# RoboCloth — sample subset

A small, self-contained slice of [RoboCloth](https://huggingface.co/datasets/koalapenguin/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:

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

## Download just this subset

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

## Loader

[`../examples/load_material.py`](../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:

```python
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})
```