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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type struct<edges: list<item: struct<id: string, x: double, y: double>>, id: string, verified: list<item: int64>> to null
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2223, in cast_table_to_schema
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2224, in <listcomp>
cast_array_to_feature(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2001, in cast_array_to_feature
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2002, in <listcomp>
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2086, in cast_array_to_feature
return array_cast(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1950, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type struct<edges: list<item: struct<id: string, x: double, y: double>>, id: string, verified: list<item: int64>> to null
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/parquet_and_info.py", line 1456, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
drivableAreas dict | pedCrossings null | laneSegments null | filename string |
|---|---|---|---|
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1030662-v0",
"x": 4125.85,
"y": 1200,
"z": -17.9
},
{
"id": "da-1030662-v1",
"x": 4125.52,
"y": 1189.61,
"z": -17.89
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1030665-v0",
"x": 4366.38,
"y": 1080,
"z": -12.91
},
{
"id": "da-1030665-v1",
"x": 4366.16,
"y": 1068.3,
"z": -12.88
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1030667-v0",
"x": 4440,
"y": 1113.52,
"z": -13.6
},
{
"id": "da-1030667-v1",
"x": 4440,
"y": 1102.39,
"z": -13.28
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1031523-v0",
"x": 4560,
"y": 1197.89,
"z": -13.27
},
{
"id": "da-1031523-v1",
"x": 4560,
"y": 1180.94,
"z": -13.27
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1031582-v0",
"x": 4608.94,
"y": 1230,
"z": -13.19
},
{
"id": "da-1031582-v1",
"x": 4619.76,
"y": 1230,
"z": -12.74
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1031590-v0",
"x": 4290,
"y": 1203.27,
"z": -16.17
},
{
"id": "da-1031590-v1",
"x": 4273.84,
"y": 1212.73,
"z": -16.55
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
{
"changes": [
0
],
"modified": false,
"new": null,
"old": {
"area_boundary": [
{
"id": "da-1031683-v0",
"x": 4350,
"y": 1297.7,
"z": -16.44
},
{
"id": "da-1031683-v1",
"x": 4346.3,
"y": 1299.94,
"z": -16.53
},
... | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
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null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
null | null | null | 01bb304d7bd835f8bbef7086b688e35e__Summer_2019 |
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End of preview.
ArgoTweak: Towards Self-Updating HD Maps through Structured Priors
Lena Wild, Rafael Valencia, Patric Jensfelt
About
Reliable integration of prior information is crucial for selfverifying and self-updating HD maps. However, no public dataset includes the required triplet of prior maps, current maps, and sensor data. As a result, existing methods must rely on synthetic priors, which create inconsistencies and lead to a significant sim2real gap. To address this, we introduce ArgoTweak, the first dataset to complete the triplet with realistic map priors. At its core, ArgoTweak employs a bijective mapping framework, breaking down large-scale modifications into fine-grained atomic changes at the map element level, thus ensuring interpretability. This paradigm shift enables accurate change detection and integration while preserving unchanged elements with high fidelity.
License
This dataset is derived from the Argoverse 2 Map Change Dataset, originally released by Argo AI under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). Our annotations are licensed under the same terms.
[v1.0.0] – 2025-08-01
🚀 Official release of the ArgoTweak dataset The numbers in the paper have been achieved with a legacy version (v0) of ArgoTweak. The official version v1 has been improved as follows:
- Refined lane segment connectivities (predecessors/successors) in multiple scenes
- Annotated changes in the test split that were not identified in the original dataset https://github.com/johnwlambert/tbv/blob/main/labeled_data/tbv_val_split_annotations.json
- Improved consistencies of geometry annotations in several maps
- Removed incorrect intersection status of isolated lane segments
If, for any reason, you require access to the legacy version (v0) of ArgoTweak, please contact the authors directly.
Quick Start
Please refer to our ✨dataset page✨ for more detail.
Citation
@inproceedings{wild2025argotweak,
title={ArgoTweak: Towards Self-Updating HD Maps through Structured Priors},
author={Lena Wild and Rafael Valencia and Patric Jensfelt},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
year={2025}
}
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