The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
source_file: string
object_bounds: list<item: double>
child 0, item: double
best_grasp_strategy: struct<method: string, gripper_type: string, target_face_id: int64, approach_direction: list<item: d (... 46 chars omitted)
child 0, method: string
child 1, gripper_type: string
child 2, target_face_id: int64
child 3, approach_direction: list<item: double>
child 0, item: double
child 4, confidence: double
child 5, reasoning: string
face_recommendations: list<item: struct<face_id: int64, category_name: string, geom_type: string, area: double, grasp_meth (... 142 chars omitted)
child 0, item: struct<face_id: int64, category_name: string, geom_type: string, area: double, grasp_method: string, (... 130 chars omitted)
child 0, face_id: int64
child 1, category_name: string
child 2, geom_type: string
child 3, area: double
child 4, grasp_method: string
child 5, gripper_type: string
child 6, approach_direction: list<item: double>
child 0, item: double
child 7, grasp_point: list<item: double>
child 0, item: double
child 8, confidence: double
child 9, notes: string
grasp_method_summary: struct<lateral_pinch: struct<face_count: int64, total_area: double>, edge_grip: struct<face_count: i (... 208 chars omitted)
child 0, lateral_pinch: struct<face_count: int64, total_area: double>
child 0, face_count: int64
child 1, total_area: double
child 1, edge_grip: struct<face_count: int64
...
child 1, commercial: int64
child 2, currency: string
legal: struct<dataset_license: string, model_license: string, original_work: bool, commercial_use_allowed: (... 47 chars omitted)
child 0, dataset_license: string
child 1, model_license: string
child 2, original_work: bool
child 3, commercial_use_allowed: bool
child 4, attribution_required: bool
child 5, note: string
objects: list<item: struct<name: string, num_faces: int64, num_triangles: int64, shape_bounds: list<item: dou (... 296 chars omitted)
child 0, item: struct<name: string, num_faces: int64, num_triangles: int64, shape_bounds: list<item: double>, topol (... 284 chars omitted)
child 0, name: string
child 1, num_faces: int64
child 2, num_triangles: int64
child 3, shape_bounds: list<item: double>
child 0, item: double
child 4, topology_categories: list<item: string>
child 0, item: string
child 5, category_distribution: struct<Boss: int64, Chamfer: int64, LateralPlane_Z: int64, HorizontalPlane: int64, LateralPlane_X: i (... 70 chars omitted)
child 0, Boss: int64
child 1, Chamfer: int64
child 2, LateralPlane_Z: int64
child 3, HorizontalPlane: int64
child 4, LateralPlane_X: int64
child 5, NearHorizontal: int64
child 6, NearLateral_X: int64
child 7, FreeSurface: int64
child 6, has_step_file: bool
child 7, has_grasp_recommendations: bool
description: string
to
{'dataset_name': Value('string'), 'version': Value('string'), 'display_name': Value('string'), 'description': Value('string'), 'industry': Value('string'), 'generated_at': Value('string'), 'num_objects': Value('int64'), 'total_faces': Value('int64'), 'total_triangles': Value('int64'), 'topology_categories_present': List(Value('string')), 'objects': List({'name': Value('string'), 'num_faces': Value('int64'), 'num_triangles': Value('int64'), 'shape_bounds': List(Value('float64')), 'topology_categories': List(Value('string')), 'category_distribution': {'Boss': Value('int64'), 'Chamfer': Value('int64'), 'LateralPlane_Z': Value('int64'), 'HorizontalPlane': Value('int64'), 'LateralPlane_X': Value('int64'), 'NearHorizontal': Value('int64'), 'NearLateral_X': Value('int64'), 'FreeSurface': Value('int64')}, 'has_step_file': Value('bool'), 'has_grasp_recommendations': Value('bool')}), 'total_statistics': {'total_faces': Value('int64'), 'total_triangles': Value('int64'), 'total_category_distribution': {'Boss': Value('int64'), 'Chamfer': Value('int64'), 'LateralPlane_Z': Value('int64'), 'HorizontalPlane': Value('int64'), 'LateralPlane_X': Value('int64'), 'NearHorizontal': Value('int64'), 'NearLateral_X': Value('int64'), 'FreeSurface': Value('int64')}}, 'pricing': {'personal': Value('int64'), 'commercial': Value('int64'), 'currency': Value('string')}, 'legal': {'dataset_license': Value('string'), 'model_license': Value('string'), 'original_work': Value('bool'), 'commercial_use_allowed': Value('bool'), 'attribution_required': Value('bool'), 'note': Value('string')}, 'source': {'topology_data': Value('string'), 'step_files': Value('string'), 'parser': Value('string')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
source_file: string
object_bounds: list<item: double>
child 0, item: double
best_grasp_strategy: struct<method: string, gripper_type: string, target_face_id: int64, approach_direction: list<item: d (... 46 chars omitted)
child 0, method: string
child 1, gripper_type: string
child 2, target_face_id: int64
child 3, approach_direction: list<item: double>
child 0, item: double
child 4, confidence: double
child 5, reasoning: string
face_recommendations: list<item: struct<face_id: int64, category_name: string, geom_type: string, area: double, grasp_meth (... 142 chars omitted)
child 0, item: struct<face_id: int64, category_name: string, geom_type: string, area: double, grasp_method: string, (... 130 chars omitted)
child 0, face_id: int64
child 1, category_name: string
child 2, geom_type: string
child 3, area: double
child 4, grasp_method: string
child 5, gripper_type: string
child 6, approach_direction: list<item: double>
child 0, item: double
child 7, grasp_point: list<item: double>
child 0, item: double
child 8, confidence: double
child 9, notes: string
grasp_method_summary: struct<lateral_pinch: struct<face_count: int64, total_area: double>, edge_grip: struct<face_count: i (... 208 chars omitted)
child 0, lateral_pinch: struct<face_count: int64, total_area: double>
child 0, face_count: int64
child 1, total_area: double
child 1, edge_grip: struct<face_count: int64
...
child 1, commercial: int64
child 2, currency: string
legal: struct<dataset_license: string, model_license: string, original_work: bool, commercial_use_allowed: (... 47 chars omitted)
child 0, dataset_license: string
child 1, model_license: string
child 2, original_work: bool
child 3, commercial_use_allowed: bool
child 4, attribution_required: bool
child 5, note: string
objects: list<item: struct<name: string, num_faces: int64, num_triangles: int64, shape_bounds: list<item: dou (... 296 chars omitted)
child 0, item: struct<name: string, num_faces: int64, num_triangles: int64, shape_bounds: list<item: double>, topol (... 284 chars omitted)
child 0, name: string
child 1, num_faces: int64
child 2, num_triangles: int64
child 3, shape_bounds: list<item: double>
child 0, item: double
child 4, topology_categories: list<item: string>
child 0, item: string
child 5, category_distribution: struct<Boss: int64, Chamfer: int64, LateralPlane_Z: int64, HorizontalPlane: int64, LateralPlane_X: i (... 70 chars omitted)
child 0, Boss: int64
child 1, Chamfer: int64
child 2, LateralPlane_Z: int64
child 3, HorizontalPlane: int64
child 4, LateralPlane_X: int64
child 5, NearHorizontal: int64
child 6, NearLateral_X: int64
child 7, FreeSurface: int64
child 6, has_step_file: bool
child 7, has_grasp_recommendations: bool
description: string
to
{'dataset_name': Value('string'), 'version': Value('string'), 'display_name': Value('string'), 'description': Value('string'), 'industry': Value('string'), 'generated_at': Value('string'), 'num_objects': Value('int64'), 'total_faces': Value('int64'), 'total_triangles': Value('int64'), 'topology_categories_present': List(Value('string')), 'objects': List({'name': Value('string'), 'num_faces': Value('int64'), 'num_triangles': Value('int64'), 'shape_bounds': List(Value('float64')), 'topology_categories': List(Value('string')), 'category_distribution': {'Boss': Value('int64'), 'Chamfer': Value('int64'), 'LateralPlane_Z': Value('int64'), 'HorizontalPlane': Value('int64'), 'LateralPlane_X': Value('int64'), 'NearHorizontal': Value('int64'), 'NearLateral_X': Value('int64'), 'FreeSurface': Value('int64')}, 'has_step_file': Value('bool'), 'has_grasp_recommendations': Value('bool')}), 'total_statistics': {'total_faces': Value('int64'), 'total_triangles': Value('int64'), 'total_category_distribution': {'Boss': Value('int64'), 'Chamfer': Value('int64'), 'LateralPlane_Z': Value('int64'), 'HorizontalPlane': Value('int64'), 'LateralPlane_X': Value('int64'), 'NearHorizontal': Value('int64'), 'NearLateral_X': Value('int64'), 'FreeSurface': Value('int64')}}, 'pricing': {'personal': Value('int64'), 'commercial': Value('int64'), 'currency': Value('string')}, 'legal': {'dataset_license': Value('string'), 'model_license': Value('string'), 'original_work': Value('bool'), 'commercial_use_allowed': Value('bool'), 'attribution_required': Value('bool'), 'note': Value('string')}, 'source': {'topology_data': Value('string'), 'step_files': Value('string'), 'parser': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Huhb3D Gear Topology Dataset
STEP topology annotated dataset for 4 spur gear variants (ISO 1328 style) with per-face semantic labels. Includes Chamfer, Boss, HorizontalPlane, and NearHorizontal labels for gear inspection and robotic assembly.
What Makes This Dataset Unique
This is the only publicly available dataset that provides STEP-parsed per-face topology labels for industrial CAD models. Unlike mesh-only datasets, our topology annotations are derived directly from the STEP B-Rep structure using OpenCascade, providing:
- Per-face semantic labels: Each mesh face is classified into one of 15 topology categories
- STEP source files: Original parametric CAD models for precise geometry queries
- Robotic grasp planning: Topology labels enable grasp strategy selection by face type
- 6DoF pose estimation: Face-level annotations support pose refinement algorithms
Overview
- 4 industrial mechanical parts
- 519 total B-Rep faces
- 8916 total mesh triangles
- 8 topology categories with per-face semantic labels
- Industry: Gear & Transmission Manufacturing
- Source models: STEP (ISO 10303-21) CAD files
Directory Structure
Huhb3D-Gear-Topology/
README.md
LICENSE
DATASET_METADATA.json
checksums.sha256
source_step/
gear.step
...
objects/
gear/
topology_labels.json # Per-triangle topology labels
topology_summary.json # Topology statistics summary
grasp_recommendations.json # Grasp recommendations (if available)
...
Object List
| Object | Faces | Triangles | STEP | Grasp | Topology Categories |
|---|---|---|---|---|---|
| gear | 127 | 2224 | ✓ | ✓ | Boss, Chamfer, FreeSurface, HorizontalPlane, LateralPlane_X, LateralPlane_Z, NearHorizontal, NearLateral_X |
| gear_small | 78 | 2004 | ✓ | ✓ | Boss, Chamfer, FreeSurface, HorizontalPlane, LateralPlane_X, LateralPlane_Z, NearHorizontal, NearLateral_X |
| gear_medium | 127 | 2224 | ✓ | ✓ | Boss, Chamfer, FreeSurface, HorizontalPlane, LateralPlane_X, LateralPlane_Z, NearHorizontal, NearLateral_X |
| gear_large | 187 | 2464 | ✓ | ✓ | Boss, Chamfer, HorizontalPlane, LateralPlane_X, LateralPlane_Z, NearHorizontal, NearLateral_X |
Topology Categories
| ID | Category | Description | Color |
|---|---|---|---|
| 0 | FreeSurface | 自由曲面(圆柱面、圆锥面、B样条曲面等) | #7F7F7F |
| 1 | HorizontalPlane | 法线平行于 Z 轴的平面(顶面/底面) | #0000FF |
| 2 | LateralPlane_X | 法线平行于 X 轴的平面(侧面) | #00FF00 |
| 3 | LateralPlane_Z | 法线平行于 Z 轴的竖直平面 | #FF0000 |
| 4 | NearHorizontal | 与水平面倾斜角 <30° 的平面 | #FFFF00 |
| 5 | NearLateral_X | 与 X 侧面倾斜角 <30° 的平面 | #FF00FF |
| 11 | Boss | 凸起圆柱台(安装凸台、垫台) | #00CC66 |
| 12 | Chamfer | 两个面之间的倾斜过渡边 | #CC6600 |
Grasp Recommendations
Some objects include grasp_recommendations.json with pre-computed robotic grasp poses.
These files are generated by the grasp_recommendations.py module and contain:
- Recommended grasp approach directions
- Gripper opening widths
- Grasp quality scores
Data Format
topology_labels.json
Per-object file containing:
source_file: Original STEP file nametotal_triangles: Total number of mesh trianglestotal_faces: Total number of B-Rep facesshape_bounds: Bounding box [xmin, ymin, zmin, xmax, ymax, zmax]category_names: Mapping from category ID to nametriangle_labels: Array of category IDs, one per trianglefaces: Array of face objects with:face_id,geom_type,category_id,category_namearea,triangle_count,triangle_startextra: Optional dict withradius,axis_direction,normal
topology_summary.json
Per-object file containing:
source_file,total_faces,total_triangles,shape_boundscategories: Dict mapping category ID to name, face_count, triangle_count, total_area
grasp_recommendations.json (optional)
Per-object file containing pre-computed grasp poses with approach directions, gripper widths, and quality scores.
Pricing
| License | Price |
|---|---|
| Personal / Academic | $29 |
| Commercial | $79 |
All prices in USD. Commercial license permits use in proprietary products.
Citation
If you use this dataset in your research, please cite:
@dataset{huhb3d_gear_topology,
title = {Huhb3D Gear Topology Dataset},
author = {Huhb},
year = {2026},
version = {1.0.0},
url = {https://github.com/huhb-ai/Huhb3D-Topology-Dataset}
}
License
- 3D Models: CC0 (Public Domain) — original creations, no restrictions
- Dataset (annotations, metadata, packaging): CC-BY-4.0 — attribution required
You are free to share and adapt for any purpose, including commercially, as long as appropriate credit is given.
See LICENSE for the full license text.
Contact
- Email: huhb_ai@outlook.com
- GitHub: https://github.com/huhb-ai
- Downloads last month
- 9