Show HN: Inferential – Multi-robot inference scheduling on shared GPUsgithub.com2 ポイント·投稿者 nalinraut·4 か月前·0 コメント
nalinraut·5 か月前·議論MARS - Multi Asset Reconstruction for Simulation Transform 2D images into physics-ready 3D scene assets for robotics training.OverviewMARS (Multi Asset Reconstruction for Simulation) is a complete pipeline that:- Detects objects using hybrid vision-language models (Qwen 2.5 VL + GroundingDINO)- Segments objects from images using SAM (Segment Anything Model)- Reconstructs full 3D geometry and textures using SAM 3D Objects- Estimates physics properties (mass, friction, inertia)- Validates scenes with PyBullet physics simulation- Exports to multiple formats (USD, MJCF, URDF)Key Features- Rich TUI Summary: Pipeline displays a comprehensive summary table at completion showing all detected objects, segmentation results, reconstruction status, physics properties, and validation results- Prefect Integration: Full workflow orchestration with Prefect, including plain-text logging compatible with Prefect's logging system- Configurable Models: Support for multiple model variants (Qwen 3B/7B, GroundingDINO tiny/base)- Intelligent Filtering: NMS-based duplicate removal and configurable area filters with include_background option for large objects