ros-yolov5配置

1.下载源码

cd catkin_ws/src
git clone https://github.com/OuyangJunyuan/ros-yolov5.git
git clone https://github.com/catkin/catkin_simple.git

然后回到工作空间目录下

catkin_make

2.修改config.yaml文件

• 文件位置：ros-yolov5-master/config/config.yaml

修改如下：

yolov5:
	  action: False #是否使用action
	  path: /home/agx/YOLOV5/yolov5 #yolo模型位置
 	  # weight: /home/ou/workspace/ros_ws/dev_ws/src/ros_yolo/model/best.pt
	  weight: /home/agx/YOLOV5/yolov5/weights/yolov5s.pt #yolo 模型的weight位置
 	  device: gpu
  	  img_size: 640

3.使用虚拟环境下的python

• 修改src/demo_service_server.py中首行 #!xxxxxx替换为你的虚拟环境下的python路径。

修改如下：

#!/home/agx/mambaforge/envs/py36/bin/python3.6  
# /home/ou/software/anaconda3/envs/dl/bin/python
import rospy
from yolo_bridge.yolo_bridge import Ros2Yolo

if __name__ == "__main__":
    yoloBridge = Ros2Yolo()
    rospy.spin()

4.进入yolov5虚拟环境

conda activate yolov5

5.运行服务端

source devel/setup.bash
roslaunch ros_yolo service_demo.launch 

终端输出：

6.运行服务端

rosrun ros_yolo service_client_demo