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Source channel @githubtrending · Post #15062 · Aug 15

#python#mllm#point_clouds#scene_understanding#spatial_intelligence SpatialLM is a powerful 3D language model that turns complex 3D point cloud data from videos, RGBD images, or LiDAR into clear, structured 3D scene layouts showing walls, doors, windows, and objects with labels. It works without needing special equipment and can detect user-specified object categories. This helps you understand and analyze indoor spaces better, useful for robotics, navigation, and 3D design. You can run it on your data, visualize results, and even customize detection tasks easily, making 3D scene understanding more accessible and flexible for many applications. https://github.com/manycore-research/SpatialLM

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Host Testing and evaluation

@HostEvaluate · Post #722 · 03/12/2021, 02:57 AM

#US#LAX#DMIT#AntiDDOS Host Provider: DMIT (PVM.Lax.sPro.CREATOR) Specification: 2 vCore | 2GB RAM | 20G SSD | 1000GB Transfer @ 100Mbps | $14.90 /month Looking glass: 45.88.194.0 https://paste.ubuntu.com/p/Fm2h5jYwnQ/ 本次使用自有资源重新测试

Host Testing and evaluation

@HostEvaluate · Post #706 · 12/25/2020, 12:13 PM

#US#LAX#DMIT#AntiDDOS Host Provider: DMIT Specification: 2 vCore | 2GB RAM | 20G Storage | 1000GB Transfer @ 100Mbps | $14.90 /month Looking glass: 45.88.194.0 https://paste.ubuntu.com/p/F7xxwvpQYh/