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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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@English_Speakers · Post #5139 · 12/23/2022, 04:46 PM

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#converisation #Beginner #Daily_life @English_speakers ⚜➖⚜➖⚜➖⚜➖⚜➖ A: I’m going to take a nap. B: You should unplug the phone. A: That’s a good idea. B: Do you want me to wake you in an hour? A: No, thanks. Just let me sleep until I wake up. B: I’ll start dinner at 6:00. A: Okay. I think I’ll be awake by then. B: If not, your nose will wake you up. A: You mean I will smell the food cooking? B: You might even dream about dinner A: I don’t think I’m going to dream about anything. I’m really tired. B: Have a nice nap. Listen and practice 👇

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