style(pre-commit): autofix

perception/autoware_tensorrt_rtmdet/README.md

@@ -12,13 +12,13 @@ bicycles, etc. in a scene. This package provides a ROS2 interface for RTMDet usi
 ### Input
 
 | Name       | Type                | Description     |
-|------------|---------------------|-----------------|
+| ---------- | ------------------- | --------------- |
 | `in/image` | `sensor_msgs/Image` | The input image |
 
 ### Output
 
 | Name              | Type                                               | Description                                                         |
-|-------------------|----------------------------------------------------|---------------------------------------------------------------------|
+| ----------------- | -------------------------------------------------- | ------------------------------------------------------------------- |
 | `out/objects`     | `tier4_perception_msgs/DetectedObjectsWithFeature` | The detected objects with 2D bounding boxes and scores              |
 | `out/mask`        | `autoware_internal_msgs/SegmentationMask`          | The instance segmentation mask                                      |
 | `out/color_mask`  | `sensor_msgs/Image`                                | The colorized image of instance segmentation mask for visualization |
@@ -64,4 +64,4 @@ archivePrefix={arXiv},
 primaryClass={cs.CV},
 url={https://arxiv.org/abs/2212.07784},
 }
-```
+```

perception/autoware_tensorrt_rtmdet/include/tensorrt_rtmdet/tensorrt_rtmdet.hpp

@@ -78,11 +78,13 @@ class TrtRTMDet
 
   ~TrtRTMDet();
 
-  bool doInference(const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask, std::vector<uint8_t> &class_ids);
+  bool doInference(
+    const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask,
+    std::vector<uint8_t> & class_ids);
 
   bool doInferenceWithRoi(
-    const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask, std::vector<uint8_t> &class_ids,
-    const std::vector<cv::Rect> & roi);
+    const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask,
+    std::vector<uint8_t> & class_ids, const std::vector<cv::Rect> & roi);
 
   bool doMultiScaleInference(
     const cv::Mat & image, ObjectArrays & objects, const std::vector<cv::Rect> & roi);
@@ -109,7 +111,9 @@ class TrtRTMDet
 
   bool multiScaleFeedforward(const cv::Mat & image, int batch_size, ObjectArrays & objects);
 
-  bool feedforward(const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask, std::vector<uint8_t> &class_ids);
+  bool feedforward(
+    const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask,
+    std::vector<uint8_t> & class_ids);
 
   void readColorMap(const std::string & color_map_path);
 

perception/autoware_tensorrt_rtmdet/include/tensorrt_rtmdet/tensorrt_rtmdet_node.hpp

@@ -22,8 +22,8 @@
 #include <image_transport/image_transport.hpp>
 #include <rclcpp/rclcpp.hpp>
 
-#include "autoware_internal_msgs/msg/segmentation_mask.hpp"
 #include "autoware_internal_msgs/msg/segmentation_config.hpp"
+#include "autoware_internal_msgs/msg/segmentation_mask.hpp"
 #include "tier4_perception_msgs/msg/detected_object_with_feature.hpp"
 #include "tier4_perception_msgs/msg/detected_objects_with_feature.hpp"
 #include "tier4_perception_msgs/msg/feature.hpp"

perception/autoware_tensorrt_rtmdet/package.xml

@@ -16,8 +16,8 @@
   <buildtool_export_depend>cudnn_cmake_module</buildtool_export_depend>
   <buildtool_export_depend>tensorrt_cmake_module</buildtool_export_depend>
 
-  <depend>autoware_perception_msgs</depend>
   <depend>autoware_internal_msgs</depend>
+  <depend>autoware_perception_msgs</depend>
   <depend>cuda_utils</depend>
   <depend>cv_bridge</depend>
   <depend>image_transport</depend>

perception/autoware_tensorrt_rtmdet/src/tensorrt_rtmdet.cpp

@@ -319,7 +319,8 @@ void TrtRTMDet::preprocess(const std::vector<cv::Mat> & images)
 }
 
 bool TrtRTMDet::doInference(
-  const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask, std::vector<uint8_t> &class_ids)
+  const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask,
+  std::vector<uint8_t> & class_ids)
 {
   if (!trt_common_->isInitialized()) {
     return false;
@@ -549,8 +550,8 @@ void TrtRTMDet::multiScalePreprocess(const cv::Mat & image, const std::vector<cv
 }
 
 bool TrtRTMDet::doInferenceWithRoi(
-  const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask, std::vector<uint8_t> &class_ids,
-  const std::vector<cv::Rect> & rois)
+  const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask,
+  std::vector<uint8_t> & class_ids, const std::vector<cv::Rect> & rois)
 {
   if (!trt_common_->isInitialized()) {
     return false;
@@ -579,7 +580,8 @@ bool TrtRTMDet::doMultiScaleInference(
 }
 
 bool TrtRTMDet::feedforward(
-  const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask, std::vector<uint8_t> &class_ids)
+  const std::vector<cv::Mat> & images, ObjectArrays & objects, cv::Mat & mask,
+  std::vector<uint8_t> & class_ids)
 {
   std::vector<void *> buffers = {
     input_d_.get(), out_dets_d_.get(), out_labels_d_.get(), out_masks_d_.get()};
@@ -635,7 +637,7 @@ bool TrtRTMDet::feedforward(
   // The intensity of each pixel corresponds to the index of the class_array,
   // which stores the class IDs.
   mask = cv::Mat(model_input_height_, model_input_width_, CV_8UC3, cv::Scalar(0, 0, 0));
-  uint8_t pixel_intensity = 1; // 0 is reserved for background
+  uint8_t pixel_intensity = 1;  // 0 is reserved for background
   for (size_t batch = 0; batch < batch_size; ++batch) {
     for (const auto & object : objects[batch]) {
       cv::Mat object_mask(
@@ -653,9 +655,7 @@ bool TrtRTMDet::feedforward(
         int j = position[1];
 
         if (object_mask.at<uchar>(i, j) > static_cast<int>(255 * mask_threshold_)) {
-          cv::Vec3b color(
-            pixel_intensity, pixel_intensity,
-            pixel_intensity);
+          cv::Vec3b color(pixel_intensity, pixel_intensity, pixel_intensity);
           pixel = color;
         }
       };

perception/autoware_tensorrt_rtmdet/src/tensorrt_rtmdet_node.cpp

@@ -82,7 +82,8 @@ TrtRTMDetNode::TrtRTMDetNode(const rclcpp::NodeOptions & node_options)
 
   objects_pub_ = this->create_publisher<tier4_perception_msgs::msg::DetectedObjectsWithFeature>(
     "~/out/objects", 1);
-  mask_pub_ = this->create_publisher<autoware_internal_msgs::msg::SegmentationMask>("~/out/mask", 1);
+  mask_pub_ =
+    this->create_publisher<autoware_internal_msgs::msg::SegmentationMask>("~/out/mask", 1);
 
   color_mask_pub_ = image_transport::create_publisher(this, "~/out/color_mask");
   debug_image_pub_ = image_transport::create_publisher(this, "~/out/debug_image");
@@ -97,7 +98,8 @@ void TrtRTMDetNode::onConnect()
 {
   using std::placeholders::_1;
   if (
-    debug_image_pub_.getNumSubscribers() == 0 && mask_pub_->get_intra_process_subscription_count() == 0 &&
+    debug_image_pub_.getNumSubscribers() == 0 &&
+    mask_pub_->get_intra_process_subscription_count() == 0 &&
     color_mask_pub_.getNumSubscribers() == 0 && objects_pub_->get_subscription_count() == 0 &&
     objects_pub_->get_intra_process_subscription_count() == 0) {
     image_sub_.shutdown();