Gelsight
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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: ValueError
Message: Invalid string class label muxGel@69c549b46bd7cdca882c7a323685623d200298c0
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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2368, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2285, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label muxGel@69c549b46bd7cdca882c7a323685623d200298c0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MuxGel: Simultaneous Dual-Modal Visuo-Tactile Sensing via Spatially Multiplexing and Deep Reconstruction
Project Website | Paper | GitHub Code
MuxGel is a novel plug-and-play visuo-tactile gel-pad design that spatially multiplexes visual and tactile sensing, enabling the simultaneous recovery of vision and tactile signals for robotic manipulation.
Dataset Structure
This repository hosts the background scenes, object patches, and calibration data needed to train and test the MuxGel framework:
- Scene Backgrounds (
indoorCVPRBlur_320_240.tar.xz): Processed using a disk defocus blur, originally from the CVPR 2009 Indoor Scene dataset. - Object Patches (
mujoco_patch_output_320_240.tar.xz): Pre-processed simulation object patches generated using MuJoCo. - Real-World Calibration (
calibration_data.zip): Assets required for real-world calibration and training.
For detailed instructions on how to set up the environment and run training or testing, please refer to the GitHub Repository.
Citation
If you find this work or dataset helpful, please cite the paper:
@article{hu2026muxgel,
title={MuxGel: Simultaneous Dual-Modal Visuo-Tactile Sensing via Spatially Multiplexing and Deep Reconstruction},
author={Hu, Zhixian and Xu, Zhengtong and Athar, Sheeraz and Wachs, Juan and She, Yu},
journal={arXiv preprint arXiv:2603.09761},
year={2026}
}
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