Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Signed-off-by: tzhong518 <[email protected]>
- Loading branch information
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,200 @@ | ||
| // Copyright 2021 TIER IV, Inc. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
||
| #include "lidar_centerpoint/node.hpp" | ||
|
|
||
| #include <lidar_centerpoint/centerpoint_config.hpp> | ||
| #include <lidar_centerpoint/preprocess/pointcloud_densification.hpp> | ||
| #include <lidar_centerpoint/ros_utils.hpp> | ||
| #include <lidar_centerpoint/utils.hpp> | ||
| #include <pcl_ros/transforms.hpp> | ||
|
|
||
| #ifdef ROS_DISTRO_GALACTIC | ||
| #include <tf2_geometry_msgs/tf2_geometry_msgs.h> | ||
| #else | ||
| #include <tf2_geometry_msgs/tf2_geometry_msgs.hpp> | ||
| #endif | ||
|
|
||
| #include <Eigen/Dense> | ||
| #include <Eigen/Geometry> | ||
|
|
||
| #include <memory> | ||
| #include <string> | ||
| #include <vector> | ||
|
|
||
| namespace centerpoint | ||
| { | ||
| LidarCenterPointNode::LidarCenterPointNode(const rclcpp::NodeOptions & node_options) | ||
| : Node("lidar_center_point", node_options), tf_buffer_(this->get_clock()) | ||
| { | ||
| const float score_threshold = | ||
| static_cast<float>(this->declare_parameter<double>("score_threshold", 0.35)); | ||
| const float circle_nms_dist_threshold = | ||
| static_cast<float>(this->declare_parameter<double>("circle_nms_dist_threshold")); | ||
| const auto yaw_norm_thresholds = | ||
| this->declare_parameter<std::vector<double>>("yaw_norm_thresholds"); | ||
| const std::string densification_world_frame_id = | ||
| this->declare_parameter("densification_world_frame_id", "map"); | ||
| const int densification_num_past_frames = | ||
| this->declare_parameter("densification_num_past_frames", 1); | ||
| const std::string trt_precision = this->declare_parameter("trt_precision", "fp16"); | ||
| const std::string encoder_onnx_path = this->declare_parameter<std::string>("encoder_onnx_path"); | ||
| const std::string encoder_engine_path = | ||
| this->declare_parameter<std::string>("encoder_engine_path"); | ||
| const std::string head_onnx_path = this->declare_parameter<std::string>("head_onnx_path"); | ||
| const std::string head_engine_path = this->declare_parameter<std::string>("head_engine_path"); | ||
| class_names_ = this->declare_parameter<std::vector<std::string>>("class_names"); | ||
| 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")); | ||
| const std::size_t max_voxel_size = | ||
| static_cast<std::size_t>(this->declare_parameter<std::int64_t>("max_voxel_size")); | ||
| const auto point_cloud_range = this->declare_parameter<std::vector<double>>("point_cloud_range"); | ||
| const auto voxel_size = this->declare_parameter<std::vector<double>>("voxel_size"); | ||
| const std::size_t downsample_factor = | ||
| 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); | ||
|
|
||
| { | ||
| NMSParams p; | ||
| p.nms_type_ = NMS_TYPE::IoU_BEV; | ||
| p.target_class_names_ = | ||
| this->declare_parameter<std::vector<std::string>>("iou_nms_target_class_names"); | ||
| p.search_distance_2d_ = this->declare_parameter<double>("iou_nms_search_distance_2d"); | ||
| p.iou_threshold_ = this->declare_parameter<double>("iou_nms_threshold"); | ||
| iou_bev_nms_.setParameters(p); | ||
| } | ||
|
|
||
| NetworkParam encoder_param(encoder_onnx_path, encoder_engine_path, trt_precision); | ||
| NetworkParam head_param(head_onnx_path, head_engine_path, trt_precision); | ||
| DensificationParam densification_param( | ||
| densification_world_frame_id, densification_num_past_frames); | ||
|
|
||
| if (point_cloud_range.size() != 6) { | ||
| RCLCPP_WARN_STREAM( | ||
| rclcpp::get_logger("lidar_centerpoint"), | ||
| "The size of point_cloud_range != 6: use the default parameters."); | ||
| } | ||
| if (voxel_size.size() != 3) { | ||
| RCLCPP_WARN_STREAM( | ||
| rclcpp::get_logger("lidar_centerpoint"), | ||
| "The size of voxel_size != 3: use the default parameters."); | ||
| } | ||
| CenterPointConfig config( | ||
| class_names_.size(), point_feature_size, max_voxel_size, point_cloud_range, voxel_size, | ||
| downsample_factor, encoder_in_feature_size, score_threshold, circle_nms_dist_threshold, | ||
| yaw_norm_thresholds); | ||
| detector_ptr_ = | ||
| std::make_unique<CenterPointTRT>(encoder_param, head_param, densification_param, config); | ||
|
|
||
| pointcloud_sub_ = this->create_subscription<sensor_msgs::msg::PointCloud2>( | ||
| "~/input/pointcloud", rclcpp::SensorDataQoS{}.keep_last(1), | ||
| std::bind(&LidarCenterPointNode::pointCloudCallback, this, std::placeholders::_1)); | ||
| objects_pub_ = this->create_publisher<autoware_auto_perception_msgs::msg::DetectedObjects>( | ||
| "~/output/objects", rclcpp::QoS{1}); | ||
|
|
||
| // initialize debug tool | ||
| { | ||
| using tier4_autoware_utils::DebugPublisher; | ||
| using tier4_autoware_utils::StopWatch; | ||
| stop_watch_ptr_ = std::make_unique<StopWatch<std::chrono::milliseconds>>(); | ||
| debug_publisher_ptr_ = std::make_unique<DebugPublisher>(this, "lidar_centerpoint"); | ||
| stop_watch_ptr_->tic("cyclic_time"); | ||
| stop_watch_ptr_->tic("processing_time"); | ||
| } | ||
|
|
||
| if (this->declare_parameter("build_only", false)) { | ||
| RCLCPP_INFO(this->get_logger(), "TensorRT engine is built and shutdown node."); | ||
| rclcpp::shutdown(); | ||
| } | ||
| } | ||
|
Check warning on line 129 in perception/lidar_centerpoint/src/node copy.cpp
|
||
|
|
||
| void LidarCenterPointNode::pointCloudCallback( | ||
| const sensor_msgs::msg::PointCloud2::ConstSharedPtr input_pointcloud_msg) | ||
| { | ||
| const auto objects_sub_count = | ||
| objects_pub_->get_subscription_count() + objects_pub_->get_intra_process_subscription_count(); | ||
| if (objects_sub_count < 1) { | ||
| return; | ||
| } | ||
|
|
||
| if (stop_watch_ptr_) { | ||
| stop_watch_ptr_->toc("processing_time", true); | ||
| } | ||
|
|
||
| std::vector<Box3D> det_boxes3d; | ||
| std::vector<Variance> det_variance; | ||
| bool is_success = | ||
| detector_ptr_->detect(*input_pointcloud_msg, tf_buffer_, det_boxes3d, det_variance); | ||
| if (!is_success) { | ||
| return; | ||
| } | ||
|
|
||
| std::cout << "-------------------------det_variance:" << det_variance.size() << std::endl; | ||
| // << det_variance[0] << std::endl; | ||
|
|
||
| std::vector<autoware_auto_perception_msgs::msg::DetectedObject> raw_objects; | ||
| raw_objects.reserve(det_boxes3d.size()); | ||
| // for (const auto & box3d : det_boxes3d) { | ||
| // autoware_auto_perception_msgs::msg::DetectedObject obj; | ||
| // box3DToDetectedObject(box3d, class_names_, has_twist_, obj); | ||
| // raw_objects.emplace_back(obj); | ||
| // } | ||
| for (size_t i = 0; i < det_boxes3d.size(); ++i) { | ||
| autoware_auto_perception_msgs::msg::DetectedObject obj; | ||
| box3DToDetectedObject(det_boxes3d[i], class_names_, has_twist_, obj); | ||
| raw_objects.emplace_back(obj); | ||
| std::cout << i << " /// x_variance:" << det_variance[i].x_variance << std::endl; | ||
| } | ||
|
|
||
| autoware_auto_perception_msgs::msg::DetectedObjects output_msg; | ||
| output_msg.header = input_pointcloud_msg->header; | ||
| output_msg.objects = iou_bev_nms_.apply(raw_objects); | ||
|
|
||
| detection_class_remapper_.mapClasses(output_msg); | ||
|
|
||
| if (objects_sub_count > 0) { | ||
| objects_pub_->publish(output_msg); | ||
| } | ||
|
|
||
| // add processing time for debug | ||
| if (debug_publisher_ptr_ && stop_watch_ptr_) { | ||
| const double cyclic_time_ms = stop_watch_ptr_->toc("cyclic_time", true); | ||
| const double processing_time_ms = stop_watch_ptr_->toc("processing_time", true); | ||
| const double pipeline_latency_ms = | ||
| std::chrono::duration<double, std::milli>( | ||
| std::chrono::nanoseconds( | ||
| (this->get_clock()->now() - output_msg.header.stamp).nanoseconds())) | ||
| .count(); | ||
| debug_publisher_ptr_->publish<tier4_debug_msgs::msg::Float64Stamped>( | ||
| "debug/cyclic_time_ms", cyclic_time_ms); | ||
| debug_publisher_ptr_->publish<tier4_debug_msgs::msg::Float64Stamped>( | ||
| "debug/processing_time_ms", processing_time_ms); | ||
| debug_publisher_ptr_->publish<tier4_debug_msgs::msg::Float64Stamped>( | ||
| "debug/pipeline_latency_ms", pipeline_latency_ms); | ||
| } | ||
| } | ||
|
|
||
| } // namespace centerpoint | ||
|
|
||
| #include <rclcpp_components/register_node_macro.hpp> | ||
| RCLCPP_COMPONENTS_REGISTER_NODE(centerpoint::LidarCenterPointNode) | ||
Oops, something went wrong.