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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 #832 · 09/26/2022, 04:48 AM

#AEZA#FI#HEL Host Provider: AEZA Location: Helsinki, Finnland (Hetzner) Specification: 1vCore(Ryzen 5950X) | 2GB RAM | 30G NVMe | Unmetered @ 1Gbps | €6.18 / Mo Looking Glass: lg.aeza.net 不贴购买地址了,有需要的话看上面的吧。性能很好,也是他家性能最好的机器了。就是每过半个小时会自动重启一次不知道为什么,而且 SSH Fingerprint 会变。移动回程 telia 绕美,联通 verizon 绕美,电信走 de-cix. 走的和 hetzner 公有云不太一样。 https://paste.red/p/830f0161bbcb

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