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
samples: list<item: struct<_id: struct<$oid: string>, filepath: string, tags: list<item: null>, _media_type: (... 134 chars omitted)
child 0, item: struct<_id: struct<$oid: string>, filepath: string, tags: list<item: null>, _media_type: string, _ra (... 122 chars omitted)
child 0, _id: struct<$oid: string>
child 0, $oid: string
child 1, filepath: string
child 2, tags: list<item: null>
child 0, item: null
child 3, _media_type: string
child 4, _rand: double
child 5, _dataset_id: struct<$oid: string>
child 0, $oid: string
child 6, created_at: struct<$date: string>
child 0, $date: string
child 7, last_modified_at: struct<$date: string>
child 0, $date: string
group_media_types: null
info: null
app_config: null
classes: null
mask_targets: null
default_mask_targets: null
skeletons: null
camera_intrinsics: null
static_transforms: null
annotation_runs: null
brain_methods: null
evaluations: null
runs: null
label_schemas: null
frame_label_schemas: null
last_deletion_at: null
last_loaded_at: struct<$date: string>
child 0, $date: string
default_classes: list<item: null>
child 0, item: null
frame_fields: list<item: null>
child 0, item: null
persistent: bool
active_label_schemas: list<item: null>
child 0, item: null
workspaces: list<item: null>
child 0, item: null
slug: string
tags: list<item: null>
child 0, item: null
created_at: struct<$date: string>
child 0, $date: string
_i
...
tring, embedded_doc_type: string, subfield: string, fields: (... 318 chars omitted)
child 0, item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: (... 306 chars omitted)
child 0, name: string
child 1, ftype: string
child 2, embedded_doc_type: string
child 3, subfield: string
child 4, fields: list<item: struct<name: string, ftype: string, embedded_doc_type: null, subfield: null, fields: list (... 115 chars omitted)
child 0, item: struct<name: string, ftype: string, embedded_doc_type: null, subfield: null, fields: list<item: null (... 103 chars omitted)
child 0, name: string
child 1, ftype: string
child 2, embedded_doc_type: null
child 3, subfield: null
child 4, fields: list<item: null>
child 0, item: null
child 5, db_field: string
child 6, description: null
child 7, info: null
child 8, read_only: bool
child 9, created_at: struct<$date: string>
child 0, $date: string
child 5, db_field: string
child 6, description: null
child 7, info: null
child 8, read_only: bool
child 9, created_at: struct<$date: string>
child 0, $date: string
last_modified_at: struct<$date: string>
child 0, $date: string
version: string
name: string
saved_views: list<item: null>
child 0, item: null
to
{'_id': {'$oid': Value('string')}, 'name': Value('string'), 'slug': Value('string'), 'version': Value('string'), 'created_at': {'$date': Value('string')}, 'last_modified_at': {'$date': Value('string')}, 'last_deletion_at': Value('null'), 'last_loaded_at': {'$date': Value('string')}, 'sample_collection_name': Value('string'), 'persistent': Value('bool'), 'media_type': Value('string'), 'group_media_types': Json(decode=True), 'tags': List(Value('null')), 'info': Json(decode=True), 'app_config': {'dynamic_groups_target_frame_rate': Value('int64'), 'grid_media_field': Value('string'), 'media_fallback': Value('bool'), 'media_fields': List(Value('string')), 'modal_media_field': Value('string'), 'plugins': Json(decode=True)}, 'classes': Json(decode=True), 'default_classes': List(Value('null')), 'mask_targets': Json(decode=True), 'default_mask_targets': Json(decode=True), 'skeletons': Json(decode=True), 'camera_intrinsics': Json(decode=True), 'static_transforms': Json(decode=True), 'sample_fields': List({'name': Value('string'), 'ftype': Value('string'), 'embedded_doc_type': Value('string'), 'subfield': Value('string'), 'fields': List({'name': Value('string'), 'ftype': Value('string'), 'embedded_doc_type': Value('null'), 'subfield': Value('null'), 'fields': List(Value('null')), 'db_field': Value('string'), 'description': Value('null'), 'info': Value('null'), 'read_only': Value('bool'), 'created_at': {'$date': Value('string')}}), 'db_field': Value('string'), 'description': Value('null'), 'info': Value('null'), 'read_only': Value('bool'), 'created_at': {'$date': Value('string')}}), 'frame_fields': List(Value('null')), 'saved_views': List(Value('null')), 'workspaces': List(Value('null')), 'annotation_runs': Json(decode=True), 'brain_methods': Json(decode=True), 'evaluations': Json(decode=True), 'runs': Json(decode=True), 'active_label_schemas': List(Value('null')), 'label_schemas': Json(decode=True), 'frame_label_schemas': Json(decode=True)}
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
samples: list<item: struct<_id: struct<$oid: string>, filepath: string, tags: list<item: null>, _media_type: (... 134 chars omitted)
child 0, item: struct<_id: struct<$oid: string>, filepath: string, tags: list<item: null>, _media_type: string, _ra (... 122 chars omitted)
child 0, _id: struct<$oid: string>
child 0, $oid: string
child 1, filepath: string
child 2, tags: list<item: null>
child 0, item: null
child 3, _media_type: string
child 4, _rand: double
child 5, _dataset_id: struct<$oid: string>
child 0, $oid: string
child 6, created_at: struct<$date: string>
child 0, $date: string
child 7, last_modified_at: struct<$date: string>
child 0, $date: string
group_media_types: null
info: null
app_config: null
classes: null
mask_targets: null
default_mask_targets: null
skeletons: null
camera_intrinsics: null
static_transforms: null
annotation_runs: null
brain_methods: null
evaluations: null
runs: null
label_schemas: null
frame_label_schemas: null
last_deletion_at: null
last_loaded_at: struct<$date: string>
child 0, $date: string
default_classes: list<item: null>
child 0, item: null
frame_fields: list<item: null>
child 0, item: null
persistent: bool
active_label_schemas: list<item: null>
child 0, item: null
workspaces: list<item: null>
child 0, item: null
slug: string
tags: list<item: null>
child 0, item: null
created_at: struct<$date: string>
child 0, $date: string
_i
...
tring, embedded_doc_type: string, subfield: string, fields: (... 318 chars omitted)
child 0, item: struct<name: string, ftype: string, embedded_doc_type: string, subfield: string, fields: list<item: (... 306 chars omitted)
child 0, name: string
child 1, ftype: string
child 2, embedded_doc_type: string
child 3, subfield: string
child 4, fields: list<item: struct<name: string, ftype: string, embedded_doc_type: null, subfield: null, fields: list (... 115 chars omitted)
child 0, item: struct<name: string, ftype: string, embedded_doc_type: null, subfield: null, fields: list<item: null (... 103 chars omitted)
child 0, name: string
child 1, ftype: string
child 2, embedded_doc_type: null
child 3, subfield: null
child 4, fields: list<item: null>
child 0, item: null
child 5, db_field: string
child 6, description: null
child 7, info: null
child 8, read_only: bool
child 9, created_at: struct<$date: string>
child 0, $date: string
child 5, db_field: string
child 6, description: null
child 7, info: null
child 8, read_only: bool
child 9, created_at: struct<$date: string>
child 0, $date: string
last_modified_at: struct<$date: string>
child 0, $date: string
version: string
name: string
saved_views: list<item: null>
child 0, item: null
to
{'_id': {'$oid': Value('string')}, 'name': Value('string'), 'slug': Value('string'), 'version': Value('string'), 'created_at': {'$date': Value('string')}, 'last_modified_at': {'$date': Value('string')}, 'last_deletion_at': Value('null'), 'last_loaded_at': {'$date': Value('string')}, 'sample_collection_name': Value('string'), 'persistent': Value('bool'), 'media_type': Value('string'), 'group_media_types': Json(decode=True), 'tags': List(Value('null')), 'info': Json(decode=True), 'app_config': {'dynamic_groups_target_frame_rate': Value('int64'), 'grid_media_field': Value('string'), 'media_fallback': Value('bool'), 'media_fields': List(Value('string')), 'modal_media_field': Value('string'), 'plugins': Json(decode=True)}, 'classes': Json(decode=True), 'default_classes': List(Value('null')), 'mask_targets': Json(decode=True), 'default_mask_targets': Json(decode=True), 'skeletons': Json(decode=True), 'camera_intrinsics': Json(decode=True), 'static_transforms': Json(decode=True), 'sample_fields': List({'name': Value('string'), 'ftype': Value('string'), 'embedded_doc_type': Value('string'), 'subfield': Value('string'), 'fields': List({'name': Value('string'), 'ftype': Value('string'), 'embedded_doc_type': Value('null'), 'subfield': Value('null'), 'fields': List(Value('null')), 'db_field': Value('string'), 'description': Value('null'), 'info': Value('null'), 'read_only': Value('bool'), 'created_at': {'$date': Value('string')}}), 'db_field': Value('string'), 'description': Value('null'), 'info': Value('null'), 'read_only': Value('bool'), 'created_at': {'$date': Value('string')}}), 'frame_fields': List(Value('null')), 'saved_views': List(Value('null')), 'workspaces': List(Value('null')), 'annotation_runs': Json(decode=True), 'brain_methods': Json(decode=True), 'evaluations': Json(decode=True), 'runs': Json(decode=True), 'active_label_schemas': List(Value('null')), 'label_schemas': Json(decode=True), 'frame_label_schemas': Json(decode=True)}
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.
RoboLab-EgoX 3D Robot Mesh Demo (FiftyOne Multimodal)
A single episode from Voxel51/RoboLab-EgoX
(BBQSauceInBinTask_aerodynamics_workshop_sf50), augmented with a real, moving 3D
Franka Panda + Robotiq 2F-85 gripper mesh rendered directly from the episode's own
joint-position telemetry — the same visual effect as Rerun's URDF playback.
What's new versus the source episode
Two channels were added on top of the original ego/exo camera streams and joint telemetry (nothing removed):
/robolab-egox-model(foxglove.SceneUpdate): 19 link meshes (8 Panda arm links- 11 Robotiq 2F-85 gripper links), each a
.glbembedded directly in the message.
- 11 Robotiq 2F-85 gripper links), each a
/robolab-egox-transforms(foxglove.FrameTransforms): one directworld -> linkpose per link per frame, computed via forward kinematics (yourdfpy) from the episode's/joint-positionschannel.
The Panda-to-gripper mounting transform uses Franka Robotics' own published
external gripper example
(panda_link8 -> robotiq_arg2f_base_link, zero translation, +90° yaw). Forward
kinematics were cross-checked against this episode's own recorded
/end-effector-pose channel: 1.9mm mean / 2.1mm max residual across the episode.
Usage
pip install -U fiftyone
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
dataset = load_from_hub("adonaivera/robolab-egox-3d-demo")
session = fo.launch_app(dataset)
In the App, open the sample and switch the 3D tile's Scene > World > Reference
Frame to world (a leaf frame is picked by default and will show nothing), then
enable the robolab-egox-model layer under the 3D tab's 3D Labels section.
Known approximations
- The 5 non-actuated Robotiq gripper joints are driven via the URDF's documented mimic multipliers from the one empirically-identified actuated joint, not their own individually-verified recorded values (contact dynamics during real grasps can make the raw per-finger telemetry not perfectly mirror-symmetric).
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