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
exposure_s: double
K: list<item: double>
child 0, item: double
t: double
i: int64
rgb: string
tracking: string
pose: list<item: double>
child 0, item: double
depth: string
h: int64
video: bool
w: int64
finished: timestamp[s]
system: string
depth_height: int64
imu_hz: int64
duration_s: double
n_imu: int64
export_images: string
n_exported: int64
device_machine: string
lidar_available: bool
created: timestamp[s]
mock: bool
device_model: string
rgb_width: int64
mode: string
export_fps: int64
rgb_height: int64
lidar_on: bool
n_frames: int64
conventions: struct<depth: string, imu: string, K: string, pose: string, time: string>
child 0, depth: string
child 1, imu: string
child 2, K: string
child 3, pose: string
child 4, time: string
depth_width: int64
n_depth: int64
n_dropped_video: int64
export_source: string
to
{'conventions': {'depth': Value('string'), 'imu': Value('string'), 'K': Value('string'), 'pose': Value('string'), 'time': Value('string')}, 'created': Value('timestamp[s]'), 'depth_height': Value('int64'), 'depth_width': Value('int64'), 'device_machine': Value('string'), 'device_model': Value('string'), 'duration_s': Value('float64'), 'export_fps': Value('int64'), 'export_images': Value('string'), 'export_source': Value('string'), 'finished': Value('timestamp[s]'), 'imu_hz': Value('int64'), 'lidar_available': Value('bool'), 'lidar_on': Value('bool'), 'mock': Value('bool'), 'mode': Value('string'), 'n_depth': Value('int64'), 'n_dropped_video': Value('int64'), 'n_exported': Value('int64'), 'n_frames': Value('int64'), 'n_imu': Value('int64'), 'rgb_height': Value('int64'), 'rgb_width': Value('int64'), 'system': 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
exposure_s: double
K: list<item: double>
child 0, item: double
t: double
i: int64
rgb: string
tracking: string
pose: list<item: double>
child 0, item: double
depth: string
h: int64
video: bool
w: int64
finished: timestamp[s]
system: string
depth_height: int64
imu_hz: int64
duration_s: double
n_imu: int64
export_images: string
n_exported: int64
device_machine: string
lidar_available: bool
created: timestamp[s]
mock: bool
device_model: string
rgb_width: int64
mode: string
export_fps: int64
rgb_height: int64
lidar_on: bool
n_frames: int64
conventions: struct<depth: string, imu: string, K: string, pose: string, time: string>
child 0, depth: string
child 1, imu: string
child 2, K: string
child 3, pose: string
child 4, time: string
depth_width: int64
n_depth: int64
n_dropped_video: int64
export_source: string
to
{'conventions': {'depth': Value('string'), 'imu': Value('string'), 'K': Value('string'), 'pose': Value('string'), 'time': Value('string')}, 'created': Value('timestamp[s]'), 'depth_height': Value('int64'), 'depth_width': Value('int64'), 'device_machine': Value('string'), 'device_model': Value('string'), 'duration_s': Value('float64'), 'export_fps': Value('int64'), 'export_images': Value('string'), 'export_source': Value('string'), 'finished': Value('timestamp[s]'), 'imu_hz': Value('int64'), 'lidar_available': Value('bool'), 'lidar_on': Value('bool'), 'mock': Value('bool'), 'mode': Value('string'), 'n_depth': Value('int64'), 'n_dropped_video': Value('int64'), 'n_exported': Value('int64'), 'n_frames': Value('int64'), 'n_imu': Value('int64'), 'rgb_height': Value('int64'), 'rgb_width': Value('int64'), 'system': 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.
AR collections
iPhone captures from ARCapture, one zip per
recording under sessions/ (10 fps exports), each with its meta.json beside it.
*_ar_lidar_10fps.zip/*_ar_10fps.zip: ARKit poses (camera-to-world, gravity-aligned), intrinsics, RGB JPEGs, LiDAR depth (float32 metres, 0 = invalid) when present, IMU at 100 Hz.*_stereo_10fps.zip: Wide + Ultra-wide synchronized pairs, per-frame intrinsics, factory extrinsics,calib/(calibration board) thenscene/, IMU at 100 Hz. No pose.
Format details: the ARCapture README.
- Downloads last month
- 104