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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', '0.3', '0.2', '0', '0.6', '0.9', '0.7', '0.1', '0.8', '0.4'}) and 10 missing columns ({'__index_level_9__', '__index_level_5__', '__index_level_1__', '__index_level_2__', '__index_level_8__', '__index_level_7__', '__index_level_0__', '__index_level_4__', '__index_level_3__', '__index_level_6__'}).
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/86430680366800-config-parquet-and-info-QDrone-UWB_IMU_GT_QDrone_-326a9221/hub/datasets--QDrone--UWB_IMU_GT_QDrone_Benchmark_Dataset/snapshots/cd3774c9db03899afde886a52f06687bbe4a1ed1/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', '0.3', '0.2', '0', '0.6', '0.9', '0.7', '0.1', '0.8', '0.4'}) and 10 missing columns ({'__index_level_9__', '__index_level_5__', '__index_level_1__', '__index_level_2__', '__index_level_8__', '__index_level_7__', '__index_level_0__', '__index_level_4__', '__index_level_3__', '__index_level_6__'}).
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/86430680366800-config-parquet-and-info-QDrone-UWB_IMU_GT_QDrone_-326a9221/hub/datasets--QDrone--UWB_IMU_GT_QDrone_Benchmark_Dataset/snapshots/cd3774c9db03899afde886a52f06687bbe4a1ed1/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.
For additional details, please visit our website: https://benchmark.qdrone.ausmlab.com.
Q-Drone UWB Benchmark Dataset
Overview
We present the Q-Drone UWB Benchmark, a unique dataset derived from experiments conducted using the Q-Drone system—a UAV equipped with a UWB network at York University. This dataset encompasses data from five different sites, including an indoor environment, an open sports field, an area near a glass building, a semi-open tunnel, and beneath a bridge. The benchmark data were collected over a total of 1 hour 50 minutes and 28 seconds of flight time, covering approximately 4.3 km with varying UAV maneuvers and spatial configurations between the UAV and UWB anchors.
Environments and Locations
The data were collected from the following sites:
- Indoor: 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
This section details the data acquired per dataset, including IMU measurements and precise coordinates of the UWB anchors for accurate localization.
UAV Platform
The UAV used is the DJI Matrice 100, a professional UAV capable of mounting up to 2.4 kg of payload. The payload consists of:
- UWB TIME DOMAIN™ P440 UWB tag
- Intel NUC computer
- Prism GRZ101, 360° mini prism
- External battery
UWB Anchor System
Developed by TIME DOMAIN, the P400 is an Ultra-Wideband (UWB) radio transceiver. For this experiment, we utilized five PulsON 440 (P440) modules from the P400 family. The UWB anchor setup includes four UWB tags mounted on tripods at varying heights, arranged in a square. Using the Time-of-Flight (TOF) method, it provides 2 cm accuracy distance measurements at up to 125 Hz rate, operable from above 40°C to below -85°C, suitable for high shock and high vibration environments.
Total Station
A robotic total station was used to ensure reliable data for validating positioning methods. The following instruments were used:
- Indoor, bridge, and tunnel datasets: Leica Nova MS60 MultiStation, measuring up to 1000m with 1” (0.00027°) angle accuracy.
- Outdoor datasets: Trimble VX Spatial Station, measuring up to 5,500 m with 4 mm accuracy and 0.4 sec measurement time.
Communication System
The flight platform of the DJI Matrice 100 can be customized via an onboard SDK. Connected devices include:
- Intel NUC computer: Connected via Micro-USB, managing communications with the flight controller and onboard sensors.
- UWB tag and prism: Provide real-time data including IMU feeds and spatial measurements.
Data Format
Data are available in csv format, and include the following types of data:
- IMU: Time(sec), angular velocity (x, y, z), linear acceleration (x, y, z), orientation quaternion (x, y, z, w), height value
- UWB: Time(sec), Module ID, Range
The data is provided raw, without calibration, within the UWB anchors' coordination system.
Structure of Dataset
UWB Data
- [row 1] 0
- [row 2] Time(sec), Module ID, Range, Self-range error
IMU Data
- [row 1] 2
- [row 2] Time(sec), angular velocity-x, angular velocity-y, angular velocity-z, linear acc-x, linear acc-y, linear acc-z, orientation quaternion-x, orientation quaternion-y, orientation quaternion-z, orientation quaternion-w
Height
- [row 1] 3
- [row 2] Height value
Citation
If you use this dataset in your research, please cite our 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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