| --- |
| 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). |
|
|
