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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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@revheadcrypto · Post #62 · 07/08/2024, 01:58 PM

Such a tragic incident, but thankfully the driver came out unharmed 🙏 Hennessy Venom F5 met with an accident while testing at speeds just below 400 km/h on the runway of Kennedy Space Center. The primary aim of the test was to evaluate new aerodynamic details. Regrettably, the crash occurred due to these enhancements: at approximately 386 km/h, the 1817-horsepower Venom F5 took flight and somersaulted several times. While the test prototype suffered damage, the driver remained uninjured. #Hennessy#VenomF5#Crash#HighSpeedTesting#Auto🚗✈️