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Source channel @githubtrending · Post #15062 · Aug 15

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#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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𝗗𝗜𝗔𝗥𝗜𝗢 𝗗𝗘 𝗟𝗔 𝗠𝗟𝗕 ⚾️🇺🇸

@MLB_Daily · Post #16733 · 02/11/2026, 02:02 AM

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👀 Isiah Kiner-Falefa dice que los Blue Jays estaban "contentos" de enfrentarse a los Yankees en lugar de los Red Sox en la Serie Divisional de la Liga Americana porque eran un enfrentamiento "más fácil", escribe Tim Healey del Boston Globe. 🐦 Los Jays avanzaron después de ganar la serie contra los Yankees, 3 juegos a 1. Los Yankees en la temporada regular estaban empatados con Toronto con 94 victorias, pero los Blue Jays ganaron la división a través del desempate cara a cara. Los Red Sox, que ahora tienen a IKF en su equipo, terminaron en tercer lugar con 89 victorias. #️⃣#BlueJays#IKF 🗞 | t.me/MLB_Daily

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