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
sim_camera: struct<name: string, pos: list<item: double>, R_world_from_cv: list<item: list<item: double>>, fovy_ (... 12 chars omitted)
child 0, name: string
child 1, pos: list<item: double>
child 0, item: double
child 2, R_world_from_cv: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 3, fovy_deg: double
sim_cup_xy: list<item: double>
child 0, item: double
sim_plate_xy: list<item: double>
child 0, item: double
sim_grasp_point: list<item: double>
child 0, item: double
plate_minus_cup_cm: list<item: double>
child 0, item: double
max_reach_m: double
min_target_height_above_table_m: double
camera_matrix: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
image_size: list<item: int64>
child 0, item: int64
instruction: string
duration_s: double
fps: int64
depth_scale: double
dropped_frames: int64
frames: int64
dist_coeffs: list<item: double>
child 0, item: double
to
{'instruction': Value('string'), 'fps': Value('int64'), 'frames': Value('int64'), 'dropped_frames': Value('int64'), 'duration_s': Value('float64'), 'image_size': List(Value('int64')), 'camera_matrix': List(List(Value('float64'))), 'dist_coeffs': List(Value('float64')), 'depth_scale': Value('float64')}
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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
sim_camera: struct<name: string, pos: list<item: double>, R_world_from_cv: list<item: list<item: double>>, fovy_ (... 12 chars omitted)
child 0, name: string
child 1, pos: list<item: double>
child 0, item: double
child 2, R_world_from_cv: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
child 3, fovy_deg: double
sim_cup_xy: list<item: double>
child 0, item: double
sim_plate_xy: list<item: double>
child 0, item: double
sim_grasp_point: list<item: double>
child 0, item: double
plate_minus_cup_cm: list<item: double>
child 0, item: double
max_reach_m: double
min_target_height_above_table_m: double
camera_matrix: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
image_size: list<item: int64>
child 0, item: int64
instruction: string
duration_s: double
fps: int64
depth_scale: double
dropped_frames: int64
frames: int64
dist_coeffs: list<item: double>
child 0, item: double
to
{'instruction': Value('string'), 'fps': Value('int64'), 'frames': Value('int64'), 'dropped_frames': Value('int64'), 'duration_s': Value('float64'), 'image_size': List(Value('int64')), 'camera_matrix': List(List(Value('float64'))), 'dist_coeffs': List(Value('float64')), 'depth_scale': Value('float64')}
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.
HChallenge: mug pick-and-place recordings
165 recordings of my hand picking up a mug and putting it on a plate, with the mug and plate moved to a new random position by hand before each one. Recorded with an Intel RealSense D405 (1280 × 720 colour + aligned depth, 30 fps) looking at a table with an ArUco marker that defines the table frame.
Code, processing pipeline and results: https://github.com/mi-robotics/HChallenge · https://mi-robotics.github.io/HChallenge/
mug_pnp_dataset/<YYYYmmdd_HHMMSS>/ 100 episodes whose sim replay succeeds (train / val / test)
mug_pnp_failed/<YYYYmmdd_HHMMSS>/ 65 episodes whose sim replay fails
raw recording
color.mp4 colour video, 30 fps
depth.mkv depth aligned to colour, lossless uint16 (FFV1); metres = value × depth_scale
frames.csv per frame: index, camera frame number, timestamp (ms)
meta.json camera intrinsics, depth_scale, frame counts
processed (scripts/preprocess_data.sh; kept episodes and the 46 replayed failed ones)
sim.npz the robot's replay per 20 Hz step: actions, state, wrist and third-person camera images
flow_sim.npz hand and mug action flow on the robot's clock
video_sim.mp4 the real video on the robot's clock (one frame per sim step)
scene.json the matching sim scene
The train / val / test / failed lists are data/splits.json in the GitHub repository.
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