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
success: bool
repo_id: string
episodes: int64
frames: int64
fps: int64
method: string
idle_mask: bool
exporter_commit: string
camera_intrinsics: struct<head_camera: list<item: list<item: double>>, left_camera: list<item: list<item: double>>, rig (... 42 chars omitted)
child 0, head_camera: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 1, left_camera: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, right_camera: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
source_slots: list<item: int64>
child 0, item: int64
values: string
feature_details: struct<task_index: struct<dimensions: int64, constant_dimensions: list<item: int64>, zero_quantile_i (... 1509 chars omitted)
child 0, task_index: struct<dimensions: int64, constant_dimensions: list<item: int64>, zero_quantile_interval_dimensions: (... 19 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: int64>
child 0, item: int64
child 2, zero_quantile_interval_dimensions: list<item: int64>
child 0, item: int64
child 1, retime.grid_index: struct<dimensions: int64, constant_dimensions: list<item: int64>, zero_quantile_interval_dimensions: (... 19 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: int64>
child 0, item: int64
...
ions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
child 9, timestamp: struct<dimensions: int64, constant_dimensions: list<item: null>, zero_quantile_interval_dimensions: (... 17 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
child 10, episode_index: struct<dimensions: int64, constant_dimensions: list<item: null>, zero_quantile_interval_dimensions: (... 17 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
child 11, observation.state: struct<dimensions: int64, constant_dimensions: list<item: null>, zero_quantile_interval_dimensions: (... 17 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
image_statistics: string
implementation_commit: string
features: list<item: string>
child 0, item: string
quantiles: list<item: double>
child 0, item: double
algorithm: string
stats_sha256: string
sampling: string
to
{'algorithm': Value('string'), 'method': Value('string'), 'values': Value('string'), 'sampling': Value('string'), 'quantiles': List(Value('float64')), 'features': List(Value('string')), 'feature_details': {'task_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('int64')), 'zero_quantile_interval_dimensions': List(Value('int64'))}, 'retime.grid_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('int64')), 'zero_quantile_interval_dimensions': List(Value('int64'))}, 'retime.source_slot': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'retime.offset_s': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'retime.source_seed': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'frame_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'action': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'retime.u': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'timestamp': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'episode_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'observation.state': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}}, 'frames': Value('int64'), 'stats_sha256': Value('string'), 'implementation_commit': Value('string'), 'image_statistics': 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
success: bool
repo_id: string
episodes: int64
frames: int64
fps: int64
method: string
idle_mask: bool
exporter_commit: string
camera_intrinsics: struct<head_camera: list<item: list<item: double>>, left_camera: list<item: list<item: double>>, rig (... 42 chars omitted)
child 0, head_camera: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 1, left_camera: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 2, right_camera: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
source_slots: list<item: int64>
child 0, item: int64
values: string
feature_details: struct<task_index: struct<dimensions: int64, constant_dimensions: list<item: int64>, zero_quantile_i (... 1509 chars omitted)
child 0, task_index: struct<dimensions: int64, constant_dimensions: list<item: int64>, zero_quantile_interval_dimensions: (... 19 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: int64>
child 0, item: int64
child 2, zero_quantile_interval_dimensions: list<item: int64>
child 0, item: int64
child 1, retime.grid_index: struct<dimensions: int64, constant_dimensions: list<item: int64>, zero_quantile_interval_dimensions: (... 19 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: int64>
child 0, item: int64
...
ions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
child 9, timestamp: struct<dimensions: int64, constant_dimensions: list<item: null>, zero_quantile_interval_dimensions: (... 17 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
child 10, episode_index: struct<dimensions: int64, constant_dimensions: list<item: null>, zero_quantile_interval_dimensions: (... 17 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
child 11, observation.state: struct<dimensions: int64, constant_dimensions: list<item: null>, zero_quantile_interval_dimensions: (... 17 chars omitted)
child 0, dimensions: int64
child 1, constant_dimensions: list<item: null>
child 0, item: null
child 2, zero_quantile_interval_dimensions: list<item: null>
child 0, item: null
image_statistics: string
implementation_commit: string
features: list<item: string>
child 0, item: string
quantiles: list<item: double>
child 0, item: double
algorithm: string
stats_sha256: string
sampling: string
to
{'algorithm': Value('string'), 'method': Value('string'), 'values': Value('string'), 'sampling': Value('string'), 'quantiles': List(Value('float64')), 'features': List(Value('string')), 'feature_details': {'task_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('int64')), 'zero_quantile_interval_dimensions': List(Value('int64'))}, 'retime.grid_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('int64')), 'zero_quantile_interval_dimensions': List(Value('int64'))}, 'retime.source_slot': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'retime.offset_s': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'retime.source_seed': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'frame_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'action': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'retime.u': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'timestamp': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'episode_index': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}, 'observation.state': {'dimensions': Value('int64'), 'constant_dimensions': List(Value('null')), 'zero_quantile_interval_dimensions': List(Value('null'))}}, 'frames': Value('int64'), 'stats_sha256': Value('string'), 'implementation_commit': Value('string'), 'image_statistics': 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.
ctr-sortblocks-100ep-mixed
100 native RoboTwin Blocks Ranking RGB-CTR expert episodes in LeRobot v3 format. This is synthetic expert data, not a learned-policy benchmark.
Task
The left arm places red then yellow; the right arm places blue then green. Initial red/blue and yellow/green poses are mirrored across the arm bisector. Final world-x order is red, yellow, blue, green. Group centers are 0.52 m apart. Every physics step checks a conservative minimum 0.10 m cross-arm/actor clearance. The lowest recorded clearance in this dataset is 0.112213 m.
Sampling
Concatenation of 34 left-first Sequential episodes (slots 0–33), 33 right-first Sequential episodes (slots 50–82), and 33 Concurrent episodes (slots 34–49 and 83–99). These 100 scene slots are disjoint and collectively cover the same cohort.
All four companion datasets use the same 100 accepted initial scenes and frozen per-scene joint/gripper controls. Timing changes do not change trajectory speed. Mixed reuses the selected source episodes; it introduces no new simulation scenes. Source scene IDs, control hashes and exact offsets are in meta/retime_manifest.json.
Contents
- Episodes: 100; training rows: 76301; FPS: 25; physics: 250 Hz.
- Robot: Aloha AgileX; observation.state: 14 measured joint/gripper values.
- action: 14 commanded joint/gripper targets at the next recorded observation.
- Images:top, left_wrist and right_wrist, 320×240 RGB H.264 video.
- Wrist preset: centered_fovy90, including calibrated optical-axis mounts.
- Fixed wider head intrinsics: fx=fy=260 px, cx=160, cy=120.
- Last observations are verification/next-target material, not extra action rows.
IdleMask
This non-CTR dataset has no IdleMask columns. Training with this dataset does not enable IdleMask.
Statistics and provenance
Numeric publication statistics use all valid published numeric rows, with exact global linear quantiles computed after promotion to float64. This includes state, action, timestamps and timing metadata. Image quantiles are omitted; native LeRobot sampled image mean/std estimates are retained. There is no episode-quantile averaging, padding, or mask-based exclusion. Training-specific delta/action-window normalization is a separate transform.
meta/source_programs contains the frozen controls and initial scenes. .ctr-revision.json identifies the generated scene/control manifest; the immutable Hugging Face commit is recorded in the external publication receipt. SHA256SUMS pins the uploaded files. All episodes passed task success, camera, control-integrity and timing checks before publication.
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