The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label PWM-ArtGen-test@f26f05b7c6ae60c7ed158ab5f48e80527096fc63
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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2386, 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 2303, 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 2178, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1460, 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 1483, 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 1158, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1095, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1116, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label PWM-ArtGen-test@f26f05b7c6ae60c7ed158ab5f48e80527096fc63Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PWM-ArtGen-test
Test inputs for PWM-ArtGen: Part World Model for Articulated Object Generation. Model weights: Wentap/PWM-ArtGen.
| Archive | Extracted directory | Objects | Views |
|---|---|---|---|
pwm_pm_test.zip |
pm/ |
77 | 154 |
pwm_acd_test.zip |
acd/ |
135 | 270 |
Each object has two inputs, view_0 and view_1, with RGB images, part masks,
bounding boxes, and a GT part graph. views.json contains the sample records
used by the inference loader. Each archive includes test_ids.json,
dataset.json, and per-file checksums in checksums.json.
Meshes and the retrieval library are downloaded separately.
Download
hf download Wentap/PWM-ArtGen-test pwm_pm_test.zip pwm_acd_test.zip SHA256SUMS \
--repo-type dataset --local-dir downloads
(cd downloads && sha256sum -c SHA256SUMS)
mkdir -p data/benchmarks
unzip downloads/pwm_pm_test.zip -d data/benchmarks
unzip downloads/pwm_acd_test.zip -d data/benchmarks
Use the extracted directories with the inference and evaluation commands in the
code repository. The inference loader
reads each dataset's included test_ids.json.
Data sources
The original datasets are PartNet-Mobility and ACD/S2O. The annotation and mesh packages used for retrieval and evaluation are provided by SINGAPO: PM package and ACD test package. These mesh packages are separate from the prepared image inputs in this repository. Original dataset terms apply.
Both test sets retrieve from the processed PM library. Evaluation uses PM ground truth for PM and ACD ground truth for ACD. These test inputs provide GT part structure; single-image inference uses its own segmentation and graph preparation. The reference PM retrieval library includes 75 PM test objects.
Citation
@inproceedings{zheng2026pwm,
title={PWM-ArtGen: Part World Model for Articulated Object Generation},
author={Zheng, Wentao and Wu, Ancong},
booktitle={European Conference on Computer Vision},
pages={251--267},
year={2026},
organization={Springer}
}
- Downloads last month
- 46