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add msg publish and convert 3dbox to 2d

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This commit is contained in:
gxt_kt 2024-08-13 18:41:01 +00:00
parent d5cc3aae62
commit 7e1439f240
10 changed files with 514 additions and 31 deletions
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2
src/guangpo_yolo_lidar/CMakeLists.txt
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@ -27,6 +27,7 @@ find_package(catkin REQUIRED COMPONENTS
pcl_ros
image_transport
cv_bridge
perception_msgs
)
find_package(yaml-cpp REQUIRED)
@ -180,6 +181,7 @@ add_executable(${PROJECT_NAME}_node src/main.cpp src/postprocess.cc src/preproc
## Add cmake target dependencies of the executable
## same as for the library above
# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
add_dependencies(${PROJECT_NAME}_node perception_msgs_gencpp)
## Specify libraries to link a library or executable target against
target_link_libraries(${PROJECT_NAME}_node

60
src/guangpo_yolo_lidar/include/message.hpp Normal file
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@ -0,0 +1,60 @@
#pragma once
#include <perception_msgs/PerceptionObstacle.h>
#include <perception_msgs/PerceptionObstacles.h>
#include "yolo_lidar_help.hpp"
inline perception_msgs::PerceptionObstacles
PackageMessage(const std::vector<mybox> &box3ds, bool verbose = false) {
static auto SetValue = [](geometry_msgs::Point &des, const cv::Point2f &src) {
des.x = src.x;
des.y = src.y;
des.z = 0;
};
perception_msgs::PerceptionObstacles obstacles;
for (int i = 0; i < box3ds.size(); i++) {
auto &box = box3ds[i];
perception_msgs::PerceptionObstacle obstacle;
obstacle.label = box.label;
// 如果聚类失败了(点太少或者不满足要求)
if (box.lidar_cluster->points.empty()) {
continue;
}
SetValue(obstacle.center_point, box.position.center);
obstacle.corner_points.resize(4);
SetValue(obstacle.corner_points.at(0), box.position.vertices.at(0));
SetValue(obstacle.corner_points.at(1), box.position.vertices.at(1));
SetValue(obstacle.corner_points.at(2), box.position.vertices.at(2));
SetValue(obstacle.corner_points.at(3), box.position.vertices.at(3));
obstacles.obstacles.emplace_back(std::move(obstacle));
}
if (verbose) {
for (int i = 0; i < obstacles.obstacles.size(); i++) {
auto &obst = obstacles.obstacles.at(i);
gDebug() << VAR("obstacle", i, obst.label);
gDebug() << VAR(obst.center_point.x, obst.center_point.y);
gDebug() << VAR(obst.corner_points.at(0).x, obst.corner_points.at(0).y);
gDebug() << VAR(obst.corner_points.at(1).x, obst.corner_points.at(1).y);
gDebug() << VAR(obst.corner_points.at(2).x, obst.corner_points.at(2).y);
gDebug() << VAR(obst.corner_points.at(3).x, obst.corner_points.at(3).y);
}
}
return obstacles;
}
inline std::vector<std::vector<cv::Point2f>>
Package2dBoxMarker(const std::vector<mybox> &box3ds) {
std::vector<std::vector<cv::Point2f>> res;
for (int i = 0; i < box3ds.size(); i++) {
auto &box = box3ds[i];
// 如果聚类失败了(点太少或者不满足要求)
if (box.lidar_cluster->points.empty()) {
continue;
}
res.push_back(box.position.vertices);
}
return res;
}

63
src/guangpo_yolo_lidar/include/yolo_lidar_help.hpp
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@ -6,6 +6,7 @@
#include <message_filters/sync_policies/approximate_time.h>
#include <message_filters/time_synchronizer.h>
#include <opencv2/core/eigen.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/opencv.hpp>
#include <ros/ros.h>
#include <sensor_msgs/Image.h>
@ -41,6 +42,12 @@ inline Eigen::Matrix4d TransforMatrix(const Eigen::Vector3d &translation,
// std::endl;
return transformation_matrix;
}
struct MinAreaRectInfo {
cv::Point2f center;
std::vector<cv::Point2f> vertices;
};
struct mybox {
mybox()
: lidar_points(new pcl::PointCloud<pcl::PointXYZ>),
@ -54,10 +61,13 @@ struct mybox {
Eigen::Vector3f obstacle_centroids;
Eigen::Vector3f obstacle_sizes;
Eigen::Quaternionf obstacle_orientations;
// 对应到机体坐标系上的点
MinAreaRectInfo position;
// 拷贝构造函数
mybox(const mybox &other)
: label(other.label), rect(other.rect), small_rect(other.small_rect),
position(other.position),
lidar_points(new pcl::PointCloud<pcl::PointXYZ>(*other.lidar_points)),
lidar_cluster(new pcl::PointCloud<pcl::PointXYZ>(*other.lidar_cluster)),
obstacle_centroids(other.obstacle_centroids),
@ -70,6 +80,8 @@ struct mybox {
label = other.label;
rect = other.rect;
small_rect = other.small_rect;
position = other.position,
lidar_points.reset(
new pcl::PointCloud<pcl::PointXYZ>(*other.lidar_points));
lidar_cluster.reset(
@ -84,6 +96,8 @@ struct mybox {
// 移动构造函数
mybox(mybox &&other) noexcept
: label(std::move(other.label)), rect(std::move(other.rect)),
position(std::move(other.position)),
small_rect(std::move(other.small_rect)),
lidar_points(std::move(other.lidar_points)),
lidar_cluster(std::move(other.lidar_cluster)),
@ -97,6 +111,7 @@ struct mybox {
label = std::move(other.label);
rect = std::move(other.rect);
small_rect = std::move(other.small_rect);
position = std::move(other.position),
lidar_points = std::move(other.lidar_points);
lidar_cluster = std::move(other.lidar_cluster);
obstacle_centroids = std::move(other.obstacle_centroids);
@ -107,6 +122,27 @@ struct mybox {
}
};
// 获取一个3维点云的最小的矩形
inline MinAreaRectInfo GetMinAreaRectInfoFrom3DCloud(
const pcl::PointCloud<pcl::PointXYZ>::Ptr &cloud) {
std::vector<cv::Point2f> points;
for (const auto &point : cloud->points) {
points.emplace_back(point.x, point.y);
}
cv::RotatedRect rect = cv::minAreaRect(points);
MinAreaRectInfo info;
info.center = rect.center;
cv::Point2f vertices[4];
rect.points(vertices);
for (int i = 0; i < 4; i++) {
info.vertices.push_back(vertices[i]);
}
return info;
}
// 把点云去除地面相关点
// 返回值第一个是非地面点,第二个是地面点
template <typename PointT>
@ -303,8 +339,11 @@ public:
convert_camera2lidar_ = Camera2Lidar();
gDebugCol5(convert_camera2lidar_);
// 初始化雷达到车体位姿
convert_lidar2car_ = Lidar2Car();
gDebugCol5(convert_lidar2car_);
auto get = Lidar2Car();
convert_lidar2car_matrix_ = get.first;
convert_lidar2car_affine_ = get.second;
gDebugCol5(convert_lidar2car_matrix_);
gDebugCol5(convert_lidar2car_affine_);
{
Eigen::Affine3d convert_point_cl = Eigen::Affine3d(
@ -316,10 +355,11 @@ public:
all_in_one_matrix_ = camera_inner_eigen * xyz2zyx * convert_point_cl;
}
}
cv::Mat camera_inner_matrix_; // 相机内参矩阵
cv::Mat camera_distort_matrix_; // 相机畸变参数矩阵
Eigen::Matrix4d convert_camera2lidar_; // 相机到雷达的位姿转换
Eigen::Matrix4d convert_lidar2car_; // 雷达到车的位姿转换
cv::Mat camera_inner_matrix_; // 相机内参矩阵
cv::Mat camera_distort_matrix_; // 相机畸变参数矩阵
Eigen::Matrix4d convert_camera2lidar_; // 相机到雷达的位姿转换
Eigen::Matrix4d convert_lidar2car_matrix_; // 雷达到车的位姿转换
Eigen::Affine3f convert_lidar2car_affine_; // 雷达到车的位姿转换
Eigen::Affine3d all_in_one_matrix_; // 激光点到相机像素坐标系点
public:
@ -380,7 +420,7 @@ private:
// 转换为Affine3f类型 affine3f_transform = affine3f_transform.inverse();
return tran_matrix;
}
inline Eigen::Matrix4d Lidar2Car() {
inline std::pair<Eigen::Matrix4d, Eigen::Affine3f> Lidar2Car() {
// 初始化坐标系变换的旋转矩阵
Eigen::Vector3d trans;
trans[0] = yaml_config["convert_lidar2car"]["transform"]["x"].as<double>();
@ -402,9 +442,10 @@ private:
Eigen::Matrix4d tran_matrix = TransforMatrix(
trans, roll * M_PI / 180.0, pitch * M_PI / 180.0, yaw * M_PI / 180.0);
gDebug() << VAR(tran_matrix);
// Eigen::Affine3d affine3d_transform(tran_matrix); // 转换为Affine3d类型
// affine3f_transform = affine3d_transform.cast<float>(); //
// 转换为Affine3f类型 affine3f_transform = affine3f_transform.inverse();
return tran_matrix;
Eigen::Affine3d affine3d_transform(tran_matrix); // 转换为Affine3d类型
Eigen::Affine3f affine3f_transform = affine3d_transform.cast<float>(); //
// 转换为Affine3f类型
affine3f_transform = affine3f_transform.inverse();
return {tran_matrix, affine3f_transform};
}
};

3
src/guangpo_yolo_lidar/package.xml
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@ -67,6 +67,9 @@
<exec_depend>rospy</exec_depend>
<exec_depend>sensor_msgs</exec_depend>
<exec_depend>std_msgs</exec_depend>
<build_depend>perception_msgs</build_depend>
<!-- <build_export_depend>perception_msgs</run_depend> -->
<exec_depend>perception_msgs</exec_depend>
<!-- The export tag contains other, unspecified, tags -->

124
src/guangpo_yolo_lidar/src/main.cpp
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@ -1,5 +1,6 @@
#include <cv_bridge/cv_bridge.h>
#include <filesystem>
#include <geometry_msgs/PolygonStamped.h>
#include <message_filters/subscriber.h>
#include <message_filters/sync_policies/approximate_time.h>
#include <message_filters/time_synchronizer.h>
@ -12,13 +13,18 @@
#include <visualization_msgs/Marker.h>
#include <visualization_msgs/MarkerArray.h>
#include <pcl/common/transforms.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl_conversions/pcl_conversions.h>
#include <perception_msgs/PerceptionObstacle.h>
#include <perception_msgs/PerceptionObstacles.h>
#include "dbscan.hpp"
#include "debugstream.hpp"
#include "message.hpp"
#include "yaml_config.h"
#include "yolo_lidar_help.hpp"
@ -95,6 +101,9 @@ public:
yolo_other.SetLabels(labels_other);
yolo_other.LoadModel(model_other_name);
pub_obstacles_ = nh.advertise<perception_msgs::PerceptionObstacles>(
yaml_config["obstacles_topic_"].as<std::string>(), 10);
person_density_pub_ = nh.advertise<std_msgs::Int8>(
yaml_config["person_density_topic"].as<std::string>(), 10);
@ -184,11 +193,17 @@ public:
ROS_INFO("Image published!");
}
// 输入的点云是激光坐标系下的,发布的是车辆坐标系
void SendLidar(ros::Publisher &pub,
const pcl::PointCloud<pcl::PointXYZ>::Ptr cloud) {
pcl::PointCloud<pcl::PointXYZ>::Ptr publish(
new pcl::PointCloud<pcl::PointXYZ>);
// 将点云进行转换
pcl::transformPointCloud(*cloud, *publish, help.convert_lidar2car_affine_);
// 发送点云数组
sensor_msgs::PointCloud2 msg;
pcl::toROSMsg(*cloud, msg);
pcl::toROSMsg(*publish, msg);
msg.header.frame_id = "map"; // 设置坐标系
msg.header.stamp = ros::Time::now();
pub.publish(msg);
@ -271,6 +286,48 @@ public:
pub_3dbox_.publish(marker_array);
}
void Publish2dObstacles(
const std::vector<std::vector<cv::Point2f>> &obstacle_polygons) {
visualization_msgs::MarkerArray marker_array;
// 首先发布一个DELETEALL命令,删除上次发布的所有障碍物标记
visualization_msgs::Marker delete_marker;
delete_marker.header.frame_id = "map";
delete_marker.action = visualization_msgs::Marker::LINE_STRIP;
marker_array.markers.push_back(delete_marker);
pub_3dbox_.publish(marker_array);
marker_array.markers.clear(); // 清空marker_array
for (size_t i = 0; i < obstacle_polygons.size(); ++i) {
visualization_msgs::Marker marker;
marker.header.frame_id = "map";
marker.type = visualization_msgs::Marker::LINE_STRIP;
marker.action = visualization_msgs::Marker::ADD;
marker.id = i;
marker.scale.x = 0.1;
marker.pose.orientation.w = 1.0; // 朝向为单位四元数
marker.color.r = 1.0f;
marker.color.g = 0.0f;
marker.color.b = 0.0f;
marker.color.a = 0.3;
geometry_msgs::Point p;
for (const auto &point : obstacle_polygons[i]) {
p.x = point.x;
p.y = point.y;
p.z = 0.0; // 2D 矩形,高度设为0
marker.points.push_back(p);
}
p.x = obstacle_polygons[i][0].x;
p.y = obstacle_polygons[i][0].y;
p.z = 0.0; // 2D 矩形,高度设为0
marker.points.push_back(p);
marker_array.markers.push_back(marker);
}
pub_3dbox_.publish(marker_array);
}
void callback(const sensor_msgs::ImageConstPtr &image_msg,
const sensor_msgs::PointCloud2ConstPtr &point_cloud_msg) {
@ -499,33 +556,59 @@ public:
}
SendLidar(lidar_pub2_, combined_lidar_points2);
gDebugWarn() << G_FILE_LINE;
// 把点云提取出3dbox
static int obb_omp_threads = yaml_config["obb_omp_threads"].as<int>();
// omp_set_num_threads(obb_omp_threads);
// #pragma omp parallel for
for (int i = 0; i < box3ds.size(); i++) {
auto &box = box3ds[i];
ExtractObstacles(box.lidar_cluster, box.obstacle_centroids,
box.obstacle_sizes, box.obstacle_orientations, true);
}
// 暂时不需要3dbox
// gDebugWarn() << G_FILE_LINE;
// // 把点云提取出3dbox
// static int obb_omp_threads = yaml_config["obb_omp_threads"].as<int>();
// // omp_set_num_threads(obb_omp_threads);
// // #pragma omp parallel for
// for (int i = 0; i < box3ds.size(); i++) {
// auto &box = box3ds[i];
// ExtractObstacles(box.lidar_cluster, box.obstacle_centroids,
// box.obstacle_sizes, box.obstacle_orientations, true);
// }
// gDebugWarn() << G_FILE_LINE;
// std::vector<Eigen::Vector3f> obstacle_centroids;
// std::vector<Eigen::Vector3f> obstacle_sizes;
// std::vector<Eigen::Quaternionf> obstacle_orientations;
// for (int i = 0; i < box3ds.size(); i++) {
// auto &box = box3ds[i];
// // 如果聚类失败了(点太少或者不满足要求)
// if (box.lidar_cluster->points.empty()) {
// continue;
// }
// obstacle_centroids.push_back(box.obstacle_centroids);
// obstacle_sizes.push_back(box.obstacle_sizes);
// obstacle_orientations.push_back(box.obstacle_orientations);
// }
// gDebugWarn() << G_FILE_LINE;
// PublishObstacles(obstacle_centroids, obstacle_sizes,
// obstacle_orientations);
gDebugWarn() << G_FILE_LINE;
std::vector<Eigen::Vector3f> obstacle_centroids;
std::vector<Eigen::Vector3f> obstacle_sizes;
std::vector<Eigen::Quaternionf> obstacle_orientations;
// 先把点云转到车体坐标系
for (int i = 0; i < box3ds.size(); i++) {
auto &box = box3ds[i];
pcl::transformPointCloud(*box.lidar_cluster, *box.lidar_cluster,
help.convert_lidar2car_affine_);
// 如果聚类失败了(点太少或者不满足要求)
if (box.lidar_cluster->points.empty()) {
continue;
}
obstacle_centroids.push_back(box.obstacle_centroids);
obstacle_sizes.push_back(box.obstacle_sizes);
obstacle_orientations.push_back(box.obstacle_orientations);
box.position = GetMinAreaRectInfoFrom3DCloud(box.lidar_cluster);
// // 输出最小包围矩形的信息
// std::cout << "Center: (" << rect.center.x << ", " << rect.center.y <<
// ")"
// << std::endl;
// std::cout << "Size: (" << rect.size.width << ", " << rect.size.height
// << ")" << std::endl;
// std::cout << "Angle: " << rect.angle << " degrees" << std::endl;
}
gDebugWarn() << G_FILE_LINE;
PublishObstacles(obstacle_centroids, obstacle_sizes, obstacle_orientations);
auto obstacles_msg = PackageMessage(box3ds, true);
pub_obstacles_.publish(obstacles_msg);
// 发布可视化内容
auto packages_marker = Package2dBoxMarker(box3ds);
Publish2dObstacles(packages_marker);
}
void Init() {
@ -597,6 +680,7 @@ private:
ros::Subscriber sub_detect_congest_enable_;
bool enable_detect_congest = true;
ros::Publisher person_density_pub_;
ros::Publisher pub_obstacles_;
ros::Publisher image_pub_;
ros::Publisher lidar_pub1_;

2
src/guangpo_yolo_lidar/yaml_config/yaml_config.yaml
View File

@ -18,6 +18,8 @@ person_distance : 5
detect_congest_enable_topic : "/detect_congest_enable"
# 发布的电梯拥挤度话题
person_density_topic : "/person_density"
# 发布的障碍物信息话题
obstacles_topic_ : "/obstacles"
# 设置传感器时间同步最大时间间隔 单位s
max_time_interval : 0.2

211
src/perception_msgs/CMakeLists.txt Normal file
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@ -0,0 +1,211 @@
cmake_minimum_required(VERSION 3.0.2)
project(perception_msgs)
## Compile as C++11, supported in ROS Kinetic and newer
# add_compile_options(-std=c++11)
## Find catkin macros and libraries
## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
## is used, also find other catkin packages
find_package(catkin REQUIRED COMPONENTS
geometry_msgs
message_generation
roscpp
rospy
std_msgs
)
## System dependencies are found with CMake's conventions
# find_package(Boost REQUIRED COMPONENTS system)
## Uncomment this if the package has a setup.py. This macro ensures
## modules and global scripts declared therein get installed
## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
# catkin_python_setup()
################################################
## Declare ROS messages, services and actions ##
################################################
## To declare and build messages, services or actions from within this
## package, follow these steps:
## * Let MSG_DEP_SET be the set of packages whose message types you use in
## your messages/services/actions (e.g. std_msgs, actionlib_msgs, ...).
## * In the file package.xml:
## * add a build_depend tag for "message_generation"
## * add a build_depend and a exec_depend tag for each package in MSG_DEP_SET
## * If MSG_DEP_SET isn't empty the following dependency has been pulled in
## but can be declared for certainty nonetheless:
## * add a exec_depend tag for "message_runtime"
## * In this file (CMakeLists.txt):
## * add "message_generation" and every package in MSG_DEP_SET to
## find_package(catkin REQUIRED COMPONENTS ...)
## * add "message_runtime" and every package in MSG_DEP_SET to
## catkin_package(CATKIN_DEPENDS ...)
## * uncomment the add_*_files sections below as needed
## and list every .msg/.srv/.action file to be processed
## * uncomment the generate_messages entry below
## * add every package in MSG_DEP_SET to generate_messages(DEPENDENCIES ...)
## Generate messages in the 'msg' folder
add_message_files(
FILES
# Message1.msg
PerceptionObstacle.msg
PerceptionObstacles.msg
# Message2.msg
)
## Generate services in the 'srv' folder
# add_service_files(
# FILES
# Service1.srv
# Service2.srv
# )
## Generate actions in the 'action' folder
# add_action_files(
# FILES
# Action1.action
# Action2.action
# )
## Generate added messages and services with any dependencies listed here
generate_messages(
DEPENDENCIES
geometry_msgs
std_msgs
)
################################################
## Declare ROS dynamic reconfigure parameters ##
################################################
## To declare and build dynamic reconfigure parameters within this
## package, follow these steps:
## * In the file package.xml:
## * add a build_depend and a exec_depend tag for "dynamic_reconfigure"
## * In this file (CMakeLists.txt):
## * add "dynamic_reconfigure" to
## find_package(catkin REQUIRED COMPONENTS ...)
## * uncomment the "generate_dynamic_reconfigure_options" section below
## and list every .cfg file to be processed
## Generate dynamic reconfigure parameters in the 'cfg' folder
# generate_dynamic_reconfigure_options(
# cfg/DynReconf1.cfg
# cfg/DynReconf2.cfg
# )
###################################
## catkin specific configuration ##
###################################
## The catkin_package macro generates cmake config files for your package
## Declare things to be passed to dependent projects
## INCLUDE_DIRS: uncomment this if your package contains header files
## LIBRARIES: libraries you create in this project that dependent projects also need
## CATKIN_DEPENDS: catkin_packages dependent projects also need
## DEPENDS: system dependencies of this project that dependent projects also need
catkin_package(
# INCLUDE_DIRS include
# LIBRARIES perception_msgs
CATKIN_DEPENDS geometry_msgs message_generation roscpp rospy std_msgs
# DEPENDS system_lib
)
###########
## Build ##
###########
## Specify additional locations of header files
## Your package locations should be listed before other locations
include_directories(
# include
${catkin_INCLUDE_DIRS}
)
## Declare a C++ library
# add_library(${PROJECT_NAME}
# src/${PROJECT_NAME}/perception_msgs.cpp
# )
## Add cmake target dependencies of the library
## as an example, code may need to be generated before libraries
## either from message generation or dynamic reconfigure
# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
## Declare a C++ executable
## With catkin_make all packages are built within a single CMake context
## The recommended prefix ensures that target names across packages don't collide
# add_executable(${PROJECT_NAME}_node src/perception_msgs_node.cpp)
## Rename C++ executable without prefix
## The above recommended prefix causes long target names, the following renames the
## target back to the shorter version for ease of user use
## e.g. "rosrun someones_pkg node" instead of "rosrun someones_pkg someones_pkg_node"
# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")
## Add cmake target dependencies of the executable
## same as for the library above
# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
## Specify libraries to link a library or executable target against
# target_link_libraries(${PROJECT_NAME}_node
# ${catkin_LIBRARIES}
# )
#############
## Install ##
#############
# all install targets should use catkin DESTINATION variables
# See http://ros.org/doc/api/catkin/html/adv_user_guide/variables.html
## Mark executable scripts (Python etc.) for installation
## in contrast to setup.py, you can choose the destination
# catkin_install_python(PROGRAMS
# scripts/my_python_script
# DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
# )
## Mark executables for installation
## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_executables.html
# install(TARGETS ${PROJECT_NAME}_node
# RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
# )
## Mark libraries for installation
## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_libraries.html
# install(TARGETS ${PROJECT_NAME}
# ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
# LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
# RUNTIME DESTINATION ${CATKIN_GLOBAL_BIN_DESTINATION}
# )
## Mark cpp header files for installation
# install(DIRECTORY include/${PROJECT_NAME}/
# DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
# FILES_MATCHING PATTERN "*.h"
# PATTERN ".svn" EXCLUDE
# )
## Mark other files for installation (e.g. launch and bag files, etc.)
# install(FILES
# # myfile1
# # myfile2
# DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
# )
#############
## Testing ##
#############
## Add gtest based cpp test target and link libraries
# catkin_add_gtest(${PROJECT_NAME}-test test/test_perception_msgs.cpp)
# if(TARGET ${PROJECT_NAME}-test)
# target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
# endif()
## Add folders to be run by python nosetests
# catkin_add_nosetests(test)

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src/perception_msgs/msg/PerceptionObstacle.msg Normal file
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string label
geometry_msgs/Point center_point
geometry_msgs/Point[] corner_points

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src/perception_msgs/msg/PerceptionObstacles.msg Normal file
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std_msgs/Header header
perception_msgs/PerceptionObstacle[] obstacles

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src/perception_msgs/package.xml Normal file
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<?xml version="1.0"?>
<package format="2">
<name>perception_msgs</name>
<version>0.0.0</version>
<description>The perception_msgs package</description>
<!-- One maintainer tag required, multiple allowed, one person per tag -->
<!-- Example: -->
<!-- <maintainer email="jane.doe@example.com">Jane Doe</maintainer> -->
<maintainer email="gxt_kt@todo.todo">gxt_kt</maintainer>
<!-- One license tag required, multiple allowed, one license per tag -->
<!-- Commonly used license strings: -->
<!-- BSD, MIT, Boost Software License, GPLv2, GPLv3, LGPLv2.1, LGPLv3 -->
<license>TODO</license>
<!-- Url tags are optional, but multiple are allowed, one per tag -->
<!-- Optional attribute type can be: website, bugtracker, or repository -->
<!-- Example: -->
<!-- <url type="website">http://wiki.ros.org/perception_msgs</url> -->
<!-- Author tags are optional, multiple are allowed, one per tag -->
<!-- Authors do not have to be maintainers, but could be -->
<!-- Example: -->
<!-- <author email="jane.doe@example.com">Jane Doe</author> -->
<!-- The *depend tags are used to specify dependencies -->
<!-- Dependencies can be catkin packages or system dependencies -->
<!-- Examples: -->
<!-- Use depend as a shortcut for packages that are both build and exec dependencies -->
<!-- <depend>roscpp</depend> -->
<!-- Note that this is equivalent to the following: -->
<!-- <build_depend>roscpp</build_depend> -->
<!-- <exec_depend>roscpp</exec_depend> -->
<!-- Use build_depend for packages you need at compile time: -->
<!-- <build_depend>message_generation</build_depend> -->
<!-- Use build_export_depend for packages you need in order to build against this package: -->
<!-- <build_export_depend>message_generation</build_export_depend> -->
<!-- Use buildtool_depend for build tool packages: -->
<!-- <buildtool_depend>catkin</buildtool_depend> -->
<!-- Use exec_depend for packages you need at runtime: -->
<!-- <exec_depend>message_runtime</exec_depend> -->
<!-- Use test_depend for packages you need only for testing: -->
<!-- <test_depend>gtest</test_depend> -->
<!-- Use doc_depend for packages you need only for building documentation: -->
<!-- <doc_depend>doxygen</doc_depend> -->
<buildtool_depend>catkin</buildtool_depend>
<build_depend>geometry_msgs</build_depend>
<build_depend>message_generation</build_depend>
<build_depend>roscpp</build_depend>
<build_depend>rospy</build_depend>
<build_depend>std_msgs</build_depend>
<build_depend>message_generation</build_depend>
<build_export_depend>message_generation</build_export_depend>
<exec_depend>message_runtime</exec_depend>
<build_export_depend>geometry_msgs</build_export_depend>
<build_export_depend>roscpp</build_export_depend>
<build_export_depend>rospy</build_export_depend>
<build_export_depend>std_msgs</build_export_depend>
<exec_depend>geometry_msgs</exec_depend>
<exec_depend>roscpp</exec_depend>
<exec_depend>rospy</exec_depend>
<exec_depend>std_msgs</exec_depend>
<!-- The export tag contains other, unspecified, tags -->
<export>
<!-- Other tools can request additional information be placed here -->
</export>
</package>