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
aligned_frame_ids: list<item: int64>
child 0, item: int64
aligned_timeline_length: int64
coordinate_frame: string
created_at: timestamp[s]
episode: int64
gripper_poses_sha256: string
num_grippers: int64
object: string
opening_m: struct<clamp_range: list<item: double>, clamped_frames: int64, clamped_values: int64, max: double, m (... 11 chars omitted)
child 0, clamp_range: list<item: double>
child 0, item: double
child 1, clamped_frames: int64
child 2, clamped_values: int64
child 3, max: double
child 4, min: double
pose_convention: string
robot: struct<bimanual: bool, integrity: struct<local_sha256: string, path: string, reason: string, remote_ (... 70 chars omitted)
child 0, bimanual: bool
child 1, integrity: struct<local_sha256: string, path: string, reason: string, remote_hash_kind: string, verified: bool>
child 0, local_sha256: string
child 1, path: string
child 2, reason: string
child 3, remote_hash_kind: string
child 4, verified: bool
child 2, loaded_with: string
child 3, path: string
families: list<item: struct<facts: struct<camera_names: list<item: string>, code_head: string, gripper_poses: (... 1628 chars omitted)
child 0, item: struct<facts: struct<camera_names: list<item: string>, code_head: string, gripper_poses: struct<alig (... 1616 chars omitted)
child 0, facts: struct<camera_names: list<item: string>, code_head: string, gripper_poses: struct<aligned_timeline_l (... 1528 chars omitted)
ch
...
ated: struct<>, path_in_repo: string>
child 0, dated: struct<>
child 1, path_in_repo: string
child 1, label: string
child 2, note: string
object_id: string
native_files: list<item: struct<path: string, roles: list<item: string>, sha256: string, size_bytes: int64>>
child 0, item: struct<path: string, roles: list<item: string>, sha256: string, size_bytes: int64>
child 0, path: string
child 1, roles: list<item: string>
child 0, item: string
child 2, sha256: string
child 3, size_bytes: int64
acknowledged_record_mismatches: list<item: null>
child 0, item: null
materialized_files: list<item: null>
child 0, item: null
time: null
unknowns: list<item: null>
child 0, item: null
repo_id: string
episode_id: string
gaps: list<item: null>
child 0, item: null
existing_recording_references: list<item: null>
child 0, item: null
disclosed_exceptions: list<item: null>
child 0, item: null
schema: string
notes: list<item: string>
child 0, item: string
window_id: null
dependencies: list<item: null>
child 0, item: null
license: struct<id: string, scope: string>
child 0, id: string
child 1, scope: string
aliases: list<item: null>
child 0, item: null
description: string
variant_id: string
relocation: struct<path_in_repo: string, recorded_root: string, resolved_root: string, rule: string>
child 0, path_in_repo: string
child 1, recorded_root: string
child 2, resolved_root: string
child 3, rule: string
kind: string
to
{'acknowledged_record_mismatches': List(Value('null')), 'aliases': List(Value('null')), 'dependencies': List(Value('null')), 'description': Value('string'), 'disclosed_exceptions': List(Value('null')), 'episode_id': Value('string'), 'existing_recording_references': List(Value('null')), 'families': List({'facts': {'camera_names': List(Value('string')), 'code_head': Value('string'), 'gripper_poses': {'aligned_timeline_length': Value('int64'), 'coordinate_frame': Value('string'), 'episode': Value('int64'), 'gripper_poses_sha256': Value('string'), 'num_grippers': Value('int64'), 'object': Value('string'), 'opening_m': {'clamp_range': List(Value('float64')), 'clamped_frames': Value('int64'), 'clamped_values': Value('int64'), 'max': Value('float64'), 'min': Value('float64')}, 'pose_convention': Value('string'), 'robot': {'bimanual': Value('bool'), 'integrity': {'local_sha256': Value('string'), 'path': Value('string'), 'reason': Value('string'), 'remote_hash_kind': Value('string'), 'verified': Value('bool')}, 'loaded_with': Value('string'), 'path': Value('string')}}, 'image_size_wh': List(Value('int64')), 'manifest': Value('string'), 'masks': {'H': Value('string'), 'encoding': Value('string'), 'rasterization': Value('string'), 'urdf': {'path': Value('string'), 'sha256': Value('string')}, 'visual_mesh_sha256': {'finger.stl': Value('string'), 'holder_left.stl': Value('string'), 'holder_right.stl': Value('string'), 'umi_gripper_base.stl': Value('string')}}, 'not_consumed_review_media':
...
lue('string'), 'accepted_scope': Value('string'), 'hc1_basis': {'dp1_observation_review': Value('string'), 'dp1_occ': Value('string'), 'independent_dp1_occ_audit': Value('string')}, 'owner_acceptance_line': Value('string'), 'pose_export_sha256': Value('string')}, 'source_bundle_manifest_sha256': Value('string'), 'time': {'aligned_frames_half_open': List(Value('int64')), 'contiguous': Value('bool'), 'domain': Value('string'), 'frame_count': Value('int64')}}, 'family': Value('string'), 'notes': List(Value('null')), 'reader': Value('string'), 'status': Value('string')}), 'gaps': List(Value('null')), 'kind': Value('string'), 'license': {'id': Value('string'), 'scope': Value('string')}, 'materialized_files': List(Value('null')), 'native_files': List({'path': Value('string'), 'roles': List(Value('string')), 'sha256': Value('string'), 'size_bytes': Value('int64')}), 'not_selected': List({'bytes': Value('int64'), 'files': Value('int64'), 'path': Value('string'), 'reason': Value('string')}), 'notes': List(Value('string')), 'object_id': Value('string'), 'relocation': {'path_in_repo': Value('string'), 'recorded_root': Value('string'), 'resolved_root': Value('string'), 'rule': Value('string')}, 'repo_id': Value('string'), 'schema': Value('string'), 'status': {'evidence': List({'dated': {}, 'path_in_repo': Value('string')}), 'label': Value('string'), 'note': Value('string')}, 'time': Value('null'), 'unknowns': List(Value('null')), 'variant_id': Value('string'), 'window_id': Value('null')}
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
aligned_frame_ids: list<item: int64>
child 0, item: int64
aligned_timeline_length: int64
coordinate_frame: string
created_at: timestamp[s]
episode: int64
gripper_poses_sha256: string
num_grippers: int64
object: string
opening_m: struct<clamp_range: list<item: double>, clamped_frames: int64, clamped_values: int64, max: double, m (... 11 chars omitted)
child 0, clamp_range: list<item: double>
child 0, item: double
child 1, clamped_frames: int64
child 2, clamped_values: int64
child 3, max: double
child 4, min: double
pose_convention: string
robot: struct<bimanual: bool, integrity: struct<local_sha256: string, path: string, reason: string, remote_ (... 70 chars omitted)
child 0, bimanual: bool
child 1, integrity: struct<local_sha256: string, path: string, reason: string, remote_hash_kind: string, verified: bool>
child 0, local_sha256: string
child 1, path: string
child 2, reason: string
child 3, remote_hash_kind: string
child 4, verified: bool
child 2, loaded_with: string
child 3, path: string
families: list<item: struct<facts: struct<camera_names: list<item: string>, code_head: string, gripper_poses: (... 1628 chars omitted)
child 0, item: struct<facts: struct<camera_names: list<item: string>, code_head: string, gripper_poses: struct<alig (... 1616 chars omitted)
child 0, facts: struct<camera_names: list<item: string>, code_head: string, gripper_poses: struct<aligned_timeline_l (... 1528 chars omitted)
ch
...
ated: struct<>, path_in_repo: string>
child 0, dated: struct<>
child 1, path_in_repo: string
child 1, label: string
child 2, note: string
object_id: string
native_files: list<item: struct<path: string, roles: list<item: string>, sha256: string, size_bytes: int64>>
child 0, item: struct<path: string, roles: list<item: string>, sha256: string, size_bytes: int64>
child 0, path: string
child 1, roles: list<item: string>
child 0, item: string
child 2, sha256: string
child 3, size_bytes: int64
acknowledged_record_mismatches: list<item: null>
child 0, item: null
materialized_files: list<item: null>
child 0, item: null
time: null
unknowns: list<item: null>
child 0, item: null
repo_id: string
episode_id: string
gaps: list<item: null>
child 0, item: null
existing_recording_references: list<item: null>
child 0, item: null
disclosed_exceptions: list<item: null>
child 0, item: null
schema: string
notes: list<item: string>
child 0, item: string
window_id: null
dependencies: list<item: null>
child 0, item: null
license: struct<id: string, scope: string>
child 0, id: string
child 1, scope: string
aliases: list<item: null>
child 0, item: null
description: string
variant_id: string
relocation: struct<path_in_repo: string, recorded_root: string, resolved_root: string, rule: string>
child 0, path_in_repo: string
child 1, recorded_root: string
child 2, resolved_root: string
child 3, rule: string
kind: string
to
{'acknowledged_record_mismatches': List(Value('null')), 'aliases': List(Value('null')), 'dependencies': List(Value('null')), 'description': Value('string'), 'disclosed_exceptions': List(Value('null')), 'episode_id': Value('string'), 'existing_recording_references': List(Value('null')), 'families': List({'facts': {'camera_names': List(Value('string')), 'code_head': Value('string'), 'gripper_poses': {'aligned_timeline_length': Value('int64'), 'coordinate_frame': Value('string'), 'episode': Value('int64'), 'gripper_poses_sha256': Value('string'), 'num_grippers': Value('int64'), 'object': Value('string'), 'opening_m': {'clamp_range': List(Value('float64')), 'clamped_frames': Value('int64'), 'clamped_values': Value('int64'), 'max': Value('float64'), 'min': Value('float64')}, 'pose_convention': Value('string'), 'robot': {'bimanual': Value('bool'), 'integrity': {'local_sha256': Value('string'), 'path': Value('string'), 'reason': Value('string'), 'remote_hash_kind': Value('string'), 'verified': Value('bool')}, 'loaded_with': Value('string'), 'path': Value('string')}}, 'image_size_wh': List(Value('int64')), 'manifest': Value('string'), 'masks': {'H': Value('string'), 'encoding': Value('string'), 'rasterization': Value('string'), 'urdf': {'path': Value('string'), 'sha256': Value('string')}, 'visual_mesh_sha256': {'finger.stl': Value('string'), 'holder_left.stl': Value('string'), 'holder_right.stl': Value('string'), 'umi_gripper_base.stl': Value('string')}}, 'not_consumed_review_media':
...
lue('string'), 'accepted_scope': Value('string'), 'hc1_basis': {'dp1_observation_review': Value('string'), 'dp1_occ': Value('string'), 'independent_dp1_occ_audit': Value('string')}, 'owner_acceptance_line': Value('string'), 'pose_export_sha256': Value('string')}, 'source_bundle_manifest_sha256': Value('string'), 'time': {'aligned_frames_half_open': List(Value('int64')), 'contiguous': Value('bool'), 'domain': Value('string'), 'frame_count': Value('int64')}}, 'family': Value('string'), 'notes': List(Value('null')), 'reader': Value('string'), 'status': Value('string')}), 'gaps': List(Value('null')), 'kind': Value('string'), 'license': {'id': Value('string'), 'scope': Value('string')}, 'materialized_files': List(Value('null')), 'native_files': List({'path': Value('string'), 'roles': List(Value('string')), 'sha256': Value('string'), 'size_bytes': Value('int64')}), 'not_selected': List({'bytes': Value('int64'), 'files': Value('int64'), 'path': Value('string'), 'reason': Value('string')}), 'notes': List(Value('string')), 'object_id': Value('string'), 'relocation': {'path_in_repo': Value('string'), 'recorded_root': Value('string'), 'resolved_root': Value('string'), 'rule': Value('string')}, 'repo_id': Value('string'), 'schema': Value('string'), 'status': {'evidence': List({'dated': {}, 'path_in_repo': Value('string')}), 'label': Value('string'), 'note': Value('string')}, 'time': Value('null'), 'unknowns': List(Value('null')), 'variant_id': Value('string'), 'window_id': Value('null')}
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.
DAIRLab Deform360 PhysTwin preprocessing
DAIRLab's own preprocessing of selected Deform360 episodes, used by the fitted models in DAIRLab/deform360_phystwin_models: per-camera gripper occluder masks with their review sign-off, and the gripper poses they were rasterized from. Folders mirror the upstream processed/<object>/<episode>/ layout. The authors' RGB, depth, masks, tracks and splats are not copied here; the models' dependencies.json points to them at a pinned revision.
Upstream data (not mirrored here)
- brownu/deform360 at
5ea8c5d3fc7b4a7b4f9f921f2ceb1de24610f6a4: raw Deform360 release (declares MIT) - brownu/deform360_processed at
e92deaf7e437e7e51ad464706ae647f522a279d9: processed Deform360 release (no license declaration at this revision)
License
The MIT license in LICENSE (Copyright (c) 2026 DAIRLab) covers the files of this repository, which
are DAIRLab's own preprocessing products. It does not cover the upstream data above, which keep their own
terms and attribution.
The owner interprets the processed Deform360 assets as covered by the raw release's MIT terms because they share project and authors (plan decision D12). That is DAIRLab's interpretation, not a declaration by brownu/deform360_processed. Please cite and attribute Deform360 when you use these files.
PhysTwin annotation and preprocessing packages
Each package is processed/<object>/<episode>/preprocessing/<variant_id>/, mirroring
the upstream Deform360 episode folders. It keeps its original files under native/
and has a sidecar (artifact.json) with the file inventory and sha256 digests, the
upstream episode, cameras and aligned-frame span, review status, known gaps and
license. The upstream RGB, depth, masks, tracks and splats are not copied here.
Files whose exact bytes are already published (at another path here, or
upstream) are not uploaded again: a sidecar's materialized_files lists each
such native path with its sha256 and origin, and
scripts/phystwin_publish.py fetch recreates it there and checks the digest.
License scope of these packages
Each row's license applies only to the files inside that package directory. It does not license the upstream Deform360 data the packages were derived from or refer to. Notices recorded in a package sidecar for third-party inputs still apply.
| Package directory | Kind | Status | License | Scope |
|---|---|---|---|---|
processed/001-rope/episode_0/preprocessing/gripper-occluders-aligned0092-0188-dp1-20260926/ |
preprocessing | accepted | MIT | DAIRLab-produced gripper occluder masks, gripper poses, sign-off and records in this directory only (D9). They derive from the upstream Deform360 robot state and UMI gripper meshes, which keep their own terms (D12 is the owner's interpretation for processed Deform360 assets, not an upstream declaration). |
processed/001-rope/episode_2/preprocessing/gripper-occluders-aligned0064-0230-u08b-d1-20261014/ |
preprocessing | accepted | MIT | DAIRLab-produced gripper occluder masks, gripper poses, sign-off and records in this directory only (D9). They derive from the upstream Deform360 robot state and UMI gripper meshes, which keep their own terms (D12 is the owner's interpretation for processed Deform360 assets, not an upstream declaration). |
processed/090-sloth/episode_0/preprocessing/gripper-occluders-aligned0050-0218-u08b-d2-20261014/ |
preprocessing | accepted | MIT | DAIRLab-produced gripper occluder masks, gripper poses, sign-off and records in this directory only (D9). They derive from the upstream Deform360 robot state and UMI gripper meshes, which keep their own terms (D12 is the owner's interpretation for processed Deform360 assets, not an upstream declaration). |
processed/090-sloth/episode_3/preprocessing/gripper-occluders-aligned0045-0204-u08b-d4-20261023/ |
preprocessing | accepted_with_disclosed_exceptions | MIT | DAIRLab-produced gripper occluder masks, gripper poses, sign-off and records in this directory only (D9). They derive from the upstream Deform360 robot state and UMI gripper meshes, which keep their own terms (D12 is the owner's interpretation for processed Deform360 assets, not an upstream declaration). |
The MIT terms for the rows marked MIT:
MIT License
Copyright (c) 2026 DAIRLab
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
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