The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: Mismatching child array lengths
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/hdf5/hdf5.py", line 83, in _generate_tables
pa_table = _recursive_load_arrays(h5, self.info.features, start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 267, in _recursive_load_arrays
arr = _recursive_load_arrays(obj, features[path], start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 267, in _recursive_load_arrays
arr = _recursive_load_arrays(obj, features[path], start, end)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 267, in _recursive_load_arrays
arr = _recursive_load_arrays(obj, features[path], start, end)
[Previous line repeated 1 more time]
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 288, in _recursive_load_arrays
sarr = pa.StructArray.from_arrays(values, names=keys)
File "pyarrow/array.pxi", line 4385, in pyarrow.lib.StructArray.from_arrays
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Mismatching child array lengthsNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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已完成：50条成功轨迹，45训练/5验证，10,550个同步时刻，21,100张RGB图像；50个文件全部检查通过。315个候选均留档。
Piper 黄色瓶子放白色杯垫：50条采集
状态以 episodes.json 和 validation.json 为准，采集过程中不要将部分文件视为整批完成。
数据与语义
train/run_*.hdf5、val/run_*.hdf5；每个文件 data/demo_0。6轴关节，不填补第7轴。
- actions [T,7]：六轴绝对目标 rad + 连续夹爪开口目标 m（joint7-joint8）。夹爪不是0/1。
- obs/proprio_obs/arm_joint_pos、arm_joint_vel [T,6]：rad、rad/s。
- gripper_pos、gripper_vel [T,1]：实际开口及开口速度，m、m/s。
- finger_joint_pos/vel [T,2]：两指原始滑动坐标及速度。
- obs/image_obs/over_shoulder_left_camera、wrist_cam：RGB uint8 [T,480,640,3]。前者映射camera2_fixed，后者camera1_wrist；固定顺序。
- timestamps [T]：秒，20 Hz。每条10.55秒，采样211帧；15步action窗口可生成197个样本。
- camera_calibration：MuJoCo原始intrinsic（传感器单位）、sensorsize、resolution，逐帧camera_to_world。相机坐标OpenGL右/上/-z前。不是未注明约定的OpenCV矩阵。
- instruction 属性：Pick up the yellow bottle and place it on the white coaster.
记录的是积分前观测状态和随后施加的控制目标，渲染由同一状态产生。每段控制五次平滑插值，六轴重力偏置补偿；不对瓶子加外力或附着。
随机化
每条同时随机瓶子xy ±3cm、杯垫xy ±3cm、预抓初始TCP xy ±4cm和高于抓位4–8cm、灯光强度±10%。维持机器人底座和相机实测标定。各物体显示网格与碰撞体同步平移。动作按新目标重新IK，未通过可达性直接留档；成功分布是可达且通过判据的条件分布，不保证填满整个采样长方体。
复现与完整性
attempts// 保留每个候选参数、scene.xml、result.json；已运行物理的候选另存1kHz raw.npz（qpos/qvel/control/phase/contact_metrics）。失败不进入成功HDF5。 读取 episodes.json 找到成功轨迹来源；按轨迹45训练/5验证，分位数仅从训练集统计。training_config.yaml 的模型/loader参数名称需按实际仓库适配；维度改为7，增加速度字段不会自动将速度拼进state。
采集沿用用户接受的简化圆柱瓶子碰撞和现有接触模型；未补全所有自碰撞、背景碰撞、真实瓶颈接触辨识。success为当前模型中的任务判据，通过不等于真机验证。仅渲染MuJoCo双相机训练RGB，无新增真实配对图或Blender增强工程。
入口 collect.py（断点跳过已记录候选），finalize.py（逐图解码/维度/时间检查和训练分位数）。引用的网格/纹理位于原工作区，迁移需同时保留资产。采集运行时为 act_conv3 Python，MUJOCO_GL=egl。
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