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README.md

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+---
+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       |
+| `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
+```

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