Dataset Preview
Duplicate
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 2 new columns ({'drift_raw_deg', 'drift_deg'}) and 6 missing columns ({'vo_z', 'vo_x', 'vo_y', 'imu_x', 'imu_y', 'imu_z'}).

This happened while the csv dataset builder was generating data using

hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work/drift_curve.csv (at revision 79d2ca01583237875788266ac07cbc2a90081e85), ['hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/accel_series.csv', 'hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/drift_curve.csv', 'hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/steps_all.csv', 'hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/summary_by_clip.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 1856, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 811, 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 822, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              clip: string
              t_s: double
              drift_raw_deg: double
              drift_deg: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 741
              to
              {'clip': Value('string'), 't_s': Value('float64'), 'imu_x': Value('float64'), 'imu_y': Value('float64'), 'imu_z': Value('float64'), 'vo_x': Value('float64'), 'vo_y': Value('float64'), 'vo_z': 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 1379, 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 956, 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 1702, 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 1858, 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 2 new columns ({'drift_raw_deg', 'drift_deg'}) and 6 missing columns ({'vo_z', 'vo_x', 'vo_y', 'imu_x', 'imu_y', 'imu_z'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work/drift_curve.csv (at revision 79d2ca01583237875788266ac07cbc2a90081e85), ['hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/accel_series.csv', 'hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/drift_curve.csv', 'hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/steps_all.csv', 'hf://datasets/origin-data-lab/stereo-visual-odometry-head-pose-imu-validation-real-work@79d2ca01583237875788266ac07cbc2a90081e85/summary_by_clip.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.

clip
string
t_s
float64
imu_x
float64
imu_y
float64
imu_z
float64
vo_x
float64
vo_y
float64
vo_z
float64
A
4.0669
0.1348
-0.1984
0.1529
0.1294
-0.16
0.1536
A
4.1333
-0.2043
-0.1314
0.2098
-0.193
-0.1312
0.2147
A
4.2004
-0.5872
-0.0587
0.0708
-0.5589
-0.0781
0.0824
A
4.2669
-0.9873
0.0062
-0.0937
-0.9398
0.0134
-0.0975
A
4.3333
-1.2439
0.1963
-0.1153
-1.1799
0.1911
-0.1387
A
4.3999
-1.2318
0.2874
-0.0468
-1.1902
0.2827
-0.1015
A
4.4669
-1.1097
0.247
-0.031
-1.0842
0.2445
-0.0855
A
4.5338
-0.965
0.1163
-0.049
-0.9304
0.1226
-0.0902
A
4.5999
-0.718
-0.0395
-0.1462
-0.702
0.0111
-0.1966
A
4.6671
-0.4331
-0.0755
-0.0955
-0.4266
0.0086
-0.1512
A
4.7333
-0.1631
-0.1096
-0.0639
-0.1625
-0.0368
-0.113
A
4.8007
0.0462
-0.217
-0.1813
0.0396
-0.1344
-0.2037
A
4.8666
0.229
-0.2489
-0.2165
0.2279
-0.1914
-0.2096
A
4.9338
0.3366
-0.2623
-0.2374
0.3368
-0.1978
-0.231
A
5.0001
0.3136
-0.1428
-0.1644
0.3286
-0.1022
-0.1577
A
5.0666
0.2463
-0.0475
-0.2089
0.2918
-0.0427
-0.1869
A
5.1336
0.2153
0.0168
-0.2546
0.2321
0.0598
-0.261
A
5.2001
0.1301
0.1924
-0.2084
0.1383
0.1937
-0.2097
A
5.2666
0.1245
0.3808
-0.0845
0.127
0.3596
-0.0936
A
5.3333
0.186
0.3339
-0.04
0.1706
0.3262
-0.0506
A
5.3999
0.1734
0.2726
-0.0478
0.1685
0.2672
-0.0536
A
5.4676
0.1294
0.1935
-0.0472
0.1278
0.1945
-0.0367
A
5.5334
0.1001
0.1217
-0.0407
0.1062
0.1364
-0.0487
A
5.5999
0.1516
0.0434
0.0339
0.14
0.0736
0.029
A
5.6671
0.2183
-0.0173
0.0818
0.2307
-0.0431
0.1007
A
5.7332
0.2761
-0.0961
0.0236
0.2692
-0.1057
0.0586
A
5.7999
0.3092
-0.0096
0.0737
0.3132
-0.0425
0.1028
A
5.8668
0.3169
0.0471
0.0883
0.314
0.0129
0.1137
A
5.9334
0.2887
0.0629
0.0881
0.2746
0.0458
0.0818
A
6.0003
0.2543
0.0744
0.0541
0.2586
0.0481
0.0569
A
6.0666
0.2574
0.0906
0.0995
0.2318
0.0895
0.072
A
6.1336
0.1642
0.0811
0.0649
0.1508
0.0689
0.0505
A
6.1999
0.0774
0.057
0.0285
0.068
0.0598
0.003
A
6.2666
-0.018
0.051
-0.0168
-0.0336
0.069
-0.0533
A
6.3332
-0.1252
0.0722
-0.041
-0.126
0.0855
-0.0738
A
6.3999
-0.2149
0.0483
-0.0595
-0.204
0.0618
-0.0844
A
6.4669
-0.2709
0.0145
-0.0782
-0.2463
0.024
-0.1067
A
6.5333
-0.3009
0.0226
-0.0713
-0.2839
0.0373
-0.0949
A
6.5999
-0.2812
0.0505
-0.0188
-0.2545
0.0464
-0.0344
A
6.6666
-0.2483
0.0212
-0.0483
-0.2435
0.0339
-0.0507
A
6.7332
-0.222
0.0053
-0.0641
-0.2062
0.015
-0.0659
A
6.8001
-0.1638
-0.0126
-0.0532
-0.1607
-0.0072
-0.0398
A
6.8666
-0.1202
-0.0559
-0.0545
-0.1216
-0.0424
-0.0562
A
6.9332
-0.0949
-0.06
-0.0625
-0.0823
-0.0663
-0.0342
A
6.9999
-0.0526
-0.0543
-0.0241
-0.0553
-0.0557
-0.0113
A
7.0666
-0.0387
-0.0317
-0.0129
-0.0477
-0.0292
-0.0027
A
7.1332
-0.027
0.0091
0.0128
-0.033
0.0003
0.0275
A
7.2002
0.0144
0.0272
0.0149
0.0054
0.0051
0.0298
A
7.2669
0.0428
0.0345
0.0068
0.0421
0.002
0.0314
A
7.3334
0.0526
0.0613
0.019
0.0451
0.0289
0.0352
A
7.3999
0.0297
0.0932
0.0105
0.0342
0.0551
0.0283
A
7.4666
0.0202
0.1081
0.0147
0.0174
0.0809
0.0226
A
7.5332
0.0361
0.0916
0.0173
0.0322
0.0714
0.0316
A
7.5999
0.0319
0.0615
0.0055
0.0294
0.0531
0.0139
A
7.6671
0.0101
0.0158
-0.0311
0.0177
0.0028
-0.0145
A
7.7332
0.0184
-0.018
-0.027
0.0227
-0.019
-0.0187
A
7.7999
0.0255
-0.0451
-0.0236
0.023
-0.0263
-0.0363
A
7.8666
0.0369
-0.0621
-0.0151
0.0303
-0.0437
-0.0205
A
7.9332
0.0416
-0.0634
0.0002
0.0418
-0.0493
-0.0065
A
8
0.044
-0.0469
0.0161
0.0365
-0.0375
0.0077
A
8.067
0.0461
-0.0326
0.0271
0.0344
-0.0187
0.0134
A
8.1336
0.0485
-0.0369
0.0238
0.0432
-0.0253
0.0138
A
8.1999
0.051
-0.0525
0.0085
0.0407
-0.0445
0.0057
A
8.2666
0.0333
-0.036
0.0033
0.0295
-0.0325
-0.0051
A
8.3338
0.0276
-0.0176
0.0018
0.0258
-0.0259
0.0077
A
8.4001
0.0199
-0.0101
-0.0008
0.0205
-0.0128
0.0046
A
8.467
0.0129
0
-0.0049
0.023
-0.0116
0.0096
A
8.5332
0.0011
0.0109
-0.0011
0.009
-0.0024
0.0095
A
8.5999
-0.0007
0.0071
-0.0177
0.0075
-0.0157
0.0135
A
8.6666
-0.0009
0.0093
-0.0113
0.0066
-0.0008
-0.001
A
8.7332
0.0004
0.0023
-0.011
0.0105
-0.0067
-0.0024
A
8.7999
-0.0044
0.0032
-0.0075
0.0055
-0.0188
0.0171
A
8.8665
-0.016
0.0047
-0.0089
-0.0053
-0.0126
0.0132
A
8.9333
-0.017
0.0059
-0.005
-0.0135
0.0012
-0.0063
A
8.9999
-0.0206
-0.0127
-0.0218
-0.024
-0.0092
-0.0282
A
9.0665
-0.0093
-0.0331
-0.0404
-0.0096
-0.0268
-0.0386
A
9.1332
-0.0033
-0.0335
-0.0361
-0.0066
-0.0335
-0.0372
A
9.1999
-0.0007
-0.0175
-0.024
-0.0011
-0.019
-0.026
A
9.2666
0.0173
-0.0091
-0.0064
0.0038
-0.005
-0.0107
A
9.3332
0.0096
-0.0006
0.0058
0.0033
0.008
-0.0017
A
9.3999
0.0001
0.0008
-0.0028
-0.0013
0.0047
0.0035
A
9.4665
-0.0153
0.0186
0.0048
-0.0194
0.0209
0.0023
A
9.5332
-0.0122
0.0246
0.017
-0.0171
0.0233
0.0274
A
9.6
-0.0164
0.0282
0.0281
-0.0142
0.0336
0.02
A
9.6665
-0.0223
0.0292
0.0419
-0.0128
0.0248
0.0489
A
9.7332
-0.0293
0.0197
0.0387
-0.0206
0.0173
0.0419
A
9.7999
-0.03
0.0079
0.036
-0.0275
0.014
0.0295
A
9.8673
-0.0188
-0.0047
0.0375
-0.0128
0.0054
0.0214
A
9.9332
-0.0143
-0.0285
0.0216
-0.0132
-0.025
0.0149
A
9.9999
-0.0029
-0.039
0.0096
-0.0027
-0.0245
-0.0013
A
10.0672
-0.0004
-0.0273
0.0233
0.0009
-0.0192
0.0117
A
10.1338
0.0123
-0.0192
0.026
0.008
-0.0172
0.0182
A
10.1999
0.0236
-0.0202
0.0263
0.0119
-0.007
0.0129
A
10.2665
0.0172
-0.0219
0.0112
0.0134
-0.016
0.007
A
10.3332
0.0084
-0.0152
0.0001
0.0046
-0.0025
-0.0053
A
10.3999
-0.0003
-0.0111
-0.0071
-0.0035
0.0061
-0.0205
A
10.4666
0.0028
-0.0126
-0.0057
-0.0036
0.0029
-0.0148
A
10.5333
-0.0028
-0.0064
0.0007
-0.0083
0.0068
-0.0136
A
10.6002
-0.0116
-0.0034
-0.0015
-0.0095
-0.0014
-0.0064
A
10.6665
-0.0186
-0.0044
-0.006
-0.016
0.0108
-0.0259
End of preview.

Origin Data Lab · Technical Field Note #21

ODL Stereo VO Checked With IMU

GitHub Hugging Face Kaggle Technical Note

English technical note | Korean technical note


ODL stereo visual odometry, checked with the IMU

Per-step rotation (vision vs gyroscope, 2694 steps), accumulated drift and acceleration (vision vs accelerometer) for 180 s of real produce-portioning work, three clips.

Limits / licence

One rig, one worker, three 60 s clips. Translation checked at 0.25–2 Hz only. Licence: Creative Commons Attribution 4.0 International (CC BY 4.0) for derived data and figures; MIT for code. No images or personal data.

About Origin Data Lab

Origin Data Lab (origindatalab.io, OriginDataLab Co., Ltd.) is a real-world data collection company based in Yangyang, Gangwon State, South Korea. We plan and run egocentric, stereo+IMU and field video capture for physical AI and robotics teams, with documented QA such as the measurements in this dataset. Not affiliated with "Origin Lab" (game data) or "OriginLab" (Origin/OriginPro software).

Visual evidence

Figures are taken from the released technical-note package. Interpret with the original methods and limitations.

Figure 1

Time series of camera acceleration from the accelerometer and from the stereo positions following each other, and a scatter plot of the two clustered along the equality line

Left: acceleration on the axis with the most motion in clip A, both band-passed the same way. Right: all filtered samples, three axes, three clips; the line marks equality.

Figure 2

Three curves of accumulated orientation difference rising over 60 seconds

Accumulated orientation difference between vision and the integrated gyroscope from the start of each clip; solid: gyroscope bias from Field Note #14 removed, dashed: raw gyroscope.

Figure 3

Time series of per-step head rotation from the gyroscope and from stereo vision lying on top of each other, and a histogram of their difference with a median near 0.05 degrees

Left: rotation per 67 ms step in clip A, gyroscope (solid) and stereo vision (dashed). Right: vision − gyroscope difference for every solved step, three clips.

Figure 4

Head path drawn as a blue line through a sparse coloured point cloud of the work area, with camera frustums along the path

Clip A, first 36 s: head path and a sparse stereo point cloud (one keyframe per second), gravity-aligned with the accelerometer.


Explore Origin Data Lab

GitHub Hugging Face Kaggle Technical Note

Official Website | Technical Field Notes | English Note | Korean Note

GitHub | Hugging Face | Kaggle Dataset | Kaggle Notebook

Downloads last month
65