---
license: mit
task_categories:
  - robotics
  - object-detection
language:
  - en
tags:
  - robotics
  - grasping
  - affordance
  - hand-object-interaction
  - contact-detection
  - YCB
  - DexYCB
  - HO3D
  - FoundationPose
  - MANO
pretty_name: Affordance2Grasp Preprocessed Assets
size_categories:
  - 1G<n<10G
---

# Affordance2Grasp — Preprocessed Assets

Preprocessed object meshes and initialization files for the
[Affordance2Grasp](https://github.com/stzabl-png/UCB_Project) pipeline.

This repository contains assets you download **once** before running the pipeline.
The pipeline then generates per-dataset intermediate data (depth maps, MANO estimates,
poses, contact labels) from the raw videos, which are not included here due to size and
licensing constraints.

---

## Contents

| Folder | Size | Description |
|---|---|---|
| `obj_meshes/ycb/` | ~1 GB | YCB object meshes + `scale.json` (metric scale) for all objects used in DexYCB and HO3D v3 |
| `obj_recon_input/ycb/` | ~50 MB | FoundationPose initialization masks (reference images + bounding boxes) for each YCB object |
| `training_fp/dexycb/` | ~1 MB | Validated contact labels for DexYCB `ycb_dex_01` and `ycb_dex_02` (sanity-check reference) |

---

## Usage

```bash
pip install huggingface_hub

python -c "
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id='StZaBL/Affordance2Grasp-ProcessedData',
    repo_type='dataset',
    local_dir='data_hub/ProcessedData',
)
"
```

Then follow the pipeline in the
[main repository README](https://github.com/stzabl-png/UCB_Project).

---

## Supported Datasets

Both datasets use the same YCB objects — the meshes here cover all required objects.

| Dataset | Objects covered |
|---|---|
| **DexYCB** | 20 YCB objects (`ycb_dex_01` – `ycb_dex_20`) |
| **HO3D v3** | `003_cracker_box`, `004_sugar_box`, `006_mustard_bottle`, `010_potted_meat_can`, `011_banana`, `021_bleach_cleanser`, `035_power_drill`, `052_extra_large_clamp` |

---

## Raw Data

Raw videos must be downloaded separately from the official sources:

- **DexYCB**: https://dex-ycb.github.io
- **HO3D v3**: https://www.tugraz.at/institute/icg/research/team-lepetit/research-projects/hand-object-3d-pose-annotation

---

## Related

- **Code**: [stzabl-png/UCB_Project](https://github.com/stzabl-png/UCB_Project)
- **Pipeline**: Depth Pro → HaPTIC → FoundationPose → Contact Labels → Affordance Model → Robot Grasp