Super-squash branch 'main' using huggingface_hub

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+*.pcm filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: cc-by-nc-sa-4.0
+task_categories:
+- video-classification
+- image-classification
+language:
+- fr
+tags:
+- sign_language
+- sign_language_processing
+- sign_language_recognition
+- isolated_sign_language_recognition
+- computer_vision
+- natural_language_processing
+pretty_name: LSFB-ISOL (Isolated French Belgian Sign Language Dataset)
+configs:
+  - config_name: "500"
+    data_files:
+      - split: train
+        path:
+          - "shards/500/shard_000003.tar"
+          - "shards/500/shard_000004.tar"
+          - "shards/500/shard_000005.tar"
+          - "shards/500/shard_000006.tar"
+          - "shards/500/shard_000007.tar"
+          - "shards/500/shard_000008.tar"
+          - "shards/500/shard_000009.tar"
+      - split: validation
+        path:
+          - "shards/500/shard_000001.tar"
+          - "shards/500/shard_000002.tar"
+      - split: test
+        path: "shards/500/shard_000000.tar"
+  - config_name: "750"
+    data_files:
+      - split: train
+        path:
+          - "shards/750/shard_000003.tar"
+          - "shards/750/shard_000004.tar"
+          - "shards/750/shard_000005.tar"
+          - "shards/750/shard_000006.tar"
+          - "shards/750/shard_000007.tar"
+          - "shards/750/shard_000008.tar"
+          - "shards/750/shard_000009.tar"
+      - split: validation
+        path:
+          - "shards/750/shard_000001.tar"
+          - "shards/750/shard_000002.tar"
+      - split: test
+        path: "shards/750/shard_000000.tar"
+  - config_name: "2000"
+    data_files:
+      - split: train
+        path:
+          - "shards/2000/shard_000003.tar"
+          - "shards/2000/shard_000004.tar"
+          - "shards/2000/shard_000005.tar"
+          - "shards/2000/shard_000006.tar"
+          - "shards/2000/shard_000007.tar"
+          - "shards/2000/shard_000008.tar"
+          - "shards/2000/shard_000009.tar"
+      - split: validation
+        path:
+          - "shards/2000/shard_000001.tar"
+          - "shards/2000/shard_000002.tar"
+      - split: test
+        path: "shards/2000/shard_000000.tar"
+  - config_name: all
+    data_files:
+      - split: train
+        path:
+          - "shards/all/shard_000003.tar"
+          - "shards/all/shard_000004.tar"
+          - "shards/all/shard_000005.tar"
+          - "shards/all/shard_000006.tar"
+          - "shards/all/shard_000007.tar"
+          - "shards/all/shard_000008.tar"
+          - "shards/all/shard_000009.tar"
+      - split: validation
+        path:
+          - "shards/all/shard_000001.tar"
+          - "shards/all/shard_000002.tar"
+      - split: test
+        path: "shards/all/shard_000000.tar"
+---
+
+# LSFB-ISOL: Isolated French Belgian Sign Language Dataset
+
+LSFB-ISOL is the **isolated-sign** subset of the [LSFB corpus](https://www.corpus-lsfb.be/): one pre-segmented, single-sign clip per sample, extracted from the continuous ([lsfb-cont](https://huggingface.co/datasets/ppoitier/lsfb-cont)) recordings. It is built for **Isolated Sign Language Recognition (ISLR)**.
+
+<video controls src="https://huggingface.co/datasets/ppoitier/lsfb-isol/resolve/main/example.mp4" width="360"></video>
+
+## Dataset structure
+
+The dataset is distributed as [WebDataset](https://github.com/webdataset/webdataset) `.tar` shards, split into four vocabulary-size variants that share the same underlying data:
+
+| Variant | Vocabulary |
+|---|---|
+| `500`   | 500 most frequent signs |
+| `750`   | 750 most frequent signs |
+| `2000`  | 2000 most frequent signs |
+| `all`   | Full vocabulary |
+
+Each variant is split into `train` (shards 3-9), `validation` (shards 1-2) and `test` (shard 0).
+
+Each sample is keyed by a clip id (e.g. `CLSFBI0301A_S008_B_12100_12437`) and contains:
+
+- `pose.<body_part>.npy` — keypoint sequence for one body part (`upper_pose`, `left_hand`, `right_hand`, `lips`, `left_eye`, `right_eye`, `left_eyebrow`, `right_eyebrow`, `left_iris`, `right_iris`)
+- `label.txt` / `label.idx` — the sign gloss (e.g. `bonjour`) and its class index
+- `signer.txt` — anonymized signer id (e.g. `S008`)
+- `language.txt` — always `lsfb`
+- `boundaries.json` — `start_ms` / `end_ms` / `start_frame` / `end_frame` of the clip within its parent recording
+- `linguistic_metadata.json` — `gloss`, `lemma`, `sign_type`
+- `parent.txt` — id of the source continuous recording (see [lsfb-cont](https://huggingface.co/datasets/ppoitier/lsfb-cont))
+
+Raw video clips are stored separately in `videos.tar`, indexed by `videos.tar.index.json` (byte offset/length per clip), so a single clip can be extracted without downloading the whole archive. `example.mp4` is a preview clip.
+
+## Usage
+
+This dataset is designed to be loaded with [sign-language-data-loading](https://github.com/ppoitier/sign-language-data-loading) (`sldl`, [PyPI](https://pypi.org/project/sign-language-data-loading/)), which reads the WebDataset shards directly and handles pose/video decoding, windowing and target encoding:
+
+```bash
+pip install sign-language-data-loading
+```
+
+```python
+from sldl import SignLanguageDataset
+from sldl.configs import LSFBIsolConfig
+
+dataset = SignLanguageDataset.from_config(
+    LSFBIsolConfig(
+        root="path/to/lsfb-isol",  # local clone or download of this repo
+        variant="500",
+        split="training",
+    )
+)
+
+sample = dataset[0]
+print(sample["label"])                             # e.g. "bonjour"
+print(sample["poses"]["upper_pose"].shape)
+```
+
+Pose/annotation transforms (e.g. converting sign boundaries to frame labels) are provided by [sign-language-tools](https://github.com/ppoitier/sign-language-tools) (`slt`, [PyPI](https://pypi.org/project/sign-language-tools/)), which `sldl`'s target encoders build on.
+
+## License
+
+This dataset is distributed under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
+
+## Related projects
+
+- [sign-language-data-loading](https://github.com/ppoitier/sign-language-data-loading) ([PyPI](https://pypi.org/project/sign-language-data-loading/)) — PyTorch-friendly data loading for sign language datasets stored as WebDataset shards; this dataset's intended loader.
+- [sign-language-tools](https://github.com/ppoitier/sign-language-tools) ([PyPI](https://pypi.org/project/sign-language-tools/)) — pose and annotation transforms for sign language processing.
+- [lsfb-cont](https://huggingface.co/datasets/ppoitier/lsfb-cont) — the continuous (untrimmed) counterpart of this dataset, useful for Continuous Sign Language Recognition (CSLR) and Sign Language Segmentation (SLS).

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