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initialneil
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TEDWB1k-preview

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Tags:
3d-human
smpl-x
flame
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gaussian-splatting
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TEDWB1k-preview / README_preview.md
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metadata 
license: cc-by-nc-nd-4.0
language:
  - en
pretty_name: TEDWB1k-preview
size_categories:
  - 1K<n<10K
task_categories:
  - other
tags:
  - 3d-human
  - smpl-x
  - flame
  - avatar
  - gaussian-splatting
  - video
  - motion-capture
  - ted
  - preview
configs:
  - config_name: subjects
    data_files:
      - split: train
        path: metadata/subjects_train.parquet
      - split: train_subset_x1
        path: metadata/subjects_train_subset_x1.parquet
      - split: train_subset_x12
        path: metadata/subjects_train_subset_x12.parquet
      - split: train_val
        path: metadata/subjects_train_val.parquet
      - split: test
        path: metadata/subjects_test.parquet

TEDWB1k-preview

⚠️ This is the public preview of initialneil/TEDWB1k. The full dataset (1,431 TED-talk speakers, ~120 GB) is hosted at the gated repo above. This preview repo exists so the HuggingFace Dataset Viewer can render the per-subject thumbnails and tracking grids without going through the gated EULA flow.

If you want the full training data (frames + mattes + per-frame SMPL-X / FLAME tracking for all 1,431 subjects), go to the gated main repo, accept the agreement, and use load_tedwb1k.py.

What's in this preview

This repo is schema-identical to the gated main repo, but it's a lightweight catalog + sample rather than a full mirror:

What Subjects Size
Per-split parquets with embedded source-frame thumbnails 1,431 ~210 MB
metadata/previews/<id>.jpg (1024×1024 source frames) 1,431 ~210 MB
Per-subject heavy data (frames.tar + mattes.tar + tracking) 12 ~540 MB
Total preview ~1 GB

The HF Dataset Viewer above renders 5 tabs (train, train_subset_x1, train_subset_x12, train_val, test) with one row per subject, the per-subject frame and shot counts, and a thumbnail of the first source frame (the actual shots_images/<id>/<first_shot>/000000.jpg that the tracker consumed).

For full-resolution per-subject tracking visualizations (metadata/ehm/<id>.jpg, metadata/flame/<id>.jpg, metadata/base/<id>.jpg), go to the gated main repo — they're fetchable per-subject without downloading the heavy frames.tar/mattes.tar.

Quick start

If you only want to play with one of the 12 sample subjects (no agreement required):

pip install huggingface_hub

python -c "
from huggingface_hub import snapshot_download
snapshot_download(
    'initialneil/TEDWB1k-preview',
    repo_type='dataset',
    allow_patterns='subjects/-2Dj9M71JAc/*',
    local_dir='./tedwb1k_x1',
)
"

That gives you tracking pickles + frames.tar + mattes.tar for one sample subject in a few seconds. To turn it into the 5-file bundle that HolisticAvatar's TrackedData expects, use the same load_tedwb1k.py from the main repo:

wget https://huggingface.co/datasets/initialneil/TEDWB1k/raw/main/load_tedwb1k.py
python load_tedwb1k.py --split train_subset_x1 --out ./tedwb1k_x1 \
    --repo_id initialneil/TEDWB1k-preview

For the full 1,361-subject training set, request access at the gated main repo.

Per-subject visualizations

In this preview, each of the 1,431 subjects has one standalone visualization file:

  • metadata/previews/<id>.jpg — clean 1024×1024 source frame (the first frame of the first shot). Also embedded in the parquet preview column so the HF Dataset Viewer renders it inline.

For full-resolution SMPL-X / FLAME / PIXIE+Sapiens overlay grids, head to the gated main repo where each subject also has:

  • metadata/ehm/<id>.jpg — final SMPL-X overlay grid (~13 MB)
  • metadata/flame/<id>.jpg — intermediate FLAME overlay grid (~6 MB)
  • metadata/base/<id>.jpg — stage-1 PIXIE+Sapiens overlay grid (~4 MB)

You can fetch any single subject's full-res visualization from the main repo (after accepting the gating EULA) with one hf_hub_download call:

from huggingface_hub import hf_hub_download
path = hf_hub_download(
    'initialneil/TEDWB1k',
    'metadata/ehm/05jJodDVJRQ.jpg',
    repo_type='dataset',
)

Splits

Same as the main repo:

Split Subjects Notes
train_subset_x1 1 tiny single-subject overfit (⊂ train)
train_subset_x12 12 small overfit (⊂ train) — the only subjects with downloadable heavy data in this preview
train_val 20 training monitor (⊂ train)
test 70 identity-disjoint evaluation
train 1,361 full training pool
total 1,431

train (1,361) and test (70) are identity-disjoint and together cover all 1,431 subjects. train_subset_x1, train_subset_x12, and train_val are subsets of train.

Why two repos?

HuggingFace's Dataset Viewer cannot render tabs/thumbnails for gated datasets — the worker that computes split names runs without a user identity and can't satisfy the gating EULA. The full TEDWB1k is gated for TED-content compliance, so to keep the viewer working we mirror the metadata + a 12-subject sample to this public preview repo.

For full discussion see this thread: https://discuss.huggingface.co/t/after-gated-user-access-was-enabled-the-huggingface-not-showing-dataset-viewer/157333

License

CC-BY-NC-ND 4.0 — same as the main repo. Non-commercial research use only. Attribution required. No derivatives — you may not distribute modified or remixed versions of this dataset.

The tracking parameters, JPG frames, and mattes are all derived works of TED talk videos that are themselves CC-BY-NC-ND on ted.com. This dataset matches the upstream license to remain compatible with TED's source restrictions.

Links