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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'display', 'dishwasher'}) and 4 missing columns ({'keyboard', 'clock', 'trashcan', 'faucet'}).
This happened while the json dataset builder was generating data using
hf://datasets/Weizm/AffordSplat/UnSeen_test.json (at revision 6bc6c766b079d0d779fa43cb8fcfd9a882e08422)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 623, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
bed: list<item: string>
child 0, item: string
dishwasher: list<item: string>
child 0, item: string
knife: list<item: string>
child 0, item: string
bottle: list<item: string>
child 0, item: string
chair: list<item: string>
child 0, item: string
bag: list<item: string>
child 0, item: string
laptop: list<item: string>
child 0, item: string
table: list<item: string>
child 0, item: string
earphone: list<item: string>
child 0, item: string
storagefurniture: list<item: string>
child 0, item: string
hat: list<item: string>
child 0, item: string
microwave: list<item: string>
child 0, item: string
mug: list<item: string>
child 0, item: string
bowl: list<item: string>
child 0, item: string
vase: list<item: string>
child 0, item: string
door: list<item: string>
child 0, item: string
display: list<item: string>
child 0, item: string
to
{'trashcan': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'clock': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'keyboard': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'bed': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'knife': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'bottle': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'chair': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'bag': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'laptop': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'table': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'faucet': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'earphone': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'storagefurniture': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'hat': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'microwave': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'mug': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'bowl': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'vase': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'door': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1433, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 989, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'display', 'dishwasher'}) and 4 missing columns ({'keyboard', 'clock', 'trashcan', 'faucet'}).
This happened while the json dataset builder was generating data using
hf://datasets/Weizm/AffordSplat/UnSeen_test.json (at revision 6bc6c766b079d0d779fa43cb8fcfd9a882e08422)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
trashcan
sequence | clock
sequence | keyboard
sequence | bed
sequence | knife
sequence | bottle
sequence | chair
sequence | bag
sequence | laptop
sequence | table
sequence | faucet
sequence | earphone
sequence | storagefurniture
sequence | hat
sequence | microwave
sequence | mug
sequence | bowl
sequence | vase
sequence | door
sequence |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[
"pour",
"contain",
"open"
] | [
"display"
] | [
"press"
] | [
"lay",
"support"
] | [
"stab",
"grasp"
] | [
"contain",
"open",
"grasp",
"wrap_grasp"
] | [
"move",
"sit"
] | [
"contain",
"open",
"grasp"
] | [
"display"
] | [
"support"
] | [
"open",
"grasp"
] | [
"listen"
] | [
"open"
] | [
"grasp"
] | [
"contain"
] | [
"pour",
"contain",
"wrap_grasp"
] | [
"pour",
"contain"
] | [
"contain",
"wrap_grasp"
] | [
"pull",
"open"
] |
In this repository, we present 3DAffordSplat, the first large-scale, multi-modal dataset tailored for 3DGS-based affordance reasoning. This dataset includes 23k Gaussian instances, 8k point cloud instances, and 6k manually annotated affordance labels, encompassing 21 object categories and 18 affordance types.
Dataset Structure
After downloading, the data structure should be as follows:
—Seen
├── train
│ ├── bag
│ │ ├── Gaussian
│ │ │ └── GS_0017.ply
│ │ │ ......
│ │ ├── PointCloud
│ │ │ └── PC_0001.ply
│ │ │ ......
│ │ ├── contain
│ │ │ ├── GS_anno_0017.ply
│ │ │ ├── PC_anno_0001.json
│ │ │ ......
│ │ └── grasp
│ │ ......
│ └── bed
│ ......
│
├── val
│ ├── bag
│ │ ├── Gaussian
│ │ │ └── GS_0009.ply
│ │ │ ......
│ │ ├── contain
│ │ │ └── GS_anno_0009.ply
│ │ │ ......
│ │ └── grasp
│ │ ......
│ └── bed
│ ......
│
└── test
├── bag
│ ├── Gaussian
│ │ └── GS_0001.ply
│ │ ......
│ ├── contain
│ │ └── GS_anno_0001.ply
│ │ ......
│ └── grasp
│ ......
└── bed
......
—Affordance-Question.csv
—obj_aff_structure.json
—UnSeen_test.json
—UnSeen_train.json
Dataset Details
For more information on detailed statistics and the methodology of AffordSplat, please refer to the following resources:
- Repository: Github Repository
- Paper: 3DAffordSplat: Efficient Affordance Reasoning with 3D Gaussians
Additionally, we sincerely thank Guantian Liu, Yao Xiao, Xinyu Li, Kecheng Liang and Yipeng Ouyang for their contributions.
Contact
This project is for research purpose only, please contact us for the licence of commercial use. For any other questions please contact ([email protected], [email protected] or [email protected]).
Citation
If you use this data, please cite our paper.
@misc{wei20253daffordsplatefficientaffordancereasoning,
title={3DAffordSplat: Efficient Affordance Reasoning with 3D Gaussians},
author={Zeming wei and Junyi Lin and Yang Liu and Weixing Chen and Jingzhou Luo and Guanbin Li and Liang Lin},
year={2025},
eprint={2504.11218},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2504.11218},
}
Acknowledgement
The construction of AffordSplat dataset is based on 3DAffordanceNet, LASO and ShapeSplat. We sincerely thank them for their contributions to the community.
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