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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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Hilol dasturlari

@hiloldasturlari · Post #2229 · 12/15/2024, 06:15 AM

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#duo ❄️ Qor yogʻganda oʻqiladigan duo اللَّهُمَّ اغْسِلْ عَنِّي خَطَايَايَ بِمَاءِ الثَّلْجِ وَالْبَرَدِ، وَنَقِ قَلْبِي مِنَ الْخَطَايَا كَمَا نَقَّيْتَ الثَّوْبَ الْأَبْيَضَ مِنَ الدَّنَسِ. 🤲 Allohummagʻsil ʼannii xotooyaaya bimaaʼis salji val barodi, va naqqi qolbii minal xotooyaa kamaa naqqoytas savbal abyado minad danasi. Maʼnosi: Allohim! Xatolarimni qor va muz ila yuvgin. Qalbimni xuddi oq kiyimni kirdan poklaganingdek poklagin. 📚«Hadis va Hayot», 35-juz – «Zikr, duolar, istigʻfor va tavba» kitobidan 🟢Telegram 🟢Instagram 🟢Facebook 🟢YouTube

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