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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 10 new columns ({'0.5', '0.1', '0.4', '0.2', '0.7', '0.8', '0.3', '0', '0.6', '0.9'}) and 10 missing columns ({'__index_level_5__', '__index_level_9__', '__index_level_2__', '__index_level_6__', '__index_level_3__', '__index_level_0__', '__index_level_7__', '__index_level_1__', '__index_level_4__', '__index_level_8__'}).
This happened while the csv dataset builder was generating data using
zip://1_Indoor/2018-05-30-11-15-17_exp1_groundtruth_addedtest.csv::/tmp/hf-datasets-cache/medium/datasets/65353969643345-config-parquet-and-info-Alouka-UWB_IMU_GT_QDrone_-32f1ca06/hub/datasets--Alouka--UWB_IMU_GT_QDrone_Benchmark_Dataset/snapshots/364e35b22d08f595d9658af4c1d06f6dfba77bee/All Datasets/indoor.zip
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 "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
2: double
0: double
0.1: double
0.2: double
0.3: double
0.4: double
0.5: double
0.6: double
0.7: double
0.8: double
0.9: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1432
to
{'2': Value(dtype='float64', id=None), '__index_level_0__': Value(dtype='float64', id=None), '__index_level_1__': Value(dtype='float64', id=None), '__index_level_2__': Value(dtype='float64', id=None), '__index_level_3__': Value(dtype='float64', id=None), '__index_level_4__': Value(dtype='float64', id=None), '__index_level_5__': Value(dtype='float64', id=None), '__index_level_6__': Value(dtype='float64', id=None), '__index_level_7__': Value(dtype='float64', id=None), '__index_level_8__': Value(dtype='float64', id=None), '__index_level_9__': Value(dtype='float64', id=None)}
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 1417, 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 1049, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
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 10 new columns ({'0.5', '0.1', '0.4', '0.2', '0.7', '0.8', '0.3', '0', '0.6', '0.9'}) and 10 missing columns ({'__index_level_5__', '__index_level_9__', '__index_level_2__', '__index_level_6__', '__index_level_3__', '__index_level_0__', '__index_level_7__', '__index_level_1__', '__index_level_4__', '__index_level_8__'}).
This happened while the csv dataset builder was generating data using
zip://1_Indoor/2018-05-30-11-15-17_exp1_groundtruth_addedtest.csv::/tmp/hf-datasets-cache/medium/datasets/65353969643345-config-parquet-and-info-Alouka-UWB_IMU_GT_QDrone_-32f1ca06/hub/datasets--Alouka--UWB_IMU_GT_QDrone_Benchmark_Dataset/snapshots/364e35b22d08f595d9658af4c1d06f6dfba77bee/All Datasets/indoor.zip
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.
2
float64 | __index_level_0__
float64 | __index_level_1__
float64 | __index_level_2__
float64 | __index_level_3__
float64 | __index_level_4__
float64 | __index_level_5__
float64 | __index_level_6__
float64 | __index_level_7__
float64 | __index_level_8__
float64 | __index_level_9__
float64 |
|---|---|---|---|---|---|---|---|---|---|---|
0.235189 | 0 | 0.000852 | -0.003245 | -0.000796 | -0.03244 | 0.09847 | 9.760156 | -0.001091 | 0.004993 | 0.971936 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235172 | 0.012915 | 0.001058 | -0.002524 | 0.000681 | -0.040358 | 0.086003 | 9.755304 | -0.001086 | 0.004998 | 0.97194 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235156 | 0.019967 | 0.002387 | -0.002337 | 0.000063 | -0.04277 | 0.081353 | 9.749039 | -0.001083 | 0.005006 | 0.971944 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235136 | 0.032896 | 0.001896 | -0.001761 | -0.002713 | -0.05141 | 0.078849 | 9.743692 | -0.001081 | 0.00502 | 0.971949 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235128 | 0.040001 | 0.000479 | -0.001731 | -0.005361 | -0.055495 | 0.081809 | 9.738906 | -0.001081 | 0.005032 | 0.971951 |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0.048069 | 100 | 11.949 | 0.056 | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235134 | 0.052979 | 0.000584 | -0.001989 | -0.007528 | -0.056606 | 0.087282 | 9.733091 | -0.001083 | 0.005038 | 0.971949 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235156 | 0.059966 | 0.000432 | -0.001635 | -0.00984 | -0.051793 | 0.091874 | 9.734534 | -0.001085 | 0.005044 | 0.971944 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235182 | 0.073236 | -0.00018 | -0.001805 | -0.009464 | -0.045423 | 0.098676 | 9.729981 | -0.001088 | 0.005049 | 0.971938 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235207 | 0.080001 | -0.000018 | -0.002715 | -0.008083 | -0.042714 | 0.098013 | 9.718899 | -0.001091 | 0.005052 | 0.971932 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235233 | 0.092905 | 0.000103 | -0.002444 | -0.004483 | -0.040242 | 0.099118 | 9.722691 | -0.00109 | 0.005054 | 0.971925 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0.093554 | 103 | 13.7 | 0.056 | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235235 | 0.099978 | -0.000027 | -0.001808 | -0.002204 | -0.04612 | 0.089273 | 9.732219 | -0.00109 | 0.005057 | 0.971925 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235224 | 0.112984 | 0.000768 | -0.002479 | -0.000103 | -0.060389 | 0.075753 | 9.733202 | -0.001091 | 0.00506 | 0.971927 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0.116259 | 100 | 11.948 | 0.055 | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235205 | 0.120055 | 0.000787 | -0.002633 | -0.000177 | -0.07906 | 0.072251 | 9.720451 | -0.00109 | 0.005066 | 0.971932 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235191 | 0.132887 | 0.00105 | -0.002765 | -0.001514 | -0.093533 | 0.076658 | 9.71211 | -0.001087 | 0.005072 | 0.971935 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235178 | 0.139966 | 0.00149 | -0.002583 | -0.004829 | -0.098235 | 0.08166 | 9.703397 | -0.001084 | 0.00508 | 0.971938 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235181 | 0.152979 | 0.000903 | -0.001944 | -0.007762 | -0.096985 | 0.084674 | 9.702172 | -0.001081 | 0.005089 | 0.971938 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235202 | 0.160007 | 0.001026 | -0.002482 | -0.009528 | -0.090181 | 0.088332 | 9.698644 | -0.001082 | 0.005095 | 0.971933 |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0.161553 | 103 | 13.7 | 0.055 | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235226 | 0.173163 | 0.002661 | -0.001829 | -0.007518 | -0.077858 | 0.091804 | 9.697092 | -0.001081 | 0.005103 | 0.971927 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0.182564 | 100 | 11.949 | 0.055 | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235243 | 0.180002 | 0.002156 | -0.001512 | -0.005334 | -0.068825 | 0.097817 | 9.709622 | -0.001081 | 0.005117 | 0.971923 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235254 | 0.192902 | 0.000579 | -0.002088 | -0.002879 | -0.062407 | 0.105207 | 9.717457 | -0.001083 | 0.00513 | 0.97192 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235247 | 0.199988 | -0.000325 | -0.002613 | -0.000148 | -0.057883 | 0.105315 | 9.721257 | -0.001083 | 0.005135 | 0.971921 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235227 | 0.213005 | -0.000705 | -0.002983 | 0.001762 | -0.046281 | 0.101191 | 9.720468 | -0.001083 | 0.005135 | 0.971926 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235198 | 0.22001 | -0.000722 | -0.002992 | 0.001304 | -0.039781 | 0.100155 | 9.721073 | -0.001081 | 0.005133 | 0.971933 |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 0.22794 | 103 | 13.699 | 0.056 | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235175 | 0.23293 | -0.000279 | -0.002514 | -0.001158 | -0.041525 | 0.090326 | 9.72714 | -0.001079 | 0.00513 | 0.971939 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.23516 | 0.239977 | 0.000309 | -0.001967 | -0.00482 | -0.046247 | 0.084694 | 9.741055 | -0.001079 | 0.005131 | 0.971942 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235163 | 0.252929 | 0.001138 | -0.00185 | -0.008619 | -0.058117 | 0.078544 | 9.757121 | -0.001081 | 0.005135 | 0.971942 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235188 | 0.259967 | 0.000643 | -0.002642 | -0.008976 | -0.062829 | 0.072426 | 9.756265 | -0.001082 | 0.005142 | 0.971936 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235209 | 0.274436 | 0.000559 | -0.002536 | -0.006528 | -0.079333 | 0.072171 | 9.748212 | -0.001081 | 0.005146 | 0.971931 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235221 | 0.280573 | 0.000221 | -0.00213 | -0.004804 | -0.093238 | 0.071739 | 9.748838 | -0.00108 | 0.005151 | 0.971928 |
null | 2 | null | null | null | null | null | null | null | null | null |
0.235232 | 0.292902 | -0.00006 | -0.002489 | -0.002318 | -0.093098 | 0.068555 | 9.761446 | -0.00108 | 0.005154 | 0.971925 |
null | 3 | null | null | null | null | null | null | null | null | null |
null | 0 | null | null | null | null | null | null | null | null | null |
null | 2 | null | null | null | null | null | null | null | null | null |
End of preview.
license: mit
Q-Drone UWB Benchmark Dataset
Overview
We present a unique UWB benchmark dataset, called Q-Drone UWB benchmark. Q-Drone system, a UAV with UWB network built at York University, was used for acquiring this benchmark over five different sites, which include an indoor, open sports field, near to a building with glasses, semi-open tunnel and underneath bridge. The benchmark data were acquired by flying for a total of 1 h 50 min 28 sec flight time and about 4.3 km traveling distances with different maneuvering patterns and spatial configuration between UAV and UWB anchors as shown in the following table.
Environments and Locations
The data were collected from the following sites:
- Indoor: Indoor environment, 26m(w) x 33m(l), Oshawa, Ontario, Canada
- Field: Outdoor open sports field, 12m(w) x 13m(l), Uxbridge, Ontario, Canada
- Building: Near a glass building, 7m(w) x 7m(l), Newmarket, Ontario, Canada
- Bridge: Underneath a concrete-metal bridge, 10m(w) x 23m(l), Niagara, Ontario, Canada
- Tunnel: Under a metal bridge, 8m(w) x 30m(l), Oshawa, Ontario, Canada
Data Acquisition and Statistics
Overall Dataset Characteristics
| Site | Number of Datasets | Avg Data per Dataset | Flight Time (sec) | Travelled Distance (m) | Deployed UWB Anchors Area (m²) | UWB Range MAE (m) |
|---|---|---|---|---|---|---|
| Indoor | 5 | 62194 | 1687 | 1260.88 | 91.96 | 0.37 |
| Field | 5 | 92108 | 2313 | 1780.52 | 158.74 | 0.17 |
| Building | 3 | 34007 | 823 | 388.92 | 50.10 | 2.02 |
| Bridge | 4 | 26359 | 726 | 330.02 | 246.80 | 0.34 |
| Tunnel | 6 | 39164 | 1079 | 504.47 | 241.80 | 1.61 |
| Total | 23 | 253832 | 6628 | 4264.81 | 789.4 | 0.902 |
Detailed Individual Dataset Information
The specifics of data acquired per dataset include data points, IMU measurements, and precise coordinates of the UWB anchors for accurate localization.
Example Dataset Detail: Indoor
- UWB Anchors:
- UWB0 (0, 0, 0.62)
- UWB1 (8.51, 0, 0.96)
- UWB2 (-0.26, 10.77, 1.32)
- UWB3 (8.25, 10.84, 1.58)
- Datasets:
- Indoor 1: 10,127 data points, 267 sec duration, traveled 167.18m, x-min: 2.592m, x-max: 4.745m, y-min: 1.779m, y-max: 12.689m, z-max: 6.91m
- Indoor 2: 11,837 data points, 308 sec duration, traveled 210.075m, coordinates range: [-0.281, 13.082]m, z-max: 6.087m
- Indoor 3, 4, 5: Additional datasets with varying data points, duration, and spatial coordinates.
[Additional tables and dataset specifics continue similarly for each site.]
Conclusion
This comprehensive dataset aims to aid in the development of UWB technologies by providing diverse scenarios and extensive benchmark data for performance testing under different environmental conditions.
Citation: |
Please Cite Our Work: If you use this dataset for your research, we kindly ask you to cite the following paper:
@inproceedings{arjmandi2020uwb, title={Benchmark Dataset of Ultra-Wideband Radio Based UAV Positioning}, author={Arjmandi, Zahra and Kang, Jungwon and Park, Sohn Kunwoo and Gunho}, booktitle={IEEE International Conference on Intelligent Transportation Systems}, year={2020} }
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