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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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EKOLOG.UZ| ENG

@ekologuzenglish · Post #10273 · 11/10/2025, 01:01 PM

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As we approach the #COP30 summit in Brazil, let’s explore some key facts about climate change together. Each number from 1 to 30 highlights an important theme — covering areas such as energy, adaptation, finance, nature, gender equality, health, and justice. At a time when climate-related misinformation is rapidly increasing, the #ClimateCounts initiative helps improve climate literacy — empowering individuals and communities to take bolder climate action and demand stronger commitments. See them all here: https://feature.undp.org/climate-counts/ #ClimateAction#ClimateCounts ☘️Read the latest environmental news on the @ekologuz page. Follow us and send your suggestions and wishes via @eklguz_bot Instagram | Facebook | Twitter | Sayt | Youtube.

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