The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<diameter: double, min_x: double, min_y: double, min_z: double, size_x: double, size_y: double, size_z: double, symmetries_discrete: list<item: list<item: double>>, symmetries_continuous: list<item: struct<axis: list<item: double>, offset: list<item: double>>>>
to
{'diameter': Value('float64'), 'min_x': Value('float64'), 'min_y': Value('float64'), 'min_z': Value('float64'), 'size_x': Value('float64'), 'size_y': Value('float64'), 'size_z': Value('float64'), 'symmetries_discrete': List(List(Value('float64')))}
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/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<diameter: double, min_x: double, min_y: double, min_z: double, size_x: double, size_y: double, size_z: double, symmetries_discrete: list<item: list<item: double>>, symmetries_continuous: list<item: struct<axis: list<item: double>, offset: list<item: double>>>>
to
{'diameter': Value('float64'), 'min_x': Value('float64'), 'min_y': Value('float64'), 'min_z': Value('float64'), 'size_x': Value('float64'), 'size_y': Value('float64'), 'size_z': Value('float64'), 'symmetries_discrete': List(List(Value('float64')))}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.
license: mit
the project's GitHub repository: https://github.com/WangYuLin-SEU/KASAL
Google Scanned Objects (GSO) Symmetry Axis Dataset
1. Dataset Description
This dataset is an extension of the Google Scanned Objects (GSO) dataset, enriched with symmetry axis annotations for each object. It is designed to assist in pose estimation tasks by providing explicit symmetry information for objects with both geometric and texture symmetries.
Key Features:
Objects: 3D scanned models of various objects from the GSO dataset.
Symmetry Annotations: Each object is annotated with one or more symmetry axes (if applicable), covering discrete, continuous, texture, and geometric symmetries.
Applications: Useful for tasks like pose estimation, object detection, and symmetry-aware 3D model analysis.
If you only need to download the rotation centers, rotational symmetry axes, and the list of rotational symmetry transformations for all objects, we provide a separate JSON file: https://huggingface.co/datasets/SEU-WYL/GSO-SAD/blob/main/gso.json
2. Data Source
This dataset is derived from the publicly available Google Scanned Objects (GSO) dataset. We added symmetry axis annotations based on the geometric and texture properties of the objects.
The GSO dataset can be accessed here: https://www.paris.inria.fr/archive_ylabbeprojectsdata/megapose/tars/google_scanned_objects.zip
3. Dataset Structure
The dataset is organized as follows:
Models: 3D object models from the GSO dataset.
Symmetry Axes: A JSON file for each object containing symmetry axis data, including discrete, and continuous symmetry information.
The JSON file is organized based on the BOP format: https://github.com/thodan/bop_toolkit
4. Project Reference
This dataset was created as part of the KASAL (Key-Axis-based Symmetry Axis Localization) Project.
You can find more details and access the project's GitHub repository here: https://github.com/WangYuLin-SEU/KASAL
5. License
This dataset consists of two parts with different licenses:
Google Scanned Objects (GSO) data: The GSO dataset is under its original license. Please refer to the Google Scanned Objects dataset page for the applicable license.
Symmetry axis data: The symmetry axis annotations provided in this dataset are released under the MIT License.
6. Contributors
Yulin Wang (Southeast University, China)
If you find our work useful, please cite it as follows:
@ARTICLE{KASAL,
author = {Wang, Yulin and Luo, Chen},
title = {Key-Axis-Based Localization of Symmetry Axes in 3D Objects Utilizing Geometry and Texture},
journal= {IEEE Transactions on Image Processing},
year = {2024},
volume = {33},
pages = {6720-6733},
doi = {10.1109/TIP.2024.3515801}
}
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