Hugging Face's logo

Datasets:
SEU-WYL
/
DSRSTO-dataset

Modalities:
3D
Text
Formats:
json
Size:
< 1K
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files Community
1
Dataset Viewer
Auto-converted to Parquet
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
sym_type: string
n-fold: int64
ADI-C: bool
current_obj_info: 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>>>>
vs
sym_type: string
n-fold: int64
ADI-C: bool
current_obj_info: struct<diameter: double, min_x: double, min_y: double, min_z: double, size_x: double, size_y: double, size_z: double, symmetries_continuous: list<item: struct<axis: list<item: double>, offset: list<item: double>>>>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 231, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3335, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2096, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2296, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 504, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              sym_type: string
              n-fold: int64
              ADI-C: bool
              current_obj_info: 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>>>>
              vs
              sym_type: string
              n-fold: int64
              ADI-C: bool
              current_obj_info: struct<diameter: double, min_x: double, min_y: double, min_z: double, size_x: double, size_y: double, size_z: double, symmetries_continuous: list<item: struct<axis: list<item: double>, offset: list<item: double>>>>

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

DSRSTO-dataset

1. Dataset Description

The DSRSTO-dataset is a specialized dataset designed to support research on 3D object symmetry. It includes annotations for seven distinct types of symmetries and is composed of 3D models created using 3D CAD software, making it a valuable resource for tasks such as pose estimation, object recognition, and symmetry-based 3D model analysis.

Key Features:

Learning Resource: This dataset serves as an excellent learning material, helping researchers quickly learn to use the KASAL software and accelerate their pose estimation task development.

2. Dataset Structure

The dataset is organized as follows:

Models: 3D models are designed using 3D CAD software such as Solidworks and Blender.

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

3. 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

4. License

MIT License.

5. 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}
}
Downloads last month
231
Size of downloaded dataset files:
196 kB
Size of the auto-converted Parquet files:
164 kB
Number of rows:
31