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rdk_robot_dev_agent/knowledge_hub/Ultralytics YOLOv8-Seg图像分割算法部署流程.md

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Ultralytics YOLOv8-Seg图像分割算法部署流程：用MIPI摄像头发布为照片

  1. 配置tros.b环境 若为humble则用source /opt/tros/humble/setup.bash source /opt/tros/setup.bash

  2. 配置MIPI摄像头 export CAM_TYPE=mipi

  3. 启动launch文件 ros2 launch dnn_node_example dnn_node_example.launch.py dnn_example_dump_render_img:=0 dnn_example_config_file:=config/yolov8segworkconfig.json dnn_example_image_width:=1920 dnn_example_image_height:=1080

Ultralytics YOLOv8-Seg图像分割算法部署流程：用usb摄像头发布为照片

  1. 配置tros.b环境 若为humble则用source /opt/tros/humble/setup.bash source /opt/tros/setup.bash

  2. 配置usb摄像头 export CAM_TYPE=usb

  3. 启动launch文件 ros2 launch dnn_node_example dnn_node_example.launch.py dnn_example_dump_render_img:=0 dnn_example_config_file:=config/yolov8segworkconfig.json dnn_example_image_width:=1920 dnn_example_image_height:=1080

Ultralytics YOLOv8-Seg图像分割算法部署流程：使用本地照片回灌

  1. 配置tros.b环境 若为humble则用source /opt/tros/humble/setup.bash source /opt/tros/setup.bash

  2. 启动launch文件 ros2 launch dnn_node_example dnn_node_example_feedback.launch.py dnn_example_config_file:=config/yolov8segworkconfig.json dnn_example_image:=config/test.jpg