Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<coordinate_reference: string, adjacency_tolerance_m: double, measurement_method: struct<alignment_error_m: string>, layers: struct<road_edges: struct<features: list<item: struct<feature_id: string, geometry: struct<type: string, coordinates: list<item: list<item: int64>>>>>>, curb_lines: struct<features: list<item: struct<feature_id: string, geometry: struct<type: string, coordinates: list<item: list<item: double>>>>>>>>
to
{'coordinate_reference': Value('string'), 'measurement_method': {'alignment_error_m': Value('string')}, 'layers': {'lane_boundaries': {'features': List({'feature_id': Value('string'), 'geometry': {'type': Value('string'), 'coordinates': List(List(Value('int64')))}})}, 'lane_centerlines': {'features': List({'feature_id': Value('string'), 'geometry': {'type': Value('string'), 'coordinates': 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<coordinate_reference: string, adjacency_tolerance_m: double, measurement_method: struct<alignment_error_m: string>, layers: struct<road_edges: struct<features: list<item: struct<feature_id: string, geometry: struct<type: string, coordinates: list<item: list<item: int64>>>>>>, curb_lines: struct<features: list<item: struct<feature_id: string, geometry: struct<type: string, coordinates: list<item: list<item: double>>>>>>>>
to
{'coordinate_reference': Value('string'), 'measurement_method': {'alignment_error_m': Value('string')}, 'layers': {'lane_boundaries': {'features': List({'feature_id': Value('string'), 'geometry': {'type': Value('string'), 'coordinates': List(List(Value('int64')))}})}, 'lane_centerlines': {'features': List({'feature_id': Value('string'), 'geometry': {'type': Value('string'), 'coordinates': 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.
High-Definition Map Cross-Layer Spatial Consistency Benchmark
Designed for evaluating urban road HD maps, this benchmark covers GIS layers such as lane markings, lane centerlines, road boundaries, and road facilities, together with feature geometries and coordinate reference information. It provides spatial relation queries and reference judgments for positions, alignment errors, and containment across layers or features, enabling assessment of a model's understanding of spatial relationships in multilayer HD maps. Typical applications include 2D spatial understanding evaluation, map data quality checks, and related model development.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| gis_layer_data | object | Raw GIS data for layers such as lane markings, lane centerlines, road boundaries, and road facilities, including features, geometric coordinates, and coordinate reference information. |
| relation_query | string | Describes the two layers or features being evaluated and the spatial relation to determine. |
| relation_exists | boolean | Indicates whether the spatial relation stated in the query holds. |
| alignment_error_m | number | The alignment error in meters, calculated from the geometric positions of the relevant layers or features. |
| containment_status | string | Records the containment judgment between target features; not applicable indicates that the query does not involve containment. |
| reference_relation | string | The spatial relation category established from layer geometries and reference annotations. |
| reference_explanation | string | Explains the geometric position, boundary alignment, or containment evidence supporting the reference spatial relation judgment. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Source & Contact
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