1 pointby nalinraut6 hours ago1 comment
  • nalinraut6 hours ago
    MARS - Multi Asset Reconstruction for Simulation Transform 2D images into physics-ready 3D scene assets for robotics training.

    Overview

    MARS (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