The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema: string
clip_id: string
intended_split: string
purpose: string
frames_captured: int64
raw_frames_retained: int64
full_raw_sequence: bool
resolution: list<item: int64>
child 0, item: int64
native_resolution: bool
source_timeline_seconds: double
requested_seconds: int64
requested_duration_completed: bool
capture_and_final_flush_fps: double
minimum_sliding_second_frames: int64
speed_pass: bool
preview_codec: string
preview_is_lossless: bool
interpolation: bool
timestamp_maximum_error_microseconds: int64
source_array_and_pairing_checks_passed: bool
source_checksums_verified: int64
hud_review_status: string
hud_review_sample_count: int64
trajectory_review_status: string
admitted_training_seconds: int64
candidate_status: string
motion_source: string
motion_precision: string
motion_maximum_quantization_error_px: double
outer_compression: string
archive_roundtrip_sha256_verified: bool
anonymization_scope: string
files: list<item: struct<path: string, bytes: int64, sha256: string>>
child 0, item: struct<path: string, bytes: int64, sha256: string>
child 0, path: string
child 1, bytes: int64
child 2, sha256: string
to
{'clip_id': Value('string'), 'files': List({'path': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema: string
clip_id: string
intended_split: string
purpose: string
frames_captured: int64
raw_frames_retained: int64
full_raw_sequence: bool
resolution: list<item: int64>
child 0, item: int64
native_resolution: bool
source_timeline_seconds: double
requested_seconds: int64
requested_duration_completed: bool
capture_and_final_flush_fps: double
minimum_sliding_second_frames: int64
speed_pass: bool
preview_codec: string
preview_is_lossless: bool
interpolation: bool
timestamp_maximum_error_microseconds: int64
source_array_and_pairing_checks_passed: bool
source_checksums_verified: int64
hud_review_status: string
hud_review_sample_count: int64
trajectory_review_status: string
admitted_training_seconds: int64
candidate_status: string
motion_source: string
motion_precision: string
motion_maximum_quantization_error_px: double
outer_compression: string
archive_roundtrip_sha256_verified: bool
anonymization_scope: string
files: list<item: struct<path: string, bytes: int64, sha256: string>>
child 0, item: struct<path: string, bytes: int64, sha256: string>
child 0, path: string
child 1, bytes: int64
child 2, sha256: string
to
{'clip_id': Value('string'), 'files': List({'path': Value('string'), 'bytes': Value('int64'), 'sha256': 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.
Game Sampling Captures
Browse capture packages · Initial video-only pilot
Each capture directory contains its measured metrics, file manifest, complete review MP4, and raw-data.tar.zst. The archive preserves captured RGB and engine motion payloads, source timestamps, camera matrices and frame pairing. It includes a standalone Python reader. Outer compression is lossless; the recorded motion encoding and its precision are specified per capture. Review MP4s are lossy exports and are not the raw training payload.
These are candidate source captures. Uploaded duration is not automatically admitted training duration. Check resolution, frame rate, requested-duration completion, full/partial payload status, HUD review and content admission in each record. Samples require separate target pairing and deduplication before model training.
File names use random IDs. Public metadata omits source game names, local paths and machine identifiers. Gameplay pixels are unchanged and can identify the game. Source mappings and subsequent quality reviews are maintained in the private provenance index.
Each capture has its own manifest.json. The root manifest covers the initial pilot and this overview. Historical manifests remain tied to their immutable commits.
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