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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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Libreware

@libreware · Post #1554 · 02/22/2026, 03:26 PM

The Internet, Reinvented. In this video, I build a #Reticulum#RNode and prove that completely different radios — #LoRa and Wi-Fi — can communicate through a hardware-agnostic networking stack. Reticulum routes traffic above the radio layer, automatically bridging dissimilar frequencies, interfaces, and modulation types. I then run it over Wi-Fi HaLow Haven nodes to create a long-range, encrypted IP #mesh with no traditional infrastructure. Finally, I push it further by running #ATAK across the network, demonstrating a fully open-source, decentralized communication stack in action. Checkout https://rmap.world/ You can install rnode software on your esp32/nrf52 based meshtastic/meshcore hardware