The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
OOD-PerceptionBench — asset pack v0.9
Cooked CARLA 0.9.15 assets for OOD-PerceptionBench, a closed-loop driving benchmark that separates visual (appearance) out-of-distribution shift from geometric (shape/size) shift.
Code, routes, baseline records and documentation:
https://github.com/farrosalferro/OODPerceptionBench (branch master).
This repository holds only the binary assets, which are too large for GitHub.
Version stamp: asset pack v0.9, corresponding to arXiv v1 of the paper. v1.0 will add replacement assets for the props that cannot be redistributed today, and the numbers it produces will not be interchangeable with v0.9 numbers. Always record which pack version you used.
⚠ Read this before you use it
This pack contains six of the benchmark's eighteen OOD props. The other twelve are not redistributable (marketplace licences that forbid standalone redistribution and AI use; two free downloads whose uploaders did not own the underlying IP). They are specified dimensionally instead, and the repository ships classifier notebooks so you can check your own substitutes against the same admissibility rule the paper uses.
With this pack you can run 237 of the 475 routes. See §4.
One asset is NonCommercial. walker.pedestrian.firefighter is CC BY-NC 4.0. It is
packaged separately so you can leave it out. See §3.
A missing CARLA asset fails silently. If a blueprint ID is not registered, the
benchmark harness substitutes a different actor and the route finishes with a plausible
Driving Score. Run tools/verify_pack.py after installing. This is not optional advice.
1. Contents
| Blueprint ID | Category | Shift level | Author | Licence |
|---|---|---|---|---|
walker.pedestrian.astronaut |
pedestrian | visual | Antropik | CC BY 4.0 |
walker.pedestrian.firefighter |
pedestrian | visual | KIFIR | ⚠ CC BY-NC 4.0 |
walker.pedestrian.deliveryrobot |
pedestrian | geometric | Bento (@gostbento) | CC BY 4.0 |
walker.pedestrian.boar |
pedestrian | geometric | AnimalMesh 3D | CC BY 4.0 |
static.prop.concreteroadbarrier |
static | geometric | widthRider | CC BY 4.0 |
static.prop.roadclosedbarricade |
static | geometric | exiS7-Gs | CC BY 4.0 |
Plus one modified CARLA base-content asset, WalkerFactory (CC BY, © CARLA Simulator
authors) — the four walkers cannot register without it. Full licence text and links:
ATTRIBUTION.md. Why the factory has to ship, and what it costs: WALKERFACTORY_DECISION.md.
ood-perceptionbench-props-v0.9.tar.gz 15.8 MB CC BY 4.0
ood-perceptionbench-walkers-ccby-v0.9.tar.gz 38.4 MB CC BY 4.0 (includes WalkerFactory)
ood-perceptionbench-walkers-ccbync-v0.9.tar.gz 112.3 MB CC BY-NC 4.0
--------
166.6 MB download · 185.5 MB installed · 195 files
2. Install
Requires an official CARLA 0.9.15 Linux build. Full instructions, including uninstall
and a tar pitfall that can silently skip the factory, are in INSTALL.md.
cd /path/to/CARLA_0.9.15
sha256sum -c SHA256SUMS
mkdir -p Import && cp ood-perceptionbench-*-v0.9.tar.gz Import/
./ImportAssets.sh
# then, with a CARLA server running:
python3 tools/verify_pack.py --port 2000
ImportAssets.sh is CARLA's own installer; the tarballs are rooted at CarlaUE4/ so they
extract straight into the build.
The pack overwrites CarlaUE4/Content/Carla/Blueprints/Walkers/WalkerFactory.{uasset,uexp}.
Install into a copy of CARLA dedicated to this benchmark, and only over 0.9.15.
3. The NonCommercial asset
walker.pedestrian.firefighter, by KIFIR, is CC BY-NC 4.0: no commercial use of
the model, of derivatives, of rendered frames, or of datasets built from them.
It lives in its own tarball. If your use is commercial, do not install
ood-perceptionbench-walkers-ccbync-v0.9.tar.gz and run the verifier with
--without-nc. Everything else in the pack is CC BY 4.0. The cost of omitting it is 18
pedestrian routes.
There is no IP defect here — it is the author's original work — and it is deliberately not being replaced.
4. Route coverage
| Category | Runnable with this pack | Total | Gap |
|---|---|---|---|
| static | 30 | 70 | 40 routes need 4 non-redistributable props |
| pedestrian | 126 | 162 | 36 routes need soldier / wheelchair |
| vehicle | 81 | 243 | 162 routes need 6 non-redistributable vehicles |
| total | 237 | 475 | 238 |
145 of the 237 are the benchmark's base-level routes, which use native CARLA blueprints
and need no pack at all. This pack unlocks the other 92 shift-level routes: 18 each for
astronaut, firefighter, boar and deliveryrobot, 10 each for concreteroadbarrier and
roadclosedbarricade.
The 238 remaining routes are not runnable at v0.9. Running them anyway yields substituted-actor results that look normal and mean nothing.
Per-route baseline records for the full 475 across 17 models are published in the code repository — verifying the paper's claims needs no GPU and no assets.
5. Phantom blueprint IDs
After installing, the blueprint library will advertise nine walker IDs whose content is not
in this pack: soldier, wheelchair, ball, caneman, cow, crutcheswoman, deer,
labrador, tire. They come from the shipped WalkerFactory, which was cooked from a
build containing more assets than are redistributable.
All nine are unspawnable — try_spawn_actor returns None and spawn_actor raises.
They cannot silently give you the wrong prop, but they are not usable. verify_pack.py
asserts that none of them spawns. Details and the reasoning: WALKERFACTORY_DECISION.md.
6. Files in this repository
README.md this file
INSTALL.md install, verify, uninstall, rebuild
ATTRIBUTION.md per-asset authors, licences, source links
WALKERFACTORY_DECISION.md why WalkerFactory ships and what it costs
SHA256SUMS checksums of the three tarballs
MANIFEST.tsv every shipped file: path, sha256, size, asset, licence
dist/ the three tarballs
tools/verify_pack.py post-install verification (run it)
tools/goldens.json reference bounding boxes for the six assets
build/build_asset_pack.sh reproduces this pack from a CARLA build
build/make_manifest.py emits SHA256SUMS and MANIFEST.tsv
build/EXCLUSIONS.tsv files present in the source build and deliberately not shipped
7. Citation
Cite the OOD-PerceptionBench paper (see CITATION.cff in the code repository), credit
CARLA for the simulator content, and reproduce the per-asset attribution in
ATTRIBUTION.md — CC BY 4.0 requires it.
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