector<int> & colsol, bool extend_cost = false,
+    float cost_limit = std::numeric_limits<float>::max(), bool return_cost = true);
 
 private:
   float track_thresh;

perception/autoware_image_projection_based_fusion/include/autoware/image_projection_based_fusion/segmentation_pointcloud_fusion/node.hpp

@@ -62,7 +62,7 @@ class SegmentPointCloudFusionNode : public FusionNode<PointCloud2, PointCloud2,
     const PointCloud2 & input_pointcloud_msg, const std::size_t image_id, const Image & input_mask,
     const CameraInfo & camera_info, PointCloud2 & output_pointcloud_msg) override;
 
-  bool out_of_scope(const PointCloud2 & filtered_cloud);
+  bool out_of_scope(const PointCloud2 & filtered_cloud) override;
   inline void copyPointCloud(
     const PointCloud2 & input, const int point_step, const size_t global_offset,
     PointCloud2 & output, size_t & output_pointcloud_size)

perception/autoware_tensorrt_common/src/tensorrt_common.cpp

@@ -315,8 +315,7 @@ void TrtCommon::printNetworkInfo(const std::string & onnx_file_path)
       total_gflops += gflops;
       total_params += num_weights;
       std::cout << "L" << i << " [conv " << k_dims.d[0] << "x" << k_dims.d[1] << " (" << groups
-                << ") "
-                << "/" << s_dims.d[0] << "] " << dim_in.d[3] << "x" << dim_in.d[2] << "x"
+                << ") " << "/" << s_dims.d[0] << "] " << dim_in.d[3] << "x" << dim_in.d[2] << "x"
                 << dim_in.d[1] << " -> " << dim_out.d[3] << "x" << dim_out.d[2] << "x"
                 << dim_out.d[1];
       std::cout << " weights:" << num_weights;
@@ -381,8 +380,7 @@ bool TrtCommon::buildEngineFromOnnx(
     if (num_available_dla > 0) {
       std::cout << "###" << num_available_dla << " DLAs are supported! ###" << std::endl;
     } else {
-      std::cout << "###Warning : "
-                << "No DLA is supported! ###" << std::endl;
+      std::cout << "###Warning : " << "No DLA is supported! ###" << std::endl;
     }
     config->setDefaultDeviceType(nvinfer1::DeviceType::kDLA);
     config->setDLACore(build_config_->dla_core_id);

planning/autoware_mission_planner/src/lanelet2_plugins/default_planner.cpp

@@ -305,8 +305,7 @@ PlannerPlugin::LaneletRoute DefaultPlanner::plan(const RoutePoints & points)
 
   std::stringstream log_ss;
   for (const auto & point : points) {
-    log_ss << "x: " << point.position.x << " "
-           << "y: " << point.position.y << std::endl;
+    log_ss << "x: " << point.position.x << " " << "y: " << point.position.y << std::endl;
   }
   RCLCPP_DEBUG_STREAM(
     logger, "start planning route with check points: " << std::endl

sensing/autoware_pointcloud_preprocessor/src/vector_map_filter/lanelet2_map_filter_node.cpp

@@ -228,9 +228,8 @@ void Lanelet2MapFilterComponent::pointcloudCallback(const PointCloud2ConstPtr cl
   if (!transformPointCloud("map", cloud_msg, input_transformed_cloud_ptr.get())) {
     RCLCPP_ERROR_STREAM_THROTTLE(
       this->get_logger(), *this->get_clock(), std::chrono::milliseconds(10000).count(),
-      "Failed transform from "
-        << "map"
-        << " to " << cloud_msg->header.frame_id);
+      "Failed transform from " << "map"
+                               << " to " << cloud_msg->header.frame_id);
     return;
   }
   pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);