---
tags:
  - sign-language
  - how2sign
  - features
---

# How2Sign — Extracted Features

Pre-computed features from the [How2Sign](https://huggingface.co/datasets/aipieces/How2Sign) dataset.

## Layout

Each modality is split by `train` / `test` / `val` and packed into ~3 GB tar shards.

| Modality                            | Content                                          | Approx size |
|-------------------------------------|--------------------------------------------------|-------------|
| `depth_rendered`                    | rendered depth-map JPGs per clip                 | ~39 GB      |
| `poses_rendered`                    | rendered pose-skeleton JPGs per clip             | ~43 GB      |
| `poses`                             | raw pose `.npy` per clip                         | ~18 GB      |
| `optical_flow`                      | optical flow `.npy` per clip                     | ~3 GB       |
| `optical_flow_rendered`             | rendered optical_flow JPGs per clip with stride 2| ~11 GB      |
| `processed_english_translations`    | translations csv per split                       | ~6 MB       |

Inside each tar, paths are relative to the split, e.g.:

    <clip_name>/00000.jpg     # rendered modalities
    <clip_name>.npy           # npy modalities

## Notes on `.npy` files

Poses `.npy` is a 0-d object array wrapping a Python object (typically a dict). Load with:

```python
import numpy as np
data = np.load("clip.npy", allow_pickle=True).item()
```

## Downloading

Everything:

```python
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="Alexeus17071/How2Sign_with_features",
    repo_type="dataset",
    local_dir="./how2sign_features",
)
```

Just one modality/split:

```python
snapshot_download(
    repo_id="Alexeus17071/How2Sign_with_features",
    repo_type="dataset",
    local_dir="./how2sign_features",
    allow_patterns=["poses/train/*"],
)
```

Extract:

```bash
mkdir -p extracted/poses/train
for f in how2sign_features/poses/train/*.tar; do
    tar -xf "$f" -C extracted/poses/train/
done
```