Datasets:

TrackingTeam
/

dagger

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/TrackingTeam/dagger@38ce0759e8d970ec53876729fb071322cc8e16bd/metadata/v6_failures/train/at/seed_101/dagger_selection_plan.json.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 336, in _generate_tables
                  raise ValueError(
                      f"Failed to convert pandas DataFrame to Arrow Table from file {file}."
                  ) from None
              ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/TrackingTeam/dagger@38ce0759e8d970ec53876729fb071322cc8e16bd/metadata/v6_failures/train/at/seed_101/dagger_selection_plan.json.

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OpenTrackVLA DAgger Recovery Dataset

Training-only DAgger recovery data generated in Habitat for OpenTrackVLA target tracking. This release contains V6-policy failure recovery data for AT, DT, and STT, using seeds 101 and 102.

The uploaded payload contains only the final training-ready datasets:

JSONL trajectory labels;
referenced RGB frames;
precomputed DINOv3 + SigLIP fine/coarse visual-token caches;
conversion, filtering, and integrity metadata.

Source rollouts, raw recovery videos, evaluation-scene data, model checkpoints, and EVT-Bench results are not included.

Layout

packed/v6_failures/train/<task>/seed_<seed>/
  jsonl.tar.zst.part-0000...
  frames.tar.zst.part-0000...
  vision_cache.tar.zst.part-0000...
metadata/v6_failures/train/<task>/seed_<seed>/
  dataset_stats.json
  dataset_inspection.json
  dagger_selection_plan.json
  referenced_frames.txt
  *.manifest.json

Each component is a Zstandard-compressed tar stream split into numbered parts. Reconstruct one component with:

cat <component>.tar.zst.part-* | tar --zstd -xf - -C /path/to/dataset

Every component manifest records the ordered part names, byte sizes, and SHA256 checksums. Verify all parts before extraction.

Data policy

This dataset is derived from simulated Habitat/HM3D tracking episodes. Users are responsible for complying with the licenses and terms of the upstream scene, avatar, simulator, and model assets. The other license marker is intentional: it does not replace those upstream terms.

Generation

Split: training scenes and training avatars only
Tasks: AT, DT, STT
Seeds: 101, 102
History: 31 frames
Prediction horizon: 8 waypoints
DAgger target fraction: 0.25
Failure window: 12 steps
Intervention pre/post windows: 12/8 steps
Maximum retained samples per episode: 26

Deterministic Habitat native-process crashes are explicitly audited and excluded; they are never converted into synthetic success/failure labels.

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Total file size:

287 GB