Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
stem: string
T: int64
H: int64
W: int64
act_dim: int64
img_bytes: int64
act_bytes: int64
action_dim: int64
bad: list<item: struct<stem: string, reason: string>>
child 0, item: struct<stem: string, reason: string>
child 0, stem: string
child 1, reason: string
hours_20hz: double
total_frames: int64
dest: string
image_shape: string
quarantine_episode_files: int64
good_episodes: int64
quarantine_raw_files: int64
source: string
bad_episodes: int64
moved_raw_files: int64
moved_episode_files: int64
to
{'source': Value('string'), 'dest': Value('string'), 'good_episodes': Value('int64'), 'bad_episodes': Value('int64'), 'total_frames': Value('int64'), 'hours_20hz': Value('float64'), 'moved_episode_files': Value('int64'), 'quarantine_episode_files': Value('int64'), 'moved_raw_files': Value('int64'), 'quarantine_raw_files': Value('int64'), 'image_shape': Value('string'), 'action_dim': Value('int64'), 'bad': List({'stem': Value('string'), 'reason': Value('string')})}
because column names don't match
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 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
stem: string
T: int64
H: int64
W: int64
act_dim: int64
img_bytes: int64
act_bytes: int64
action_dim: int64
bad: list<item: struct<stem: string, reason: string>>
child 0, item: struct<stem: string, reason: string>
child 0, stem: string
child 1, reason: string
hours_20hz: double
total_frames: int64
dest: string
image_shape: string
quarantine_episode_files: int64
good_episodes: int64
quarantine_raw_files: int64
source: string
bad_episodes: int64
moved_raw_files: int64
moved_episode_files: int64
to
{'source': Value('string'), 'dest': Value('string'), 'good_episodes': Value('int64'), 'bad_episodes': Value('int64'), 'total_frames': Value('int64'), 'hours_20hz': Value('float64'), 'moved_episode_files': Value('int64'), 'quarantine_episode_files': Value('int64'), 'moved_raw_files': Value('int64'), 'quarantine_raw_files': Value('int64'), 'image_shape': Value('string'), 'action_dim': Value('int64'), 'bad': List({'stem': Value('string'), 'reason': Value('string')})}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
pan-2 VPT
Cleaned OpenAI VPT contractor demos, packed for Infatoshi/pan-2.
This is not a re-dump of the original VPT Azure blobs, and it is not the same layout as zhwang4ai/OpenAI-Minecraft-Contractor (jsonl-only), p-doom/openai-minecraft-dataset (Grain/ArrayRecord tars), or TESS-Computer/minecraft-vla-stage1 (parquet JPEGs at 640x360 / 5 Hz).
| Episodes | 1625 validated stems (27 dropped) |
| Frames | 8,155,382 (~113.3 h at 20 Hz) |
| Image | uint8 [T, 64, 64, 3] |
| Actions | float32 [T, 25] (23 buttons + camera dx/dy in [-1, 1]) |
| Raw video | H.264 640x360 @ 20 fps, sibling jsonl |
Layout
raw/<stem>.mp4
raw/<stem>.jsonl # original VPT per-tick action dicts
episodes/<stem>.img.npy # (T, 64, 64, 3) uint8
episodes/<stem>.act.npy # (T, 25) float32
shards/manifest.jsonl
shards/shard-XXXXX.frames.npy
shards/shard-XXXXX.act.npy
meta/README.md
meta/cleanup_summary.json
meta/episodes_manifest.jsonl
Episodes never straddle shards. manifest.jsonl starts with a header:
{"type":"header","version":1,"image_size":64,"act_dim":25,"n_shards":24,"total_frames":8155382,"total_episodes":1625}
then one segment row per episode (shard, stem, offset, n_frames, has_act).
Load shards
import json
from pathlib import Path
import numpy as np
root = Path("shards")
header = json.loads(root.joinpath("manifest.jsonl").read_text().splitlines()[0])
frames = np.load(root / "shard-00000.frames.npy", mmap_mode="r") # (N, 64, 64, 3) uint8
acts = np.load(root / "shard-00000.act.npy", mmap_mode="r") # (N, 25) float32
Rebuild shards from episodes with the pan-2 repo:
uv run python scripts/build_shards.py --source episodes --episodes-dir episodes --out shards
Source
OpenAI Video PreTraining contractor data (Baker et al., 2022). Original index/blobs: https://openaipublic.blob.core.windows.net/. Some origin mp4s 404; this tree is the surviving cleaned 1625-stem subset used for pan-2.
Action columns: see src/pan2/actions.py in the code repo.
License
MIT, same as the upstream VPT contractor release. Cite OpenAI VPT if you use this.
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