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Datasets:
ppoitier
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lsfb-isol

Tasks:
Video Classification
Image Classification
Languages:
French
Tags:
sign_language
sign_language_processing
sign_language_recognition
isolated_sign_language_recognition
computer_vision
natural_language_processing
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metadata 
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: one pre-segmented, single-sign clip per sample, extracted from the continuous (lsfb-cont) recordings. It is built for Isolated Sign Language Recognition (ISLR).

Dataset structure

The dataset is distributed as 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)

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 (sldl, PyPI), which reads the WebDataset shards directly and handles pose/video decoding, windowing and target encoding:

pip install sign-language-data-loading

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 (slt, PyPI), which sldl's target encoders build on.

License

This dataset is distributed under CC BY-NC-SA 4.0.

Related projects

  • sign-language-data-loading (PyPI) — PyTorch-friendly data loading for sign language datasets stored as WebDataset shards; this dataset's intended loader.
  • sign-language-tools (PyPI) — pose and annotation transforms for sign language processing.
  • lsfb-cont — the continuous (untrimmed) counterpart of this dataset, useful for Continuous Sign Language Recognition (CSLR) and Sign Language Segmentation (SLS).