feat(centerpoint): update ceterpoint (autowarefoundation#145)

* fix(lidar_centerpoint): fix function sigmoid() (autowarefoundation#1555) fix(lidar_centerpoint): fix function sigmoid() (autowarefoundation#1545) Signed-off-by: WfHit <33973397+WfHit@users.noreply.github.com> * feat(lidar_centerpoint): add score threshold parameter to center point (autowarefoundation#1699) Signed-off-by: scepter914 <scepter914@gmail.com> Signed-off-by: scepter914 <scepter914@gmail.com> * feat(behavior_path_planner): add new turn signal algorithm (autowarefoundation#1964) * clean code Signed-off-by: yutaka <purewater0901@gmail.com> * clean format Signed-off-by: yutaka <purewater0901@gmail.com> * udpate Signed-off-by: yutaka <purewater0901@gmail.com> * update Signed-off-by: yutaka <purewater0901@gmail.com> * update Signed-off-by: yutaka <purewater0901@gmail.com> * update Signed-off-by: yutaka <purewater0901@gmail.com> * update Signed-off-by: yutaka <purewater0901@gmail.com> * add test Signed-off-by: yutaka <purewater0901@gmail.com> * add test * add test Signed-off-by: yutaka <purewater0901@gmail.com> * fix(avoidance): use new turn signal algorithm Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com> * fix(avoidance): fix desired_start_point position Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com> * update Signed-off-by: yutaka <purewater0901@gmail.com> * change policy Signed-off-by: yutaka <purewater0901@gmail.com> * feat(behavior_path_planner): update pull_over for new blinker logic Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * feat(behavior_path_planner): update pull_out for new blinker logic * tmp: install flask via pip Signed-off-by: Takayuki Murooka <takayuki5168@gmail.com> * feat(lane_change): added lane change point * fix start_point and non backward driving turn signal Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * get 3 second during constructing lane change path Signed-off-by: Muhammad Zulfaqar Azmi <zulfaqar.azmi@tier4.jp> * fix pull over desired start point Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> * update Signed-off-by: yutaka <purewater0901@gmail.com> * delete Signed-off-by: yutaka <purewater0901@gmail.com> * Update Readme * Update planning/behavior_path_planner/src/scene_module/avoidance/avoidance_module.cpp Co-authored-by: Fumiya Watanabe <rej55.g@gmail.com> * Update planning/behavior_path_planner/src/scene_module/avoidance/avoidance_module.cpp Co-authored-by: Fumiya Watanabe <rej55.g@gmail.com> * fix format Signed-off-by: yutaka <purewater0901@gmail.com> Signed-off-by: yutaka <purewater0901@gmail.com> Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com> Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> Signed-off-by: Takayuki Murooka <takayuki5168@gmail.com> Signed-off-by: Muhammad Zulfaqar Azmi <zulfaqar.azmi@tier4.jp> Co-authored-by: Satoshi OTA <44889564+satoshi-ota@users.noreply.github.com> Co-authored-by: satoshi-ota <satoshi.ota928@gmail.com> Co-authored-by: kosuke55 <kosuke.tnp@gmail.com> Co-authored-by: Takayuki Murooka <takayuki5168@gmail.com> Co-authored-by: Muhammad Zulfaqar Azmi <zulfaqar.azmi@tier4.jp> Co-authored-by: Fumiya Watanabe <rej55.g@gmail.com> Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> * fix(lidar_centerpoint): include zero in range of yaw_norm_threshold (autowarefoundation#1830) Signed-off-by: Shin-kyoto <58775300+Shin-kyoto@users.noreply.github.com> Signed-off-by: Shin-kyoto <58775300+Shin-kyoto@users.noreply.github.com> * feat(multi_object_tracker): increase max-area for truck and trailer (autowarefoundation#1710) * feat(multi_object_tracker): increase max-area for truck Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * feat: change truck and trailer max-area gate params Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * feat: change trailer params Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> * feat(multi_object_tracker): update bus size (autowarefoundation#1887) Signed-off-by: Yukihiro Saito <yukky.saito@gmail.com> Signed-off-by: Yukihiro Saito <yukky.saito@gmail.com> * fix(multi_object_tracker): add missing trailer tracker (autowarefoundation#1885) Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * feat(lidar_centerpoint): implemented a class remapping according to the detections shape (autowarefoundation#1876) * Implemented a small package to remap detection classes depending on their shape Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Update perception/detection_class_adapter/include/detection_class_adapter/detection_class_adapter.hpp Co-authored-by: Yukihiro Saito <yukky.saito@gmail.com> * Removed the hardcoded mapping from centerpoint and pointfusion. Fixed the description of the config file Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Deleted the new package and moved the logic to centerpoint Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Update perception/lidar_centerpoint/config/detection_class_adapter.param.yaml Co-authored-by: Yusuke Muramatsu <yukke42@users.noreply.github.com> * Changed: adapter->remapper * Update perception/lidar_centerpoint/lib/detection_class_remapper.cpp Co-authored-by: Yukihiro Saito <yukky.saito@gmail.com> * Delted duplicated file Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Modified the parameters to match autowarefoundation#1710 Now we do not map cars to buses no mather the size Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Update perception/lidar_centerpoint/config/detection_class_remapper.param.yaml Co-authored-by: Yusuke Muramatsu <yukke42@users.noreply.github.com> Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> Co-authored-by: Yukihiro Saito <yukky.saito@gmail.com> Co-authored-by: Yusuke Muramatsu <yukke42@users.noreply.github.com> Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> * feat(lidar_centerpoint): add IoU-based NMS (autowarefoundation#1935) * feat(lidar_centerpoint): add IoU-based NMS Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * feat: add magic number name Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * feat: remove unnecessary headers Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * fix: typo Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * fix: typo Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> * feat(lidar_centerpoint): enabled per class yaw norm threshold (autowarefoundation#1962) * feat(lidar_centerpoint): enabled per class yaw norm threshold Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Updated thresholds Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Moved the yaw threshold parameters to gpu memory Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> * Moved the thresholds as a member variable Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> * fix(lidar_centeproint): fix cmake Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> * revert(lidar_centerpoint): "fix(lidar_centeproint): fix cmake" This reverts commit 2efc31d. Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * chore(lidar_centerpoint): add trained model of centerpoint (autowarefoundation#1202) * chore(lidar_centerpoint): add trained model of centerpoint Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> * docs: add description of models Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: WfHit <33973397+WfHit@users.noreply.github.com> Signed-off-by: scepter914 <scepter914@gmail.com> Signed-off-by: yutaka <purewater0901@gmail.com> Signed-off-by: satoshi-ota <satoshi.ota928@gmail.com> Signed-off-by: kosuke55 <kosuke.tnp@gmail.com> Signed-off-by: Takayuki Murooka <takayuki5168@gmail.com> Signed-off-by: Muhammad Zulfaqar Azmi <zulfaqar.azmi@tier4.jp> Signed-off-by: tomoya.kimura <tomoya.kimura@tier4.jp> Signed-off-by: Shin-kyoto <58775300+Shin-kyoto@users.noreply.github.com> Signed-off-by: yukke42 <yusuke.muramatsu@tier4.jp> Signed-off-by: Yukihiro Saito <yukky.saito@gmail.com> Signed-off-by: Kenzo Lobos-Tsunekawa <kenzo.lobos@tier4.jp> Co-authored-by: WfHit <33973397+WfHit@users.noreply.github.com> Co-authored-by: Satoshi Tanaka <16330533+scepter914@users.noreply.github.com> Co-authored-by: Kenzo Lobos Tsunekawa <kenzo.lobos@tier4.jp> Co-authored-by: Satoshi OTA <44889564+satoshi-ota@users.noreply.github.com> Co-authored-by: satoshi-ota <satoshi.ota928@gmail.com> Co-authored-by: kosuke55 <kosuke.tnp@gmail.com> Co-authored-by: Takayuki Murooka <takayuki5168@gmail.com> Co-authored-by: Muhammad Zulfaqar Azmi <zulfaqar.azmi@tier4.jp> Co-authored-by: Fumiya Watanabe <rej55.g@gmail.com> Co-authored-by: Shintaro Tomie <58775300+Shin-kyoto@users.noreply.github.com> Co-authored-by: Yusuke Muramatsu <yukke42@users.noreply.github.com> Co-authored-by: Yukihiro Saito <yukky.saito@gmail.com> Co-authored-by: yukke42 <yusuke.muramatsu@tier4.jp>
badai-nguyen · Feb 1, 2023 · be021a9 · be021a9
1 parent 8449e72
commit be021a9
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diff --git a/...onfig/object_recognition/tracking/multi_object_tracker/data_association_matrix.param.yaml b/...onfig/object_recognition/tracking/multi_object_tracker/data_association_matrix.param.yaml
@@ -22,12 +22,14 @@
        3.0,     1.0, 1.0,   1.0,  1.0,     3.0,       3.0,     2.0,       #BICYCLE
        2.0,     1.0, 1.0,   1.0,  1.0,     3.0,       3.0,     2.0]       #PEDESTRIAN
     max_area_matrix:
+      # NOTE(yukke42): The size of truck is 12 m length x 3 m width.
+      # NOTE(yukke42): The size of trailer is 20 m length x 3 m width.
       #UNKNOWN,  CAR,      TRUCK,    BUS,      TRAILER,   MOTORBIKE, BICYCLE,  PEDESTRIAN
-      [10000.00, 10000.00, 10000.00, 10000.00, 10000.00,  10000.00,  10000.00, 10000.00,   #UNKNOWN
-          12.10,    12.10,    19.75,    40.00,    40.00,  10000.00,  10000.00, 10000.00,   #CAR
-          19.75,    12.10,    19.75,    40.00,    40.00,  10000.00,  10000.00, 10000.00,   #TRUCK
-          40.00,    12.10,    19.75,    40.00,    40.00,  10000.00,  10000.00, 10000.00,   #BUS
-          40.00,    12.10,    19.75,    40.00,    40.00,  10000.00,  10000.00, 10000.00,   #TRAILER
+        [100.00,   100.00,   100.00,   100.00,   100.00,    100.00,    100.00,   100.00,   #UNKNOWN
+          12.10,    12.10,    36.00,    60.00,    60.00,  10000.00,  10000.00, 10000.00,   #CAR
+          36.00,    12.10,    36.00,    60.00,    60.00,  10000.00,  10000.00, 10000.00,   #TRUCK
+          60.00,    12.10,    36.00,    60.00,    60.00,  10000.00,  10000.00, 10000.00,   #BUS
+          60.00,    12.10,    36.00,    60.00,    60.00,  10000.00,  10000.00, 10000.00,   #TRAILER
            2.50, 10000.00, 10000.00, 10000.00, 10000.00,      2.50,      2.50,     1.00,   #MOTORBIKE
            2.50, 10000.00, 10000.00, 10000.00, 10000.00,      2.50,      2.50,     1.00,   #BICYCLE
            2.00, 10000.00, 10000.00, 10000.00, 10000.00,      1.50,      1.50,     1.00]   #PEDESTRIAN

diff --git a/perception/image_projection_based_fusion/config/pointpainting.param.yaml b/perception/image_projection_based_fusion/config/pointpainting.param.yaml
@@ -1,10 +1,10 @@
 /**:
   ros__parameters:
     class_names: ["CAR", "PEDESTRIAN", "BICYCLE"]
-    rename_car_to_truck_and_bus: true
     point_feature_size: 6  # x, y, z and car, pedestrian, bicycle
     max_voxel_size: 40000
     point_cloud_range: [-76.8, -76.8, -3.0, 76.8, 76.8, 5.0]
     voxel_size: [0.32, 0.32, 8.0]
     downsample_factor: 1
     encoder_in_feature_size: 11
+    yaw_norm_thresholds: [0.3, 0.0, 0.3]
diff --git a/...ojection_based_fusion/include/image_projection_based_fusion/pointpainting_fusion/node.hpp b/...ojection_based_fusion/include/image_projection_based_fusion/pointpainting_fusion/node.hpp
@@ -21,6 +21,7 @@
 #include <image_projection_based_fusion/utils/geometry.hpp>
 #include <image_projection_based_fusion/utils/utils.hpp>
 #include <lidar_centerpoint/centerpoint_trt.hpp>
+#include <lidar_centerpoint/detection_class_remapper.hpp>
 
 #include <map>
 #include <memory>
@@ -52,9 +53,10 @@ class PointpaintingFusionNode : public FusionNode<sensor_msgs::msg::PointCloud2,
   float score_threshold_{0.0};
   std::vector<std::string> class_names_;
   std::vector<double> pointcloud_range;
-  bool rename_car_to_truck_and_bus_{false};
   bool has_twist_{false};
 
+  centerpoint::DetectionClassRemapper detection_class_remapper_;
+
   std::unique_ptr<image_projection_based_fusion::PointPaintingTRT> detector_ptr_{nullptr};
 
   bool out_of_scope(const DetectedObjects & obj);

diff --git a/perception/image_projection_based_fusion/launch/pointpainting_fusion.launch.xml b/perception/image_projection_based_fusion/launch/pointpainting_fusion.launch.xml
@@ -21,6 +21,7 @@
   <arg name="model_name" default="pointpainting" description="options: `pointpainting`"/>
   <arg name="model_path" default="$(find-pkg-share image_projection_based_fusion)/data"/>
   <arg name="model_param_path" default="$(find-pkg-share image_projection_based_fusion)/config/$(var model_name).param.yaml"/>
+  <arg name="class_remapper_param_path" default="$(find-pkg-share lidar_centerpoint)/config/detection_class_remapper.param.yaml"/>
 
   <!-- for eval variable-->
   <arg name="input_rois_number" default="$(var input/rois_number)"/>
@@ -74,6 +75,7 @@
       <param name="head_onnx_path" value="$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx"/>
       <param name="head_engine_path" value="$(var model_path)/pts_backbone_neck_head_$(var model_name).engine"/>
       <param from="$(var model_param_path)"/>
+      <param from="$(var class_remapper_param_path)"/>
       <param name="rois_number" value="$(var input/rois_number)"/>
 
       <!-- debug -->

diff --git a/perception/image_projection_based_fusion/src/pointpainting_fusion/node.cpp b/perception/image_projection_based_fusion/src/pointpainting_fusion/node.cpp
@@ -33,6 +33,8 @@ PointpaintingFusionNode::PointpaintingFusionNode(const rclcpp::NodeOptions & opt
     static_cast<float>(this->declare_parameter<double>("score_threshold", 0.4));
   const float circle_nms_dist_threshold =
     static_cast<float>(this->declare_parameter<double>("circle_nms_dist_threshold", 1.5));
+  const auto yaw_norm_thresholds =
+    this->declare_parameter<std::vector<double>>("yaw_norm_thresholds");
   // densification param
   const std::string densification_world_frame_id =
     this->declare_parameter("densification_world_frame_id", "map");
@@ -45,7 +47,6 @@ PointpaintingFusionNode::PointpaintingFusionNode(const rclcpp::NodeOptions & opt
   const std::string head_onnx_path = this->declare_parameter("head_onnx_path", "");
   const std::string head_engine_path = this->declare_parameter("head_engine_path", "");
   class_names_ = this->declare_parameter<std::vector<std::string>>("class_names");
-  rename_car_to_truck_and_bus_ = this->declare_parameter("rename_car_to_truck_and_bus", false);
   has_twist_ = this->declare_parameter("has_twist", false);
   const std::size_t point_feature_size =
     static_cast<std::size_t>(this->declare_parameter<std::int64_t>("point_feature_size"));
@@ -57,14 +58,22 @@ PointpaintingFusionNode::PointpaintingFusionNode(const rclcpp::NodeOptions & opt
     static_cast<std::size_t>(this->declare_parameter<std::int64_t>("downsample_factor"));
   const std::size_t encoder_in_feature_size =
     static_cast<std::size_t>(this->declare_parameter<std::int64_t>("encoder_in_feature_size"));
+  const auto allow_remapping_by_area_matrix =
+    this->declare_parameter<std::vector<int64_t>>("allow_remapping_by_area_matrix");
+  const auto min_area_matrix = this->declare_parameter<std::vector<double>>("min_area_matrix");
+  const auto max_area_matrix = this->declare_parameter<std::vector<double>>("max_area_matrix");
+
+  detection_class_remapper_.setParameters(
+    allow_remapping_by_area_matrix, min_area_matrix, max_area_matrix);
 
   centerpoint::NetworkParam encoder_param(encoder_onnx_path, encoder_engine_path, trt_precision);
   centerpoint::NetworkParam head_param(head_onnx_path, head_engine_path, trt_precision);
   centerpoint::DensificationParam densification_param(
     densification_world_frame_id, densification_num_past_frames);
   centerpoint::CenterPointConfig config(
     class_names_.size(), point_feature_size, max_voxel_size, pointcloud_range, voxel_size,
-    downsample_factor, encoder_in_feature_size, score_threshold, circle_nms_dist_threshold);
+    downsample_factor, encoder_in_feature_size, score_threshold, circle_nms_dist_threshold,
+    yaw_norm_thresholds);
 
   // create detector
   detector_ptr_ = std::make_unique<image_projection_based_fusion::PointPaintingTRT>(
@@ -237,11 +246,12 @@ void PointpaintingFusionNode::postprocess(sensor_msgs::msg::PointCloud2 & painte
       continue;
     }
     autoware_auto_perception_msgs::msg::DetectedObject obj;
-    centerpoint::box3DToDetectedObject(
-      box3d, class_names_, rename_car_to_truck_and_bus_, has_twist_, obj);
+    centerpoint::box3DToDetectedObject(box3d, class_names_, has_twist_, obj);
     output_obj_msg.objects.emplace_back(obj);
   }
 
+  detection_class_remapper_.mapClasses(output_obj_msg);
+
   obj_pub_ptr_->publish(output_obj_msg);
 }
 

diff --git a/perception/lidar_centerpoint/CMakeLists.txt b/perception/lidar_centerpoint/CMakeLists.txt
@@ -70,10 +70,12 @@ message(STATUS "start to download")
 if(TRT_AVAIL AND CUDA_AVAIL AND CUDNN_AVAIL)
 # Download trained models
   set(DATA_PATH ${CMAKE_CURRENT_SOURCE_DIR}/data)
+  set(DOWNLOAD_BASE_URL https://awf.ml.dev.web.auto/perception/models/centerpoint)
   execute_process(COMMAND mkdir -p ${DATA_PATH})
 
-  function(download FILE_NAME FILE_HASH)
-    message(STATUS "Checking and downloading ${FILE_NAME}")
+  function(download VERSION FILE_NAME FILE_HASH)
+    message(STATUS "Checking and downloading ${FILE_NAME} ")
+    set(DOWNLOAD_URL ${DOWNLOAD_BASE_URL}/${VERSION}/${FILE_NAME})
     set(FILE_PATH ${DATA_PATH}/${FILE_NAME})
     set(STATUS_CODE 0)
     message(STATUS "start ${FILE_NAME}")
@@ -86,31 +88,31 @@ if(TRT_AVAIL AND CUDA_AVAIL AND CUDNN_AVAIL)
       else()
         message(STATUS "diff ${FILE_NAME}")
         message(STATUS "File hash changes. Downloading now ...")
-        file(DOWNLOAD https://awf.ml.dev.web.auto/perception/models/${FILE_NAME} ${FILE_PATH} STATUS DOWNLOAD_STATUS TIMEOUT 300)
+        file(DOWNLOAD ${DOWNLOAD_URL} ${FILE_PATH} STATUS DOWNLOAD_STATUS TIMEOUT 300)
         list(GET DOWNLOAD_STATUS 0 STATUS_CODE)
         list(GET DOWNLOAD_STATUS 1 ERROR_MESSAGE)
       endif()
     else()
       message(STATUS "not found ${FILE_NAME}")
       message(STATUS "File doesn't exists. Downloading now ...")
-      file(DOWNLOAD https://awf.ml.dev.web.auto/perception/models/${FILE_NAME} ${FILE_PATH} STATUS DOWNLOAD_STATUS TIMEOUT 300)
+      file(DOWNLOAD ${DOWNLOAD_URL} ${FILE_PATH} STATUS DOWNLOAD_STATUS TIMEOUT 300)
       list(GET DOWNLOAD_STATUS 0 STATUS_CODE)
       list(GET DOWNLOAD_STATUS 1 ERROR_MESSAGE)
     endif()
     if(${STATUS_CODE} EQUAL 0)
       message(STATUS "Download completed successfully!")
     else()
-      message(FATAL_ERROR "Error occurred during download: ${ERROR_MESSAGE}")
+      message(FATAL_ERROR "Error occurred during download: ${ERROR_MESSAGE} ${DOWNLOAD_URL}")
     endif()
   endfunction()
 
-  # default model
-  download(pts_voxel_encoder_default.onnx 410f730c537968cb27fbd70c941849a8)
-  download(pts_backbone_neck_head_default.onnx e97c165c7877222c0e27e44409a07517)
+  # centerpoint
+  download(v1 pts_voxel_encoder_centerpoint.onnx 94dcf01ccd53ef14a79787afaada63b4)
+  download(v1 pts_backbone_neck_head_centerpoint.onnx 7046995e502e11f35c9459668d8afde3)
 
-  # aip_x2 model
-  download(pts_voxel_encoder_aip_x2.onnx 3ae5e9efd7b2ed12115e6f0b28cac58d)
-  download(pts_backbone_neck_head_aip_x2.onnx 6a406a19e05660677c162486ab332de8)
+  # centerpoint_tiny
+  download(v1 pts_voxel_encoder_centerpoint_tiny.onnx 410f730c537968cb27fbd70c941849a8)
+  download(v1 pts_backbone_neck_head_centerpoint_tiny.onnx e97c165c7877222c0e27e44409a07517)
 
   find_package(ament_cmake_auto REQUIRED)
   ament_auto_find_build_dependencies()
@@ -123,10 +125,12 @@ if(TRT_AVAIL AND CUDA_AVAIL AND CUDNN_AVAIL)
   ### centerpoint ###
   ament_auto_add_library(centerpoint_lib SHARED
     lib/centerpoint_trt.cpp
+    lib/detection_class_remapper.cpp
     lib/utils.cpp
     lib/ros_utils.cpp
     lib/network/network_trt.cpp
     lib/network/tensorrt_wrapper.cpp
+    lib/postprocess/non_maximum_suppression.cpp
     lib/preprocess/pointcloud_densification.cpp
     lib/preprocess/voxel_generator.cpp
   )

diff --git a/perception/lidar_centerpoint/README.md b/perception/lidar_centerpoint/README.md
@@ -30,21 +30,45 @@ We trained the models using <https://github.com/open-mmlab/mmdetection3d>.
 
 ### Core Parameters
 
-| Name                            | Type   | Default Value | Description                                                 |
-| ------------------------------- | ------ | ------------- | ----------------------------------------------------------- |
-| `score_threshold`               | float  | `0.4`         | detected objects with score less than threshold are ignored |
-| `densification_world_frame_id`  | string | `map`         | the world frame id to fuse multi-frame pointcloud           |
-| `densification_num_past_frames` | int    | `1`           | the number of past frames to fuse with the current frame    |
-| `trt_precision`                 | string | `fp16`        | TensorRT inference precision: `fp32` or `fp16`              |
-| `encoder_onnx_path`             | string | `""`          | path to VoxelFeatureEncoder ONNX file                       |
-| `encoder_engine_path`           | string | `""`          | path to VoxelFeatureEncoder TensorRT Engine file            |
-| `head_onnx_path`                | string | `""`          | path to DetectionHead ONNX file                             |
-| `head_engine_path`              | string | `""`          | path to DetectionHead TensorRT Engine file                  |
+| Name                            | Type         | Default Value | Description                                                   |
+| ------------------------------- | ------------ | ------------- | ------------------------------------------------------------- |
+| `score_threshold`               | float        | `0.4`         | detected objects with score less than threshold are ignored   |
+| `densification_world_frame_id`  | string       | `map`         | the world frame id to fuse multi-frame pointcloud             |
+| `densification_num_past_frames` | int          | `1`           | the number of past frames to fuse with the current frame      |
+| `trt_precision`                 | string       | `fp16`        | TensorRT inference precision: `fp32` or `fp16`                |
+| `encoder_onnx_path`             | string       | `""`          | path to VoxelFeatureEncoder ONNX file                         |
+| `encoder_engine_path`           | string       | `""`          | path to VoxelFeatureEncoder TensorRT Engine file              |
+| `head_onnx_path`                | string       | `""`          | path to DetectionHead ONNX file                               |
+| `head_engine_path`              | string       | `""`          | path to DetectionHead TensorRT Engine file                    |
+| `nms_iou_target_class_names`    | list[string] | -             | target classes for IoU-based Non Maximum Suppression          |
+| `nms_iou_search_distance_2d`    | double       | -             | If two objects are farther than the value, NMS isn't applied. |
+| `nms_iou_threshold`             | double       | -             | IoU threshold for the IoU-based Non Maximum Suppression       |
 
 ## Assumptions / Known limits
 
 - The `object.existence_probability` is stored the value of classification confidence of a DNN, not probability.
 
+## Trained Models
+
+You can download the onnx format of trained models by clicking on the links below.
+
+### Changelog
+
+#### v1 (2022/07/06)
+
+| Name               | URLs                                                                                                     | Description                                                                                                                        |
+| ------------------ | -------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------- |
+| `centerpoint`      | [pts_voxel_encoder][v1-encoder-centerpoint] <br> [pts_backbone_neck_head][v1-head-centerpoint]           | There is a single change due to the limitation in the implementation of this package. `num_filters=[32, 32]` of `PillarFeatureNet` |
+| `centerpoint_tiny` | [pts_voxel_encoder][v1-encoder-centerpoint-tiny] <br> [pts_backbone_neck_head][v1-head-centerpoint-tiny] | The same model as `default` of `v0`.                                                                                               |
+
+These changes are compared with [this configuration](https://github.com/tianweiy/CenterPoint/blob/v0.2/configs/waymo/pp/waymo_centerpoint_pp_two_pfn_stride1_3x.py).
+
+#### v0 (2021/12/03)
+
+| Name      | URLs                                                                                   | Description                                                                                                                                          |
+| --------- | -------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `default` | [pts_voxel_encoder][v0-encoder-default] <br> [pts_backbone_neck_head][v0-head-default] | There are two changes from the original CenterPoint architecture. `num_filters=[32]` of `PillarFeatureNet` and `ds_layer_strides=[2, 2, 2]` of `RPN` |
+
 ## (Optional) Error detection and handling
 
 <!-- Write how to detect errors and how to recover from them.
@@ -91,3 +115,10 @@ Example:
   Currently, this package can't handle the chattering obstacles well. We plan to add some probabilistic filters in the perception layer to improve it.
   Also, there are some parameters that should be global(e.g. vehicle size, max steering, etc.). These will be refactored and defined as global parameters so that we can share the same parameters between different nodes.
 -->
+
+[v0-encoder-default]: https://awf.ml.dev.web.auto/perception/models/pts_voxel_encoder_default.onnx
+[v0-head-default]: https://awf.ml.dev.web.auto/perception/models/pts_backbone_neck_head_default.onnx
+[v1-encoder-centerpoint]: https://awf.ml.dev.web.auto/perception/models/centerpoint/v1/pts_voxel_encoder_centerpoint.onnx
+[v1-head-centerpoint]: https://awf.ml.dev.web.auto/perception/models/centerpoint/v1/pts_backbone_neck_head_centerpoint.onnx
+[v1-encoder-centerpoint-tiny]: https://awf.ml.dev.web.auto/perception/models/centerpoint/v1/pts_voxel_encoder_centerpoint_tiny.onnx
+[v1-head-centerpoint-tiny]: https://awf.ml.dev.web.auto/perception/models/centerpoint/v1/pts_backbone_neck_head_centerpoint_tiny.onnx
diff --git a/perception/lidar_centerpoint/config/aip_x2.param.yaml b/perception/lidar_centerpoint/config/aip_x2.param.yaml
diff --git a/perception/lidar_centerpoint/config/centerpoint.param.yaml b/perception/lidar_centerpoint/config/centerpoint.param.yaml
@@ -0,0 +1,15 @@
+/**:
+  ros__parameters:
+    class_names: ["CAR", "PEDESTRIAN", "BICYCLE"]
+    point_feature_size: 4
+    max_voxel_size: 40000
+    point_cloud_range: [-89.6, -89.6, -3.0, 89.6, 89.6, 5.0]
+    voxel_size: [0.32, 0.32, 8.0]
+    downsample_factor: 1
+    encoder_in_feature_size: 9
+    # post-process params
+    circle_nms_dist_threshold: 0.5
+    iou_nms_target_class_names: ["CAR"]
+    iou_nms_search_distance_2d: 10.0
+    iou_nms_threshold: 0.1
+    yaw_norm_thresholds: [0.3, 0.0, 0.3]
diff --git a/...dar_centerpoint/config/default.param.yaml → ...rpoint/config/centerpoint_tiny.param.yaml b/...dar_centerpoint/config/default.param.yaml → ...rpoint/config/centerpoint_tiny.param.yaml
@@ -1,10 +1,15 @@
 /**:
   ros__parameters:
     class_names: ["CAR", "PEDESTRIAN", "BICYCLE"]
-    rename_car_to_truck_and_bus: true
     point_feature_size: 4
     max_voxel_size: 40000
     point_cloud_range: [-89.6, -89.6, -3.0, 89.6, 89.6, 5.0]
     voxel_size: [0.32, 0.32, 8.0]
     downsample_factor: 2
     encoder_in_feature_size: 9
+    # post-process params
+    circle_nms_dist_threshold: 0.5
+    iou_nms_target_class_names: ["CAR"]
+    iou_nms_search_distance_2d: 10.0
+    iou_nms_threshold: 0.1
+    yaw_norm_thresholds: [0.3, 0.0, 0.3]