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tianshuwu/sugar
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Language ·
Python
License ·
MIT
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Set up a Python 3.11 conda environment for SUGAR with IsaacSim 5.1.0, IsaacLab 2.3.0, and the pinned flatdict version.
Download the SUGAR data, descriptions, and demo checkpoints from Google Drive with gdown and place them in the expected paths.
Run inference.sh on the StandBottle task with the released tracker and generator checkpoints and capture the simulation video.
Install the CUDA 12.8 torch 2.8.0 wheels on an RTX 5090 box so SUGAR runs on the new GPU.
Extend SUGAR with a new task that loads my own RGB-D human video and trains a tracker, even though the data processing pipeline is not yet released.
Full explanation on explaingit →
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