feat:把rdk算法部署流程写为skill #4
@ -34,13 +34,9 @@ ros2 launch mono_mobilesam sam.launch.py
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# MobileSAM图像分割算法部署流程:使用本地照片回灌
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<<<<<<< Updated upstream
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1. 配置tros.b环境 若为humble则用source /opt/tros/humble/setup.bash
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source /opt/tros/setup.bash
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=======
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1. 配置tros.b环境
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source /opt/tros/humble/setup.bash
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>>>>>>> Stashed changes
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2. 从tros.b的安装路径中拷贝出运行示例需要的配置文件。
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cp -r /opt/tros/${TROS_DISTRO}/lib/mono_mobilesam/config/ .
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@ -5,11 +5,8 @@ foxy版本:source /opt/tros/setup.bash
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humble版本:source /opt/tros/humble/setup.bash
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2. 从tros.b的安装路径中拷贝出运行示例需要的配置文件。
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<<<<<<< Updated upstream
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cp -r /opt/tros/${TROS_DISTRO}/lib/elevation_net/config/
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=======
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cp -r /opt/tros/${TROS_DISTRO}/lib/elevation_net/config/ .
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>>>>>>> Stashed changes
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3. 启动launch文件
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ros2 launch elevation_net elevation_net.launch.py
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@ -15,11 +15,8 @@ ln -s `ros2 pkg prefix hobot_centerpoint`/lib/hobot_centerpoint/qat/ qat
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ln -s ~/centerpoint_data centerpoint_data
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4. 启动launch文件
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<<<<<<< Updated upstream
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ros2 launch hobot_centerpoint hobot_centerpoint.launch.p
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=======
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ros2 launch hobot_centerpoint hobot_centerpoint.launch.py
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>>>>>>> Stashed changes
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5. 测试效果
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运行成功后在pc端游览器输入:[http://IP:8000](http://ip:8000/),即可查看图像和算法渲染效果(IP为RDK的IP地址)
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