ros2视觉yolo
时间: 2025-05-05 17:56:11 浏览: 25
### 集成YOLO至ROS 2环境
#### 安装依赖项
为了使YOLO能在ROS 2环境中正常工作,需先安装必要的软件包和工具。这通常涉及Python版本的选择以及特定于操作系统的配置[^1]。
```bash
sudo apt-get update && sudo apt-get install -y \
python3-pip \
ros-$ROS_DISTRO-vision-msgs \
ros-$ROS_DISTRO-image-transport
pip3 install --upgrade pip setuptools wheel
```
#### 获取并编译YOLO节点
获取适用于ROS 2的YOLO源码仓库,并按照官方说明完成构建过程。对于大多数情况而言,推荐使用`colcon build`命令来进行编译[^4]。
```bash
cd ~/ros2_ws/src/
git clone https://github.com/your-repo/yolov5_ros2.git
cd ~/ros2_ws
colcon build --symlink-install
source install/setup.bash
```
#### 启动与测试
启动ROS 2核心服务之后,可以运行预先准备好的发射文件(launch file),该文件会自动加载相机驱动程序、图像传输管道及YOLO检测器[^2]。
```xml
<launch>
<!-- Camera node -->
<node pkg="usb_cam" type="usb_cam_node" name="camera"/>
<!-- Image transport pipeline -->
<node pkg="image_transport" type="republish" args="compressed in:=/image_raw raw out:=/image"/>
<!-- YOLO detector -->
<include file="$(find yolov5_ros2)/launch/detector.launch.xml">
</launch>
```
#### 数据可视化
借助RViz或其他兼容工具查看由YOLO产生的标注框和其他元数据。确保订阅正确的主题(topic)以便接收处理后的图像流[^3]。
```python
import rclpy
from rclpy.node import Node
from sensor_msgs.msg import Image, CompressedImage
from cv_bridge import CvBridge
import numpy as np
import cv2
class ImageViewer(Node):
def __init__(self):
super().__init__('image_viewer')
self.subscription = self.create_subscription(
Image,
'/detections/image',
self.listener_callback,
10)
self.bridge = CvBridge()
def listener_callback(self, msg):
frame = self.bridge.imgmsg_to_cv2(msg, desired_encoding='bgr8')
cv2.imshow('Detection Results', frame)
cv2.waitKey(1)
def main(args=None):
rclpy.init(args=args)
image_viewer = ImageViewer()
rclpy.spin(image_viewer)
image_viewer.destroy_node()
rclpy.shutdown()
if __name__ == '__main__':
main()
```
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