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6ac6bc5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | # UCBProject / ProcessedData
Phase 1A outputs of the Affordance2Grasp pipeline — used by downstream phases:
* **Phase 2** (training the main method's PointNet++ contact-prediction net) reads
`training_fp/{dataset}/{object}.hdf5`.
* **Phase 3** (inference, grasp sampling, sim execution, Sim2Real deployment) reads
per-object affordance priors from `human_prior_fp/{object}.hdf5`.
The upstream object meshes (SAM3D reconstructions) live in a sibling repo,
[`UCBProject/ObjMesh`](https://huggingface.co/datasets/UCBProject/ObjMesh).
## Layout
```
training_fp/
oakink/ 100 files (A* C* O* S* Y* — OakInk object IDs)
dexycb/ 20 files (ycb_dex_01 ... ycb_dex_20 — DexYCB grasp objects)
human_prior_fp/
A01001.hdf5 ... Y35037.hdf5 100 oakink files
ycb_dex_01.hdf5 ... ycb_dex_20.hdf5 20 dexycb files
```
## HDF5 schema
### `training_fp/{ds}/{obj}.hdf5` (training-ready)
| key | shape | dtype | meaning |
|---|---|---|---|
| `point_cloud` | (4096, 3) | float32 | 4096 surface samples of the SAM3D object mesh (metric m, mesh canonical frame) |
| `normals` | (4096, 3) | float32 | per-point unit normals |
| `human_prior` | (4096,) | float32 | per-point contact probability in [0, 1] (Gaussian-smoothed, per-object max-normalised) |
| `robot_gt` | (4096,) | float32 | all-zero placeholder (no robot ground truth for this regime) |
| `force_center` | (3,) | float32 | centroid of mesh verts with `contact_smooth >= 80th percentile` |
| attr `object` | str | — | object id (e.g. `ycb_dex_14` or `A01001`) |
### `human_prior_fp/{obj}.hdf5` (inference-ready, indexed by object only)
Same five fields as above. Same content as `training_fp/{ds}/{obj}.hdf5`, but flattened
across datasets so that `inference/predictor.py` can read by object id alone.
## Provenance
Generated by:
* `data/batch_depth_pro.py` → `data/batch_haptic.py` → `tools/batch_obj_pose.py` → `data/batch_align_mano_fp.py`
* Source raw data: DexYCB (NVIDIA, CC-BY-NC-4.0) + OakInk (CVPR 2022).
* Phase 1A run on lab RTX 5090; OakInk completed 2026-05-10, DexYCB completed 2026-05-14.
HO3D-v3 and ARCTIC are not included here — those will be added when the partner runs
their Phase 1A on those datasets.
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