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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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@priborpedals · Post #560 · 10/29/2025, 08:12 AM

А вы знали, что Руководство по эксплуатации модуля Прибор Эксперимент представляет собой сувенирную коллекционную открытку? ️💌 #eurorack#vco#vcf @priborpedals

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@pptdaily · Post #5 · 01/18/2019, 08:56 AM

vcftools基于的是使用bgzip压缩过的vcf.gz文件,还需要用tabix进行index。将多个vcf样本进行merge使用vcf-merge命令,将同一样本的不同vcf整合使用vcf-concat #vcf#vcftools#snp