Error code:   ConfigNamesError
Exception:    TypeError
Message:      List.__init__() got an unexpected keyword argument 'description'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
                  ).get_module()
                    ^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 605, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 386, in from_dataset_card_data
                  dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2031, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1876, in from_dict
                  obj = generate_from_dict(dic)
                        ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1463, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                               ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1476, in generate_from_dict
                  return List(generate_from_dict(feature), **obj)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              TypeError: List.__init__() got an unexpected keyword argument 'description'

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.

FastUMI Pro – Multimodal Sample Dataset

Small-Scale Demonstration Data from the FastUMI Pro Multimodal Sensing System
(Only Dozens of Trajectories — Full Dataset Available Upon Request)

Project Homepage

📖 Overview

The FastUMI Pro Sample Dataset provides a public preview of the multimodal sensing capabilities of the FastUMI Pro data collection system.

This release contains only dozens of sample trajectories and is intended for:

System testing
Robotics and AI pipeline integration
Preliminary algorithm development
Demonstrating multimodal alignment and synchronization

Included sensor streams:

RGB camera images
Visual SLAM trajectory
Vive tracking trajectory
ToF point cloud frames
Clamp (gripper width) sensor readings
Fused multi-sensor trajectory

Full-scale datasets are available upon request for research or enterprise collaboration.

📊 Data Specifications

Data Type	Path	Shape	Type	Description
RGB Images	RGB_Images/Frames/*.jpg	(H, W, 3)	uint8	Multi-view RGB images
SLAM Poses	SLAM_Poses/slam_raw.txt	(N, 8)	float	Timestamp + SE(3) pose
Vive Poses	Vive_Poses/vive_data_tum.txt	(N, 8)	float	Vive tracking system poses
ToF PointClouds	ToF_PointClouds/PointClouds/*.pcd	variable	pcd	Time-of-Flight point clouds
Clamp Data	Clamp_Data/clamp_data_tum.txt	(N, 2)	float	Timestamp + clamp width
Merged Trajectory	Merged_Trajectory/merged_trajectory.txt	(N, 8)	float	Fused multi-sensor pose

🧭 Pose Data Format

All pose data (SLAM, Vive, fused) follow the same structure:

timestamp  x  y  z  qx  qy  qz  qw

Field	Description
timestamp	Unix timestamp
x	Position X (meters)
y	Position Y (meters)
z	Position Z (meters)
qx	Quaternion X component
qy	Quaternion Y component
qz	Quaternion Z component
qw	Quaternion W component

📥 Download

huggingface-cli download FastUMIPro/example_data_fastumi_pro_raw \
  --repo-type dataset \
  --local-dir ./fastumi_sample/

Optional:

export HF_ENDPOINT=https://hf-mirror.com

⚠️ Dataset Scale Notice

This dataset contains only a small number of sample episodes
and is not intended for large-scale training.

For full multimodal datasets or enterprise collaborations, please contact the FastUMI team.

📞 Contact

Lead: Ding Yan
Email: [email protected]
WeChat: Duke_dingyan

Downloads last month: 97