注册网站建设,专业免费网站建设一般多少钱,烟台做网站建设,用wordpress做商城目录 1. ros2 yolov8 检测需要以来一些库#xff0c;分别是:rclpy cv_bridge std_msgs sensor_msgs sensor_msgs_py vision_msgs
2. 创建一个新的功能包 3. 建立 yolo_launch.py 里面先加载gazebo和rviz2,在创建好本地的yolov8的node文件后也加入进来。
4. 创建好本地的yol…目录 1. ros2 yolov8 检测需要以来一些库分别是:rclpy cv_bridge std_msgs sensor_msgs sensor_msgs_py vision_msgs
2. 创建一个新的功能包 3. 建立 yolo_launch.py 里面先加载gazebo和rviz2,在创建好本地的yolov8的node文件后也加入进来。
4. 创建好本地的yolov8的node文件
5. 修改setup.py文件
6. 编译包
7. 运行launch文件 1. ros2 yolov8 检测需要以来一些库分别是:rclpy cv_bridge std_msgs sensor_msgs sensor_msgs_py vision_msgs
(1) rclpy Python语言的ROS Client Library操作ROS2的节点话题服务 (2) cv-bridge 在ROS图像消息和OpenCV图像之间进行转换的一个功能包 (3) std-msgs 一种标准消息类型包,包含了一些常用的基本数据类型的消息定义
以上设计的是图像依赖的下面两个是获取其他数据类型的 ---------------------------------------------------------------
(4) sensor-msgs-py point_cloud2模块 (5) vision-msgs ROS的与算法无关的计算机视觉消息类型,ROS视觉信息介绍该软件包定义了一组消息,以统一ROS中的计算机视觉和对象检测工作
# 库安装命令如下
sudo apt-get install ros-galactic-rclpy
sudo apt-get install ros-galactic-cv-bridge
sudo apt-get install ros-galactic-std-msgs
sudo apt-get install ros-galactic-sensor-msgs-py
sudo apt-get install ros-galactic-vision-msgs
2. 创建一个新的功能包
ros2 pkg create ros_yolov8 --build-type ament_python --node-name detect_node --dependencies rclpy cv_bridge std_msgs sensor_msgs sensor_msgs_py vision_msgs 运行结果 going to create a new package
package name: ros_yolov8
destination directory:
package format: 3
version: 0.0.0
description: TODO: Package description
maintainer:
licenses: [TODO: License declaration]
build type: ament_python
dependencies: [rclpy, cv_bridge, std_msgs, sensor_msgs, sensor_msgs_py, vision_msgs]
node_name: detect_node
creating folder ./ros_yolov8
creating ./ros_yolov8/package.xml
creating source folder
creating folder ./ros_yolov8/ros_yolov8
creating ./ros_yolov8/setup.py
creating ./ros_yolov8/setup.cfg
creating folder ./ros_yolov8/resource
creating ./ros_yolov8/resource/ros_yolov8
creating ./ros_yolov8/ros_yolov8/__init__.py
creating folder ./ros_yolov8/test
creating ./ros_yolov8/test/test_copyright.py
creating ./ros_yolov8/test/test_flake8.py
creating ./ros_yolov8/test/test_pep257.py
creating ./ros_yolov8/ros_yolov8/detect_node.py # ./ros_yolov8/package.xml ?xml version1.0? ...... dependrclpy/depend dependcv_bridge/depend dependstd_msgs/depend dependsensor_msgs/depend dependsensor_msgs_py/depend dependvision_msgs/depend ...... /package 3. 建立 yolo_launch.py 里面先加载gazebo和rviz2,在创建好本地的yolov8的node文件后也加入进来。 # 创建一个新目录来存储(launch)启动文件
cd ./ros_yolov8 mkdir launch
cd ./ros_yolov8/launch touch detect_demo.launch.py
tree ./ros_yolov8/launch 运行结果 ./ros_yolov8/launch
└── detect_demo.launch.py #!/usr/bin/python3
# ./ros_yolov8/launch/detect_demo.launch.pyimport osfrom ament_index_python.packages import get_package_share_directoryfrom launch import LaunchDescription
from launch_ros.actions import Nodefrom launch.substitutions import LaunchConfiguration
from launch.actions import DeclareLaunchArgument
from launch.conditions import IfConditionfrom launch.actions import IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSourcedef generate_launch_description():# all kinds of file pathros_root_path /xxx/ros2_wstry:pkg_name ros_yolov8share_pkg_path get_package_share_directory(pkg_name)except:share_pkg_path os.path.join(ros_root_path, install, pkg_name, share, pkg_name)print(f{share_pkg_path})assert os.path.exists(share_pkg_path)# -1-Include the Gazebo launch file, provided by the gazebo_ros packageworld_file_path os.path.join(share_pkg_path, worlds, yolo.world)# 包含其它的launch文件 :/opt/ros/galactic/share/gazebo_ros/launch/gazebo.launch.py# $ ros2 launch /opt/ros/galactic/share/gazebo_ros/launch/gazebo.launch.py world:/xxx/yolo.worldgazebo_ros_dirpath get_package_share_directory(gazebo_ros)print(f{gazebo_ros_dirpath})gazebo_launch_filepath os.path.join(gazebo_ros_dirpath, launch, gazebo.launch.py)print(f{gazebo_launch_filepath})assert os.path.exists(gazebo_launch_filepath)# -2-Include the Rviz2 config file, provided by the rviz2 package# /opt/ros/galactic/lib/rviz2/rviz2# $ ros2 run rviz2 rviz2 -d # start rviz2rviz_filepath os.path.join(share_pkg_path, rviz2, yolo.rviz)print(f{rviz_filepath})assert os.path.exists(rviz_filepath)# Nodesgazebo_cmd IncludeLaunchDescription(PythonLaunchDescriptionSource([gazebo_launch_filepath]),launch_arguments{world: world_file_path}.items())static_transform_cmd Node(packagetf2_ros,executablestatic_transform_publisher,namestatic_transform_publisher,arguments[0, 0, 0, 0, 0, 0, map, camera_link_optical],outputscreen)start_rviz_cmd Node(packagerviz2,executablerviz2,namerviz2,arguments[-d, rviz_filepath],outputscreen)# Launch arguments# start yolov8_nodestart_yolov8_node Node(packageros_yolov8,executableyolov8_node,nameyolov8_node,outputscreen,arguments[-model, /xxx/yolo.pt])# Add everything to launch description and returnld LaunchDescription()ld.add_action(gazebo_cmd)ld.add_action(static_transform_cmd)ld.add_action(start_rviz_cmd)ld.add_action(start_yolov8_node)return ld
/opt/ros/galactic/lib/tf2_ros/static_transform_publisher
# ros2 run tf2_ros static_transform_publisher 0 0 0 0 0 0 map camera_link_optical
# -2-1- map axis between origin and world4. 创建好本地的yolov8的node文件
# ./ros_yolov8/ros_yolov8/yolov8_node.pyimport os
import sys
import time
import argparse
import random
import torch
# ROS2的客户端库(python) rclpy
import rclpy
from rclpy.qos import qos_profile_sensor_data
from rclpy.node import Node
# image-----below----
# topic sensor_msgs/msg/Image to cv2
import cv2
from sensor_msgs.msg import Image
from cv_bridge import CvBridge
# yolov8
from ultralytics import YOLOdef parse_argument():parser argparse.ArgumentParser(descriptiondetect image from topic (gazebo))parser.add_argument(-model, typestr, default/xxx/yolo.pt)parser.add_argument(-device, typestr, defaultcpu)parser.add_argument(-conf_threshold, typefloat, default0.5)parser.add_argument(-iou_threshold, typefloat, default0.7)parser.add_argument(-enable, typebool, defaultTrue)parser.add_argument(-input_image_topic, typestr, default/camera/image_raw)parser.add_argument(-show_inference_image, typebool, defaultTrue)parser.add_argument(-save, typebool, defaultFalse)args, unknown parser.parse_known_args()return argsclass Yolov8Node(Node):# Node constructordef __init__(self) - None:super().__init__(yolov8_node)# node paramsself.args parse_argument()#self._class_to_color {}self.cv_bridge CvBridge()# yoloself.yolo YOLO(self.args.model)self.yolo.fuse()print(f{self.args.device})self.yolo.to(self.args.device)# topic publishers subscribersself._infer_pub self.create_publisher(Image, inference_image, 10)self._image_sub self.create_subscription(Image,self.args.input_image_topic,self.image_cb,qos_profile_sensor_data)def image_cb(self, msg: Image) - None:# if self.args.enable:# record start timefps_start_t time.time()# convert to cv image predictcv_image self.cv_bridge.imgmsg_to_cv2(msg)infer_start_t time.perf_counter()results self.yolo.predict(sourcecv_image,verboseFalse,streamFalse,confself.args.conf_threshold,iouself.args.iou_threshold,showself.args.show_inference_image,modepredict,saveself.args.save)end_time time.perf_counter()# visualize the results on the frameannotated_image results[0].plot()# record the end time and calculate FPSfps 1.0 / (end_time - fps_start_t)cv2.putText(annotated_image, FPS: {:.2f}.format(fps), (10, 30),cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2, cv2.LINE_AA)results results[0].cpu()for b in results.boxes:label self.yolo.names[int(b.cls)]score float(b.conf)if score self.args.conf_threshold:continue# get boxes valuesbox b.xywh[0]x_center float(box[0])y_center float(box[1])x_size float(box[2])y_size float(box[3])x_min round(x_center - x_size / 2.0)x_max round(x_center x_size / 2.0)y_min round(y_center - y_size / 2.0)y_max round(y_center y_size / 2.0)# draw boxes for debuggingif label not in self._class_to_color:r random.randint(0, 255)g random.randint(0, 255)b random.randint(0, 255)self._class_to_color[label] (r, g, b)color self._class_to_color[label]cv2.rectangle(cv_image, (x_min, y_min), (x_max, y_max), color, 2)label {} ({:.3f}).format(label, score)pos (x_min 5, y_min 25)font cv2.FONT_HERSHEY_SIMPLEXcv2.putText(cv_image, label, pos, font,1, color, 1, cv2.LINE_AA)# append msgself._infer_pub.publish(self.cv_bridge.cv2_to_imgmsg(annotated_image, encodingmsg.encoding))def main():rclpy.init()node Yolov8Node()rclpy.spin(node)node.destroy_node()rclpy.shutdown()if __name__ __main__:main()5. 修改setup.py文件
# ./ros_yolov8/setup.py
from setuptools import setup
import os
from glob import globpackage_name ros_yolov8setup(namepackage_name,version0.0.0,packages[package_name],# new ros2_ws/install/{package_name}/share/*, copy from src/{package_name}/*data_files[(share/ament_index/resource_index/packages, [resource/ package_name]),(share/ package_name, [package.xml]),# During installation, we need to copy the launch files(os.path.join(share, package_name, launch), glob(launch/*launch.[pxy][yma]*)),# Same with the RViz2 configuration file.(os.path.join(share, package_name, rviz2), glob(rviz2/*)),# And the Gazebo world files.(os.path.join(share, package_name, worlds), glob(worlds/*)),# And the config files.(os.path.join(share, package_name, config), glob(config/*)),],
......
6. 编译包
source /opt/ros/galactic/setup.bash
colcon build --packages-select ros-yolov8
. install/setup.bash
7. 运行launch文件
ros2 launch /xxx/ros_yolov8/launch/detect_demo.launch.py
# 或
ros2 launch ros_yolov8 detect_demo.launch.py
