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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 13 new columns ({'1544578684920578496', '4078658.998', '0.003359874599', '0.01546711812', '18.51297703', '-0.005881348065', '0.9998747319', '0.01469456516', '-0.9860059176', '337320.3546', '0.1660614348', '0.9861096851', '0.1659912607'}) and 13 missing columns ({'-0.001397078874', '18.51783', '0.00229921451', '0.002030150658', '-0.247800239', '0.999995296', '-0.9688073005', '-0.2478046169', '336429.2038', '0.002730580465', '4074319.999', '0.9688090214', '1544578500918889766'}).
This happened while the csv dataset builder was generating data using
hf://datasets/gladiator7737/kaist-urban-dataset/urban19.csv (at revision fa6ebd163d47da9f0e01b523614733908752a0b6), ['hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban18.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban19.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban20.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban21.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban22.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban23.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban24.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban25.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban26.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban27.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban28.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban29.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban30.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban31.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban32.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban33.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban34.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban35.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban36.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban37.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban38.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban39.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
1544578684920578496: int64
0.1660614348: double
-0.9860059176: double
0.01469456516: double
337320.3546: double
0.9861096851: double
0.1659912607: double
-0.005881348065: double
4078658.998: double
0.003359874599: double
0.01546711812: double
0.9998747319: double
18.51297703: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1926
to
{'1544578500918889766': Value('int64'), '-0.2478046169': Value('float64'), '-0.9688073005': Value('float64'), '0.00229921451': Value('float64'), '336429.2038': Value('float64'), '0.9688090214': Value('float64'), '-0.247800239': Value('float64'), '0.002030150658': Value('float64'), '4074319.999': Value('float64'), '-0.001397078874': Value('float64'), '0.002730580465': Value('float64'), '0.999995296': Value('float64'), '18.51783': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 13 new columns ({'1544578684920578496', '4078658.998', '0.003359874599', '0.01546711812', '18.51297703', '-0.005881348065', '0.9998747319', '0.01469456516', '-0.9860059176', '337320.3546', '0.1660614348', '0.9861096851', '0.1659912607'}) and 13 missing columns ({'-0.001397078874', '18.51783', '0.00229921451', '0.002030150658', '-0.247800239', '0.999995296', '-0.9688073005', '-0.2478046169', '336429.2038', '0.002730580465', '4074319.999', '0.9688090214', '1544578500918889766'}).
This happened while the csv dataset builder was generating data using
hf://datasets/gladiator7737/kaist-urban-dataset/urban19.csv (at revision fa6ebd163d47da9f0e01b523614733908752a0b6), ['hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban18.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban19.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban20.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban21.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban22.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban23.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban24.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban25.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban26.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban27.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban28.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban29.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban30.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban31.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban32.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban33.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban34.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban35.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban36.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban37.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban38.csv', 'hf://datasets/gladiator7737/kaist-urban-dataset@fa6ebd163d47da9f0e01b523614733908752a0b6/urban39.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
1544578500918889766 int64 | -0.2478046169 float64 | -0.9688073005 float64 | 0.00229921451 float64 | 336429.2038 float64 | 0.9688090214 float64 | -0.247800239 float64 | 0.002030150658 float64 | 4074319.999 float64 | -0.001397078874 float64 | 0.002730580465 float64 | 0.999995296 float64 | 18.51783 float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,544,578,500,929,064,700 | -0.247735 | -0.968825 | 0.002278 | 336,429.1458 | 0.968827 | -0.247731 | 0.002028 | 4,074,320.223 | -0.001401 | 0.002709 | 0.999995 | 18.517553 |
1,544,578,500,939,261,400 | -0.247638 | -0.96885 | 0.002392 | 336,429.0876 | 0.968852 | -0.247633 | 0.002111 | 4,074,320.448 | -0.001453 | 0.00284 | 0.999995 | 18.517274 |
1,544,578,500,949,454,600 | -0.247532 | -0.968877 | 0.002454 | 336,429.0296 | 0.968879 | -0.247527 | 0.002091 | 4,074,320.672 | -0.001418 | 0.002895 | 0.999995 | 18.516984 |
1,544,578,500,959,680,000 | -0.247447 | -0.968899 | 0.002324 | 336,428.9716 | 0.9689 | -0.247443 | 0.002008 | 4,074,320.896 | -0.001371 | 0.002749 | 0.999995 | 18.516702 |
1,544,578,500,969,864,200 | -0.247317 | -0.968932 | 0.002239 | 336,428.9135 | 0.968934 | -0.247313 | 0.002005 | 4,074,321.121 | -0.001389 | 0.002666 | 0.999995 | 18.51643 |
1,544,578,500,980,081,400 | -0.247161 | -0.968972 | 0.002311 | 336,428.8556 | 0.968973 | -0.247157 | 0.002077 | 4,074,321.345 | -0.001441 | 0.002753 | 0.999995 | 18.516155 |
1,544,578,500,990,259,500 | -0.247094 | -0.968989 | 0.002417 | 336,428.7975 | 0.96899 | -0.247089 | 0.002216 | 4,074,321.57 | -0.00155 | 0.00289 | 0.999995 | 18.515865 |
1,544,578,501,000,460,000 | -0.246997 | -0.969014 | 0.002311 | 336,428.7397 | 0.969015 | -0.246992 | 0.002241 | 4,074,321.795 | -0.001601 | 0.002793 | 0.999995 | 18.515552 |
1,544,578,501,010,672,000 | -0.246867 | -0.969047 | 0.002275 | 336,428.6818 | 0.969048 | -0.246862 | 0.002286 | 4,074,322.019 | -0.001654 | 0.002769 | 0.999995 | 18.515226 |
1,544,578,501,020,863,700 | -0.246768 | -0.969071 | 0.002498 | 336,428.624 | 0.969073 | -0.246762 | 0.002387 | 4,074,322.244 | -0.001697 | 0.00301 | 0.999994 | 18.51489 |
1,544,578,501,031,053,300 | -0.246684 | -0.969092 | 0.002674 | 336,428.5663 | 0.969094 | -0.246677 | 0.002517 | 4,074,322.468 | -0.001779 | 0.003213 | 0.999993 | 18.514541 |
1,544,578,501,041,256,200 | -0.246611 | -0.969111 | 0.002616 | 336,428.5086 | 0.969113 | -0.246605 | 0.002542 | 4,074,322.693 | -0.001818 | 0.003162 | 0.999993 | 18.514178 |
1,544,578,501,051,461,600 | -0.2465 | -0.969139 | 0.002659 | 336,428.4508 | 0.969141 | -0.246493 | 0.0027 | 4,074,322.918 | -0.001962 | 0.003242 | 0.999993 | 18.513802 |
1,544,578,501,061,673,500 | -0.246359 | -0.969175 | 0.002813 | 336,428.3931 | 0.969176 | -0.246351 | 0.002857 | 4,074,323.142 | -0.002076 | 0.003431 | 0.999992 | 18.51339 |
1,544,578,501,071,865,900 | -0.246279 | -0.969194 | 0.002982 | 336,428.3354 | 0.969197 | -0.24627 | 0.002933 | 4,074,323.367 | -0.002108 | 0.003613 | 0.999991 | 18.512953 |
1,544,578,501,082,062,300 | -0.246227 | -0.969208 | 0.00299 | 336,428.2778 | 0.96921 | -0.246219 | 0.002951 | 4,074,323.592 | -0.002124 | 0.003624 | 0.999991 | 18.512511 |
1,544,578,501,092,257,500 | -0.24614 | -0.96923 | 0.002971 | 336,428.2202 | 0.969232 | -0.246131 | 0.002931 | 4,074,323.817 | -0.00211 | 0.003601 | 0.999991 | 18.512061 |
1,544,578,501,102,459,400 | -0.246033 | -0.969256 | 0.003161 | 336,428.1627 | 0.969259 | -0.246024 | 0.002958 | 4,074,324.042 | -0.00209 | 0.003792 | 0.999991 | 18.511623 |
1,544,578,501,112,665,900 | -0.245951 | -0.969276 | 0.003384 | 336,428.1052 | 0.96928 | -0.245941 | 0.003105 | 4,074,324.266 | -0.002178 | 0.004043 | 0.999989 | 18.511184 |
1,544,578,501,122,865,000 | -0.245895 | -0.96929 | 0.003465 | 336,428.0477 | 0.969294 | -0.245884 | 0.003173 | 4,074,324.491 | -0.002223 | 0.004139 | 0.999989 | 18.510723 |
1,544,578,501,133,062,700 | -0.245803 | -0.969313 | 0.003512 | 336,427.9903 | 0.969317 | -0.245792 | 0.003219 | 4,074,324.716 | -0.002257 | 0.004196 | 0.999989 | 18.510255 |
1,544,578,501,143,275,800 | -0.245687 | -0.969342 | 0.003699 | 336,427.933 | 0.969346 | -0.245676 | 0.003304 | 4,074,324.94 | -0.002294 | 0.004397 | 0.999988 | 18.509777 |
1,544,578,501,153,475,000 | -0.245601 | -0.969363 | 0.00392 | 336,427.8756 | 0.969368 | -0.245589 | 0.003358 | 4,074,325.165 | -0.002293 | 0.004625 | 0.999987 | 18.50929 |
1,544,578,501,163,656,400 | -0.245531 | -0.969381 | 0.004011 | 336,427.8182 | 0.969386 | -0.245519 | 0.003285 | 4,074,325.39 | -0.002199 | 0.004695 | 0.999987 | 18.508799 |
1,544,578,501,173,855,200 | -0.245443 | -0.969402 | 0.004139 | 336,427.7608 | 0.969409 | -0.245432 | 0.003189 | 4,074,325.615 | -0.002076 | 0.004795 | 0.999986 | 18.508337 |
1,544,578,501,184,058,000 | -0.245343 | -0.969426 | 0.004374 | 336,427.7036 | 0.969434 | -0.24533 | 0.003216 | 4,074,325.84 | -0.002044 | 0.005029 | 0.999985 | 18.507904 |
1,544,578,501,194,259,500 | -0.245242 | -0.969451 | 0.004613 | 336,427.6464 | 0.96946 | -0.245229 | 0.003285 | 4,074,326.065 | -0.002054 | 0.005278 | 0.999984 | 18.507476 |
1,544,578,501,204,460,000 | -0.245167 | -0.969469 | 0.004808 | 336,427.5892 | 0.969479 | -0.245153 | 0.003288 | 4,074,326.289 | -0.002008 | 0.005468 | 0.999983 | 18.507042 |
1,544,578,501,214,672,000 | -0.245098 | -0.969486 | 0.004931 | 336,427.5322 | 0.969496 | -0.245085 | 0.003214 | 4,074,326.514 | -0.001907 | 0.005568 | 0.999983 | 18.506622 |
1,544,578,501,224,878,600 | -0.244983 | -0.969514 | 0.005082 | 336,427.475 | 0.969526 | -0.244969 | 0.003183 | 4,074,326.739 | -0.001841 | 0.005707 | 0.999982 | 18.506227 |
1,544,578,501,235,074,800 | -0.244863 | -0.969543 | 0.005307 | 336,427.4179 | 0.969556 | -0.244848 | 0.003214 | 4,074,326.964 | -0.001816 | 0.005932 | 0.999981 | 18.505846 |
1,544,578,501,245,281,300 | -0.244788 | -0.969561 | 0.005488 | 336,427.3607 | 0.969575 | -0.244774 | 0.003207 | 4,074,327.189 | -0.001766 | 0.006106 | 0.99998 | 18.505467 |
1,544,578,501,255,489,800 | -0.244729 | -0.969576 | 0.005426 | 336,427.3037 | 0.96959 | -0.244715 | 0.003064 | 4,074,327.414 | -0.001643 | 0.006011 | 0.999981 | 18.505101 |
1,544,578,501,265,667,800 | -0.244659 | -0.969594 | 0.005354 | 336,427.2468 | 0.969608 | -0.244646 | 0.002944 | 4,074,327.639 | -0.001545 | 0.005911 | 0.999981 | 18.504767 |
1,544,578,501,275,856,000 | -0.244563 | -0.969618 | 0.005524 | 336,427.1899 | 0.969632 | -0.24455 | 0.002941 | 4,074,327.864 | -0.001501 | 0.006076 | 0.99998 | 18.504456 |
1,544,578,501,286,073,600 | -0.24446 | -0.969642 | 0.005772 | 336,427.133 | 0.969658 | -0.244447 | 0.002963 | 4,074,328.089 | -0.001462 | 0.006322 | 0.999979 | 18.504152 |
1,544,578,501,296,266,200 | -0.244445 | -0.969647 | 0.005602 | 336,427.0761 | 0.969662 | -0.244432 | 0.00277 | 4,074,328.314 | -0.001317 | 0.006109 | 0.99998 | 18.503854 |
1,544,578,501,306,452,000 | -0.244422 | -0.969654 | 0.005405 | 336,427.0194 | 0.969668 | -0.24441 | 0.002715 | 4,074,328.538 | -0.001312 | 0.005905 | 0.999982 | 18.503599 |
1,544,578,501,316,673,500 | -0.244278 | -0.96969 | 0.005424 | 336,426.9625 | 0.969704 | -0.244266 | 0.00284 | 4,074,328.763 | -0.001429 | 0.005954 | 0.999981 | 18.50334 |
1,544,578,501,326,874,600 | -0.244162 | -0.969718 | 0.005609 | 336,426.9055 | 0.969733 | -0.244148 | 0.002962 | 4,074,328.989 | -0.001502 | 0.006162 | 0.99998 | 18.503051 |
1,544,578,501,337,071,400 | -0.24413 | -0.969727 | 0.00551 | 336,426.8486 | 0.969742 | -0.244118 | 0.002817 | 4,074,329.215 | -0.001387 | 0.006031 | 0.999981 | 18.502742 |
1,544,578,501,347,282,700 | -0.24407 | -0.969742 | 0.005457 | 336,426.792 | 0.969757 | -0.244058 | 0.002728 | 4,074,329.44 | -0.001313 | 0.005958 | 0.999981 | 18.502467 |
1,544,578,501,357,470,000 | -0.243967 | -0.969768 | 0.00542 | 336,426.7353 | 0.969783 | -0.243957 | 0.002587 | 4,074,329.664 | -0.001187 | 0.005888 | 0.999982 | 18.502205 |
1,544,578,501,367,688,700 | -0.24387 | -0.969792 | 0.005574 | 336,426.6786 | 0.969807 | -0.243859 | 0.00259 | 4,074,329.89 | -0.001152 | 0.006038 | 0.999981 | 18.501976 |
1,544,578,501,377,875,200 | -0.243796 | -0.969811 | 0.005525 | 336,426.622 | 0.969826 | -0.243786 | 0.002514 | 4,074,330.115 | -0.001091 | 0.005972 | 0.999982 | 18.501752 |
1,544,578,501,388,071,000 | -0.243714 | -0.969831 | 0.005521 | 336,426.5654 | 0.969846 | -0.243704 | 0.002535 | 4,074,330.34 | -0.001113 | 0.005972 | 0.999982 | 18.501544 |
1,544,578,501,398,275,000 | -0.243589 | -0.969863 | 0.005556 | 336,426.5089 | 0.969878 | -0.243577 | 0.00263 | 4,074,330.565 | -0.001197 | 0.006029 | 0.999981 | 18.501329 |
1,544,578,501,408,473,900 | -0.243449 | -0.969899 | 0.005378 | 336,426.4522 | 0.969913 | -0.243438 | 0.002573 | 4,074,330.79 | -0.001186 | 0.005843 | 0.999982 | 18.501095 |
1,544,578,501,418,685,400 | -0.243378 | -0.969917 | 0.005205 | 336,426.3957 | 0.969931 | -0.243368 | 0.002493 | 4,074,331.016 | -0.001151 | 0.005655 | 0.999983 | 18.500863 |
1,544,578,501,428,859,400 | -0.243265 | -0.969945 | 0.005306 | 336,426.3392 | 0.969959 | -0.243255 | 0.002463 | 4,074,331.241 | -0.001098 | 0.005746 | 0.999983 | 18.500639 |
1,544,578,501,439,070,700 | -0.243118 | -0.969982 | 0.005357 | 336,426.2827 | 0.969996 | -0.243109 | 0.002337 | 4,074,331.466 | -0.000964 | 0.005765 | 0.999983 | 18.500428 |
1,544,578,501,449,277,000 | -0.243038 | -0.970003 | 0.005228 | 336,426.2264 | 0.970016 | -0.243029 | 0.002256 | 4,074,331.692 | -0.000918 | 0.00562 | 0.999984 | 18.500248 |
1,544,578,501,459,466,500 | -0.242935 | -0.970029 | 0.00509 | 336,426.1701 | 0.970042 | -0.242926 | 0.00223 | 4,074,331.917 | -0.000927 | 0.00548 | 0.999985 | 18.500079 |
1,544,578,501,469,674,200 | -0.242797 | -0.970064 | 0.005123 | 336,426.1138 | 0.970077 | -0.242788 | 0.002328 | 4,074,332.142 | -0.001014 | 0.005535 | 0.999984 | 18.499908 |
1,544,578,501,479,878,100 | -0.242695 | -0.970088 | 0.005281 | 336,426.0576 | 0.970102 | -0.242684 | 0.002503 | 4,074,332.367 | -0.001147 | 0.005731 | 0.999983 | 18.499716 |
1,544,578,501,490,090,800 | -0.242549 | -0.970126 | 0.005134 | 336,426.0013 | 0.970138 | -0.242539 | 0.00259 | 4,074,332.593 | -0.001268 | 0.005609 | 0.999983 | 18.499491 |
1,544,578,501,500,273,200 | -0.24239 | -0.970166 | 0.005036 | 336,425.9451 | 0.970178 | -0.24238 | 0.002556 | 4,074,332.818 | -0.001259 | 0.005505 | 0.999984 | 18.49924 |
1,544,578,501,510,469,600 | -0.2423 | -0.970188 | 0.005132 | 336,425.8889 | 0.970201 | -0.242289 | 0.002585 | 4,074,333.044 | -0.001265 | 0.005605 | 0.999983 | 18.498991 |
1,544,578,501,520,661,200 | -0.242234 | -0.970206 | 0.004905 | 336,425.8329 | 0.970217 | -0.242224 | 0.002535 | 4,074,333.269 | -0.001272 | 0.005373 | 0.999985 | 18.498739 |
1,544,578,501,530,875,600 | -0.242133 | -0.970231 | 0.004829 | 336,425.7768 | 0.970242 | -0.242124 | 0.002481 | 4,074,333.495 | -0.001238 | 0.005286 | 0.999985 | 18.498492 |
1,544,578,501,541,084,400 | -0.241989 | -0.970266 | 0.004974 | 336,425.7207 | 0.970278 | -0.241978 | 0.002706 | 4,074,333.72 | -0.001422 | 0.005481 | 0.999984 | 18.498248 |
1,544,578,501,551,304,000 | -0.241861 | -0.970298 | 0.005016 | 336,425.6647 | 0.97031 | -0.241849 | 0.002918 | 4,074,333.946 | -0.001618 | 0.005573 | 0.999983 | 18.497958 |
1,544,578,501,561,475,800 | -0.241746 | -0.970327 | 0.004883 | 336,425.6088 | 0.970338 | -0.241734 | 0.002964 | 4,074,334.171 | -0.001695 | 0.005455 | 0.999984 | 18.497626 |
1,544,578,501,571,673,600 | -0.241615 | -0.97036 | 0.004869 | 336,425.5529 | 0.970371 | -0.241603 | 0.00302 | 4,074,334.397 | -0.001755 | 0.005454 | 0.999984 | 18.497273 |
1,544,578,501,581,875,500 | -0.241489 | -0.97039 | 0.00514 | 336,425.497 | 0.970402 | -0.241476 | 0.003051 | 4,074,334.622 | -0.00172 | 0.005725 | 0.999982 | 18.496912 |
1,544,578,501,592,078,600 | -0.241443 | -0.970401 | 0.005236 | 336,425.441 | 0.970414 | -0.24143 | 0.002979 | 4,074,334.848 | -0.001626 | 0.0058 | 0.999982 | 18.496565 |
1,544,578,501,602,270,700 | -0.241461 | -0.970398 | 0.005046 | 336,425.385 | 0.970409 | -0.241449 | 0.002827 | 4,074,335.073 | -0.001525 | 0.00558 | 0.999983 | 18.496243 |
1,544,578,501,612,471,600 | -0.241443 | -0.970402 | 0.00502 | 336,425.3291 | 0.970414 | -0.241432 | 0.002816 | 4,074,335.298 | -0.001521 | 0.005552 | 0.999983 | 18.495944 |
1,544,578,501,622,676,500 | -0.241303 | -0.970436 | 0.005197 | 336,425.2733 | 0.970448 | -0.241291 | 0.002936 | 4,074,335.523 | -0.001596 | 0.005752 | 0.999982 | 18.495643 |
1,544,578,501,632,870,400 | -0.241226 | -0.970455 | 0.005241 | 336,425.2175 | 0.970468 | -0.241213 | 0.003 | 4,074,335.748 | -0.001647 | 0.00581 | 0.999982 | 18.49532 |
1,544,578,501,643,073,300 | -0.241282 | -0.970441 | 0.005179 | 336,425.1618 | 0.970454 | -0.241269 | 0.002924 | 4,074,335.973 | -0.001588 | 0.005732 | 0.999982 | 18.494985 |
1,544,578,501,653,278,000 | -0.241221 | -0.970456 | 0.005248 | 336,425.1059 | 0.970469 | -0.241209 | 0.002828 | 4,074,336.198 | -0.001478 | 0.005776 | 0.999982 | 18.494665 |
1,544,578,501,663,485,000 | -0.241085 | -0.970489 | 0.005445 | 336,425.05 | 0.970503 | -0.241073 | 0.002765 | 4,074,336.423 | -0.00137 | 0.005951 | 0.999981 | 18.494368 |
1,544,578,501,673,683,500 | -0.241053 | -0.970496 | 0.005562 | 336,424.9941 | 0.970511 | -0.24104 | 0.002818 | 4,074,336.649 | -0.001394 | 0.006077 | 0.999981 | 18.494104 |
1,544,578,501,683,874,000 | -0.241043 | -0.9705 | 0.005374 | 336,424.9383 | 0.970513 | -0.241031 | 0.002858 | 4,074,336.874 | -0.001479 | 0.005904 | 0.999981 | 18.493819 |
1,544,578,501,694,094,600 | -0.241005 | -0.97051 | 0.00527 | 336,424.8825 | 0.970523 | -0.240993 | 0.002847 | 4,074,337.099 | -0.001493 | 0.0058 | 0.999982 | 18.493521 |
1,544,578,501,704,316,200 | -0.24095 | -0.970522 | 0.005426 | 336,424.8267 | 0.970536 | -0.240938 | 0.002792 | 4,074,337.324 | -0.001402 | 0.005939 | 0.999981 | 18.49321 |
1,544,578,501,714,508,300 | -0.240871 | -0.970541 | 0.005516 | 336,424.7709 | 0.970556 | -0.24086 | 0.002649 | 4,074,337.549 | -0.001242 | 0.005992 | 0.999981 | 18.49293 |
1,544,578,501,724,707,600 | -0.240851 | -0.970546 | 0.005632 | 336,424.7152 | 0.970562 | -0.240841 | 0.00245 | 4,074,337.774 | -0.001021 | 0.006056 | 0.999981 | 18.492677 |
1,544,578,501,734,889,500 | -0.240848 | -0.970546 | 0.005691 | 336,424.6594 | 0.970562 | -0.240838 | 0.00235 | 4,074,338 | -0.00091 | 0.00609 | 0.999981 | 18.492488 |
1,544,578,501,745,079,600 | -0.240791 | -0.970561 | 0.005626 | 336,424.6037 | 0.970577 | -0.240781 | 0.002354 | 4,074,338.225 | -0.00093 | 0.006028 | 0.999981 | 18.492315 |
1,544,578,501,755,284,000 | -0.240683 | -0.970587 | 0.005647 | 336,424.5479 | 0.970603 | -0.240673 | 0.002489 | 4,074,338.45 | -0.001057 | 0.00608 | 0.999981 | 18.49214 |
1,544,578,501,765,498,600 | -0.240577 | -0.970613 | 0.005743 | 336,424.492 | 0.970629 | -0.240566 | 0.002608 | 4,074,338.676 | -0.001149 | 0.006202 | 0.99998 | 18.491926 |
1,544,578,501,775,701,500 | -0.240561 | -0.970617 | 0.005793 | 336,424.4362 | 0.970634 | -0.24055 | 0.002484 | 4,074,338.902 | -0.001017 | 0.006221 | 0.99998 | 18.491688 |
1,544,578,501,785,881,900 | -0.240578 | -0.970613 | 0.005804 | 336,424.3806 | 0.97063 | -0.240569 | 0.002216 | 4,074,339.127 | -0.000755 | 0.006166 | 0.999981 | 18.491485 |
1,544,578,501,796,072,400 | -0.24051 | -0.97063 | 0.005725 | 336,424.3249 | 0.970647 | -0.240502 | 0.001961 | 4,074,339.352 | -0.000526 | 0.006028 | 0.999982 | 18.491345 |
1,544,578,501,806,291,500 | -0.240453 | -0.970643 | 0.005803 | 336,424.2693 | 0.970661 | -0.240446 | 0.001817 | 4,074,339.577 | -0.000368 | 0.006069 | 0.999982 | 18.491256 |
1,544,578,501,816,496,600 | -0.240443 | -0.970645 | 0.006002 | 336,424.2137 | 0.970663 | -0.240437 | 0.001831 | 4,074,339.802 | -0.000334 | 0.006266 | 0.99998 | 18.491205 |
1,544,578,501,826,677,800 | -0.240355 | -0.970666 | 0.005994 | 336,424.1581 | 0.970685 | -0.240348 | 0.001884 | 4,074,340.027 | -0.000388 | 0.006271 | 0.99998 | 18.491158 |
1,544,578,501,836,905,500 | -0.240275 | -0.970688 | 0.005745 | 336,424.1025 | 0.970705 | -0.240267 | 0.001994 | 4,074,340.252 | -0.000556 | 0.006056 | 0.999982 | 18.491098 |
1,544,578,501,847,101,700 | -0.240257 | -0.970693 | 0.005636 | 336,424.0467 | 0.970709 | -0.240249 | 0.00211 | 4,074,340.478 | -0.000694 | 0.005978 | 0.999982 | 18.490995 |
1,544,578,501,857,329,000 | -0.240231 | -0.970699 | 0.005646 | 336,423.9909 | 0.970716 | -0.240223 | 0.002034 | 4,074,340.704 | -0.000618 | 0.005969 | 0.999982 | 18.490856 |
1,544,578,501,867,510,300 | -0.240152 | -0.970718 | 0.005728 | 336,423.9353 | 0.970735 | -0.240145 | 0.001824 | 4,074,340.929 | -0.000395 | 0.005999 | 0.999982 | 18.490736 |
1,544,578,501,877,715,700 | -0.240111 | -0.97073 | 0.005463 | 336,423.8797 | 0.970745 | -0.240106 | 0.001584 | 4,074,341.155 | -0.000226 | 0.005684 | 0.999984 | 18.49067 |
1,544,578,501,887,913,700 | -0.240117 | -0.970729 | 0.005391 | 336,423.8241 | 0.970744 | -0.240112 | 0.001551 | 4,074,341.38 | -0.000212 | 0.005606 | 0.999984 | 18.490643 |
1,544,578,501,898,088,700 | -0.240076 | -0.97074 | 0.005296 | 336,423.7685 | 0.970754 | -0.240072 | 0.001366 | 4,074,341.605 | -0.000055 | 0.005469 | 0.999985 | 18.490614 |
1,544,578,501,908,279,600 | -0.239989 | -0.970761 | 0.005402 | 336,423.7129 | 0.970776 | -0.239984 | 0.001549 | 4,074,341.83 | -0.000207 | 0.005616 | 0.999984 | 18.490625 |
1,544,578,501,918,497,300 | -0.239939 | -0.970775 | 0.00504 | 336,423.6574 | 0.970788 | -0.239935 | 0.001545 | 4,074,342.055 | -0.000291 | 0.005263 | 0.999986 | 18.490602 |
1,544,578,501,928,704,300 | -0.239873 | -0.970791 | 0.005127 | 336,423.6019 | 0.970804 | -0.239867 | 0.001709 | 4,074,342.28 | -0.000429 | 0.005387 | 0.999985 | 18.49056 |
1,544,578,501,938,892,500 | -0.239884 | -0.970789 | 0.004911 | 336,423.5462 | 0.970802 | -0.239879 | 0.001465 | 4,074,342.507 | -0.000245 | 0.005119 | 0.999987 | 18.490485 |
End of preview.
KAIST Complex Urban Dataset — Converted ROS Bags
This repository mirrors ROS bag conversions of the KAIST Complex Urban Dataset,
covering sequences urban18 through urban39. Each sequence includes:
urbanXX.bag— ROS bag with the full multi-sensor recording (camera, LiDAR, IMU, GPS, wheel encoders)urbanXX.csv— ground truth trajectoryurbanXX.txt— ground truth converted to TUM/text format (viakaist_gt_csv2txt.m)
Origin
The underlying sensor data was collected and originally released by the authors of the Complex Urban Dataset:
Jeong, J., Cho, Y., Shin, Y.S., Roh, H. and Kim, A., 2019. Complex urban dataset with multi-level sensors from highly diverse urban environments. The International Journal of Robotics Research, 38(6), pp.642-657.
Original dataset page: https://sites.google.com/view/complex-urban-dataset
All rights to the raw sensor data remain with the original KAIST authors. Please cite their paper if you use this data.
Conversion / recombination
The raw KAIST sensor readings were converted into ROS bag format (using kaist2bag) by Woosik Lee as part of the MINS (Multisensor-aided Inertial Navigation System) project, where these sequences are used as a real-world multi-sensor benchmark:
Lee, W., Geneva, P., Chen, C. and Huang, G., 2025. MINS: Efficient and Robust Multisensor‐Aided Inertial Navigation System. Journal of Field Robotics, 42(7), pp.3252-3284.
MINS project: https://github.com/rpng/MINS
These converted bags were previously distributed via Google Drive, linked from the MINS README. After the original storage policy change broke those links, this Hugging Face repository (along with a NAS mirror) was set up as the replacement — see rpng/MINS#63.
If you use this data, please cite both papers above.
Reassembling split files
urban38.bag and urban28.bag exceeded Hugging Face's 50GB per-file limit, so they were
split in half:
cat urban38.bag.part_00 urban38.bag.part_01 > urban38.bag
cat urban28.bag.part_00 urban28.bag.part_01 > urban28.bag
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