README.md

metadata

license: other
task_categories:
  - image-segmentation
tags:
  - robotics
  - video
  - foreground-segmentation

RoboMME demonstration-prefix frames with foreground masks

The demonstration prefix of RoboMME episodes -- the video-instruction frames, where info/is_video_demo is True -- together with a binary foreground mask for each frame.

These frames are worth publishing separately because they are missing from the usual export: the pickle conversion that training pipelines consume writes a file only when is_demo is False, so the demo prefix (292k of RoboMME's 769k frames) exists only in the raw HDF5. Of the 16 tasks, 9 carry a demo prefix; the other 7 have none.

Contents

<Task>/episode_<NNNN>/rgb/00000.png    front camera, 256x256 RGB, raw pixels
<Task>/episode_<NNNN>/mask/00000.png   1-bit foreground mask, same size
<Task>/episode_<NNNN>/done.json        demo_len, num_timesteps, per-frame foreground fraction
demo_manifest.json                     the episode list and demo lengths

Frame 00000 is absolute timestep 0 of the episode, and frames run to demo_len - 1. RGB is untouched: no crop, no resize, no normalisation, so any preprocessing is the consumer's choice.

Masks

ZhengPeng7/BiRefNet_lite, run at 1024x1024 and thresholded at 0.5, then resized back to 256. The resolution matters: below roughly 512 the mask comes back essentially empty, which makes a foreground-weighted loss put most of its weight on the wooden table instead of the arm and the objects.

The masks are model output, not ground truth. They are accurate on the arm and the manipulated objects and they do pick up small painted markers, but they are not a substitute for simulator segmentation.

Provenance and licence

Frames are derived from the RoboMME dataset; its licence governs their use. The masks are generated by BiRefNet_lite (MIT). Nothing here is human-annotated.