Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Real2Sim Agent · robot-twin datasets
Robot-twin data made from one egocentric human video per task: the human motion is replayed object-centrically on a dual
7-DoF arm robot with two 22-DoF dexterous hands and a stereo camera in Isaac Sim, under randomized placements and physics.
These are the datasets the policies on the Real2Sim Agent page were
finetuned on (strict successes of the valid episodes); failures and invalid episodes (flagged invalid with an
invalid_reason, e.g. a failed render-look gate) are kept so the data can be re-filtered.
| Folder | Dataset | Episodes | Strict successes | Size |
|---|---|---|---|---|
serve_bread/v1/ |
Serve bread · twin data v1 | 500 (0 invalid) | 312 | 1.28 GB |
serve_bread/v2/ |
Serve bread · twin data v2 (photoreal, diverse) | 640 (3 invalid) | 352 | 2.11 GB |
water_flowers/data4/ |
Water flowers · twin data | 500 (0 invalid) | 448 | 0.45 GB |
water_flowers/v3/ |
Water flowers · twin data v3 (realistic fixtures) | 500 (0 invalid) | 450 | 0.45 GB |
Files
Each episode <task>/<version>/<job>/<stem> has three files:
<stem>.json: the runner's result: strict / loose success, stage flags, timings, controller and physics settings, the initial placement (init.knobs), force and safety summaries.<stem>_viz.npz: the recording (r2s.viz.v1), one row per 1/30 s: joint anglesq(order injoint_names), end-effector and object poses (xyz + wxyz quaternion, world = robot base, z up, metres), fingertips, the camera intrinsicszed_Kand extrinsicszed_c2w, the policy-call rows and predicted wrist paths when a policy drove it, andmeta_json.<stem>_obs.mp4: the policy-input video: the robot camera view with the robot replaced by a rendered human hand.
index.json lists every episode with its outcome fields and files.
import json, numpy as np
ep = "serve_bread/v1/r2s-one002-data-1/serve_bread_002_s0_g00"
meta = json.load(open(ep + ".json"))
rec = np.load(ep + "_viz.npz")
print(meta["success_strict"], rec["q"].shape, json.loads(str(rec["meta_json"]))["spec"])
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