sample/README.md

RoboCloth — sample subset

A small, self-contained slice of RoboCloth for inspecting the data format without downloading terabytes.

What is here

• A handful of complete materials, drawn from the test split and chosen to span different physical sample sizes. The material ids present are the material_<id>/ folders listed above.
• Each material keeps ~12 HDR frames in hdr.tar, evenly subsampled from the full ~580.
• The small per-material files — point_positions.npz, rotated_camera.json, scan_log.json, point_metadata.json, bbox.json, hdr_crop_bboxes.json, unmatched_scan_ids.json — are included verbatim, so names, shapes and dtypes match the full release exactly.
• The per-point observation tensor observations_structured.npz (≈1 GB per material) is not part of the sample; fetch it from materials/<id>/ when you need it (see below).

Mapping back to the full dataset

sample/material_<id>/ here corresponds to materials/<id>/ in the main tree. To pull the same material at full size:

hf download koalapenguin/RoboCloth --repo-type dataset \
    --include "globals/*" --include "materials/<id>/*" --local-dir ./RoboCloth

Download just this subset

hf download koalapenguin/RoboCloth --repo-type dataset \
    --include "sample/*" --include "globals/*" --include "examples/*" \
    --local-dir ./robocloth-sample

Loader

../examples/load_material.py shows how to read every file type in a material directory. Once this subset is downloaded, the same arrays load directly:

import numpy as np
pts = np.load("robocloth-sample/sample/material_<id>/point_positions.npz")
print({k: (pts[k].shape, pts[k].dtype) for k in pts.files})