The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema: string
updated: timestamp[s]
release_status: string
downloadable_scene_artifacts: list<item: null>
child 0, item: null
development_scene: struct<id: string, source_sha256: string, source_included: bool, visual_acceptance: bool>
child 0, id: string
child 1, source_sha256: string
child 2, source_included: bool
child 3, visual_acceptance: bool
planned_components: list<item: string>
child 0, item: string
neural_checkpoints_included: bool
kind: string
formal_benchmark: bool
files: list<item: struct<path: string, bytes: int64, sha256: string>>
child 0, item: struct<path: string, bytes: int64, sha256: string>
child 0, path: string
child 1, bytes: int64
child 2, sha256: string
date: timestamp[s]
to
{'schema': Value('string'), 'kind': Value('string'), 'date': Value('timestamp[s]'), 'formal_benchmark': Value('bool'), 'files': List({'path': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string')})}
because column names don't match
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 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema: string
updated: timestamp[s]
release_status: string
downloadable_scene_artifacts: list<item: null>
child 0, item: null
development_scene: struct<id: string, source_sha256: string, source_included: bool, visual_acceptance: bool>
child 0, id: string
child 1, source_sha256: string
child 2, source_included: bool
child 3, visual_acceptance: bool
planned_components: list<item: string>
child 0, item: string
neural_checkpoints_included: bool
kind: string
formal_benchmark: bool
files: list<item: struct<path: string, bytes: int64, sha256: string>>
child 0, item: struct<path: string, bytes: int64, sha256: string>
child 0, path: string
child 1, bytes: int64
child 2, sha256: string
date: timestamp[s]
to
{'schema': Value('string'), 'kind': Value('string'), 'date': Value('timestamp[s]'), 'formal_benchmark': Value('bool'), 'files': List({'path': Value('string'), 'bytes': Value('int64'), 'sha256': 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.
CityAgentBench — scene resources
Project page · GitHub · Task preview
This repository is the distribution entry for CityAgentBench's reconstructed Shenzhen city assets and future evaluation environment packages. The project covers Talent Park, the Chunsun district, the Chuncan venue and their surrounding streets.
Current release: resource card and manifest only. No Blender scene, UE project, engine, standalone application, texture bundle or neural-network checkpoint is downloadable here yet. This page does not establish that a clean-machine evaluation can already be run.
Intended artifacts
| Component | Purpose | Current state |
|---|---|---|
| Blender source scene | Continue construction and repair | Packaging and dependency closure pending |
| UE city scene/project | Native rendering, movement and collision | Runtime packaging and visual acceptance pending |
| Geometry/material dependencies | Restore the exact resource bindings | Inventory and redistribution review pending |
| Runtime configuration and public map | Reproduce a compatible environment | Versioned portable bundle pending |
The current development scene identifier is saved193. Its source hash is recorded in
resource-manifest.json for identity only. It does not mean that the source file is included
or that native glass/grass appearance has passed final acceptance.
Reproducibility
Each future artifact will include its version, filename, byte size, SHA-256, dependencies, compatible code/protocol revision, restoration instructions and applicable terms. The resource manifest will distinguish available downloads from planned components. Large archives may be split into named parts with exact reconstruction and verification steps. Engine caches and redundant historical working copies are not part of the intended release.
Scene models are distributed as Dataset assets. Neural-network weights, if released later, will use a separate Model repository with their own model card. This repository has no dataset table or Data Viewer content yet; the task/image preview is in the linked tasks repository.
Terms
No project-wide scene/data license is declared yet. Engine, plugin, texture and source-data terms remain component-specific. A future asset package will document its redistribution basis instead of implying that all dependencies share one license.
中文说明
本页用于后续分发深圳项目的 Blender/UE 城市场景及评测运行资源，目前先建立资源说明和清单。 完整场景大文件尚未上传；saved193 是当前开发版本身份，不代表已经完成全部视觉验收。 题目与题图放在独立的 CityAgentBench-tasks 仓库。这里的“三维模型”属于场景资产， 与需要放入 Model 仓库的神经网络权重不同。
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