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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 23 new columns ({'ph_lvel_z', 'ph_m', 'ph_lacc_y', 'ph_lvel_x', 'ph_grav_x', 'ph_6drr_cal_5', 'ph_grav_y', 'ph_s', 'ph_gyro_x', 'ph_dt', 'ph_6drr_cal_1', 'ph_lacc_x', 'ph_gyro_z', 'ph_6drr_cal_4', 'ph_grav_z', 'ph_6drr_cal_2', 'ph_h', 'ph_6drr_cal_3', 'ph_6drr_cal_6', 'ph_lacc_z', 'ph_gyro_y', 'ph_lvel_y', 'ph_ns'}) and 5 missing columns ({'ph_hips_yrot_cal_sin', 'ph_hips_yrot_cal_cos', 'gt_uarm_orig_cal_x', 'gt_uarm_orig_cal_z', 'gt_uarm_orig_cal_y'}).
This happened while the csv dataset builder was generating data using
hf://datasets/faweigend/wearmocap/WATCH_PHONE_UARM/01/01_phone_uarm_001.csv (at revision 47ab10bd614a88a539a43a03b6aa53288d956d76)
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
gt_hand_orig_cal_x: double
gt_hand_orig_cal_y: double
gt_hand_orig_cal_z: double
gt_larm_6drr_cal_1: double
gt_larm_6drr_cal_2: double
gt_larm_6drr_cal_3: double
gt_larm_6drr_cal_4: double
gt_larm_6drr_cal_5: double
gt_larm_6drr_cal_6: double
gt_larm_orig_cal_x: double
gt_larm_orig_cal_y: double
gt_larm_orig_cal_z: double
gt_uarm_6drr_cal_1: double
gt_uarm_6drr_cal_2: double
gt_uarm_6drr_cal_3: double
gt_uarm_6drr_cal_4: double
gt_uarm_6drr_cal_5: double
gt_uarm_6drr_cal_6: double
gt_hips_yrot_cal_sin: double
gt_hips_yrot_cal_cos: double
sw_dt: double
sw_h: double
sw_m: double
sw_s: double
sw_ns: double
sw_gyro_x: double
sw_gyro_y: double
sw_gyro_z: double
sw_lvel_x: double
sw_lvel_y: double
sw_lvel_z: double
sw_lacc_x: double
sw_lacc_y: double
sw_lacc_z: double
sw_grav_x: double
sw_grav_y: double
sw_grav_z: double
sw_6drr_cal_1: double
sw_6drr_cal_2: double
sw_6drr_cal_3: double
sw_6drr_cal_4: double
sw_6drr_cal_5: double
sw_6drr_cal_6: double
sw_pres_cal: double
ph_dt: double
ph_h: double
ph_m: double
ph_s: double
ph_ns: double
ph_gyro_x: double
ph_gyro_y: double
ph_gyro_z: double
ph_lvel_x: double
ph_lvel_y: double
ph_lvel_z: double
ph_lacc_x: double
ph_lacc_y: double
ph_lacc_z: double
ph_grav_x: double
ph_grav_y: double
ph_grav_z: double
ph_6drr_cal_1: double
ph_6drr_cal_2: double
ph_6drr_cal_3: double
ph_6drr_cal_4: double
ph_6drr_cal_5: double
ph_6drr_cal_6: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 8612
to
{'gt_hand_orig_cal_x': Value(dtype='float64', id=None), 'gt_hand_orig_cal_y': Value(dtype='float64', id=None), 'gt_hand_orig_cal_z': Value(dtype='float64', id=None), 'gt_larm_6drr_cal_1': Value(dtype='float64', id=None), 'gt_larm_6drr_cal_2': Value(dtype='float64', id=None), 'gt_larm_6drr_cal_3': Value(dtype='float64', id=None), 'gt_larm_6drr_cal_4': Value(dtype='float64', id=None), 'gt_larm_6drr_cal_5': Value(dtype='float64', id=None), 'gt_larm_6drr_cal_6': Value(dtype='float64', id=None), 'gt_larm_orig_cal_x': Value(dtype='float64', id=None), 'gt_larm_orig_cal_y': Value(dtype='float64', id=None), 'gt_larm_orig_cal_z': Value(dtype='float64', id=None), 'gt_uarm_6drr_cal_1': Value(dtype='float64', id=None), 'gt_uarm_6drr_cal_2': Value(dtype='float64', id=None), 'gt_uarm_6drr_cal_3': Value(dtype='float64', id=None), 'gt_uarm_6drr_cal_4': Value(dtype='float64', id=None), 'gt_uarm_6drr_cal_5': Value(dtype='float64', id=None), 'gt_uarm_6drr_cal_6': Value(dtype='float64', id=None), 'gt_uarm_orig_cal_x': Value(dtype='float64', id=None), 'gt_uarm_orig_cal_y': Value(dtype='float64', id=None), 'gt_uarm_orig_cal_z': Value(dtype='float64', id=None), 'gt_hips_yrot_cal_sin': Value(dtype='float64', id=None), 'gt_hips_yrot_cal_cos': Value(dtype='float64', id=None), 'sw_dt': Value(dtype='float64', id=None), 'sw_h': Value(dtype='float64', id=None), 'sw_m': Value(dtype='float64', id=None), 'sw_s': Value(dtype='float64', id=None), 'sw_ns': Value(dtype='float64', id=None), 'sw_gyro_x': Value(dtype='float64', id=None), 'sw_gyro_y': Value(dtype='float64', id=None), 'sw_gyro_z': Value(dtype='float64', id=None), 'sw_lvel_x': Value(dtype='float64', id=None), 'sw_lvel_y': Value(dtype='float64', id=None), 'sw_lvel_z': Value(dtype='float64', id=None), 'sw_lacc_x': Value(dtype='float64', id=None), 'sw_lacc_y': Value(dtype='float64', id=None), 'sw_lacc_z': Value(dtype='float64', id=None), 'sw_grav_x': Value(dtype='float64', id=None), 'sw_grav_y': Value(dtype='float64', id=None), 'sw_grav_z': Value(dtype='float64', id=None), 'sw_6drr_cal_1': Value(dtype='float64', id=None), 'sw_6drr_cal_2': Value(dtype='float64', id=None), 'sw_6drr_cal_3': Value(dtype='float64', id=None), 'sw_6drr_cal_4': Value(dtype='float64', id=None), 'sw_6drr_cal_5': Value(dtype='float64', id=None), 'sw_6drr_cal_6': Value(dtype='float64', id=None), 'sw_pres_cal': Value(dtype='float64', id=None), 'ph_hips_yrot_cal_sin': Value(dtype='float64', id=None), 'ph_hips_yrot_cal_cos': 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 23 new columns ({'ph_lvel_z', 'ph_m', 'ph_lacc_y', 'ph_lvel_x', 'ph_grav_x', 'ph_6drr_cal_5', 'ph_grav_y', 'ph_s', 'ph_gyro_x', 'ph_dt', 'ph_6drr_cal_1', 'ph_lacc_x', 'ph_gyro_z', 'ph_6drr_cal_4', 'ph_grav_z', 'ph_6drr_cal_2', 'ph_h', 'ph_6drr_cal_3', 'ph_6drr_cal_6', 'ph_lacc_z', 'ph_gyro_y', 'ph_lvel_y', 'ph_ns'}) and 5 missing columns ({'ph_hips_yrot_cal_sin', 'ph_hips_yrot_cal_cos', 'gt_uarm_orig_cal_x', 'gt_uarm_orig_cal_z', 'gt_uarm_orig_cal_y'}).
This happened while the csv dataset builder was generating data using
hf://datasets/faweigend/wearmocap/WATCH_PHONE_UARM/01/01_phone_uarm_001.csv (at revision 47ab10bd614a88a539a43a03b6aa53288d956d76)
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.
gt_hand_orig_cal_x
float64 | gt_hand_orig_cal_y
float64 | gt_hand_orig_cal_z
float64 | gt_larm_6drr_cal_1
float64 | gt_larm_6drr_cal_2
float64 | gt_larm_6drr_cal_3
float64 | gt_larm_6drr_cal_4
float64 | gt_larm_6drr_cal_5
float64 | gt_larm_6drr_cal_6
float64 | gt_larm_orig_cal_x
float64 | gt_larm_orig_cal_y
float64 | gt_larm_orig_cal_z
float64 | gt_uarm_6drr_cal_1
float64 | gt_uarm_6drr_cal_2
float64 | gt_uarm_6drr_cal_3
float64 | gt_uarm_6drr_cal_4
float64 | gt_uarm_6drr_cal_5
float64 | gt_uarm_6drr_cal_6
float64 | gt_uarm_orig_cal_x
float64 | gt_uarm_orig_cal_y
float64 | gt_uarm_orig_cal_z
float64 | gt_hips_yrot_cal_sin
float64 | gt_hips_yrot_cal_cos
float64 | sw_dt
float64 | sw_h
float64 | sw_m
float64 | sw_s
float64 | sw_ns
float64 | sw_gyro_x
float64 | sw_gyro_y
float64 | sw_gyro_z
float64 | sw_lvel_x
float64 | sw_lvel_y
float64 | sw_lvel_z
float64 | sw_lacc_x
float64 | sw_lacc_y
float64 | sw_lacc_z
float64 | sw_grav_x
float64 | sw_grav_y
float64 | sw_grav_z
float64 | sw_6drr_cal_1
float64 | sw_6drr_cal_2
float64 | sw_6drr_cal_3
float64 | sw_6drr_cal_4
float64 | sw_6drr_cal_5
float64 | sw_6drr_cal_6
float64 | sw_pres_cal
float64 | ph_hips_yrot_cal_sin
float64 | ph_hips_yrot_cal_cos
float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.032231
| 0.321967
| 0.237904
| -0.98628
| 0.12077
| 0.154085
| 0.918143
| -0.059244
| 0.377397
| -0.204074
| 0.358882
| 0.223705
| 0.182963
| -0.262193
| 0.200443
| 0.953485
| -0.962469
| 0.148729
| -0.156069
| 0.411472
| -0.028821
| 0
| 1
| 0.011
| 0
| 0
| 0
| 19,000,000
| -0.074526
| -0.037874
| -0.009774
| -0.00158
| 0.00187
| -0.001396
| -0.143652
| 0.169988
| -0.126893
| -0.936811
| 1.937557
| 9.567583
| 0.99525
| 0.096464
| -0.091955
| 0.975737
| 0.03196
| -0.196548
| -0.004459
| 0
| 1
|
0.032247
| 0.32205
| 0.237875
| -0.986314
| 0.120598
| 0.153838
| 0.918452
| -0.05932
| 0.376699
| -0.20403
| 0.358901
| 0.223661
| 0.183115
| -0.261824
| 0.200196
| 0.953617
| -0.962492
| 0.148538
| -0.155986
| 0.411427
| -0.028871
| 0
| 1
| 0.01
| 0
| 0
| 0
| 29,000,000
| -0.074526
| -0.037874
| -0.009774
| -0.001437
| 0.0017
| -0.001269
| -0.143652
| 0.169988
| -0.126893
| -0.936811
| 1.937557
| 9.567583
| 0.99525
| 0.096464
| -0.091955
| 0.975737
| 0.03196
| -0.196548
| -0.004459
| 0
| 1
|
0.032286
| 0.322158
| 0.237734
| -0.986347
| 0.120553
| 0.153723
| 0.918352
| -0.059064
| 0.376958
| -0.204026
| 0.358985
| 0.223579
| 0.182815
| -0.262311
| 0.200009
| 0.953519
| -0.962588
| 0.148307
| -0.15606
| 0.411462
| -0.028978
| 0
| 1
| 0.011
| 0
| 0
| 0
| 40,000,000
| -0.074526
| -0.037874
| -0.009774
| -0.00158
| 0.00187
| -0.001396
| -0.143652
| 0.169988
| -0.126893
| -0.936811
| 1.937557
| 9.567583
| 0.99525
| 0.096464
| -0.091955
| 0.975737
| 0.03196
| -0.196548
| -0.004459
| 0
| 1
|
0.032307
| 0.322363
| 0.237576
| -0.986493
| 0.119939
| 0.152989
| 0.918007
| -0.058535
| 0.377992
| -0.203999
| 0.359008
| 0.22355
| 0.182734
| -0.261925
| 0.19979
| 0.953641
| -0.962649
| 0.148201
| -0.156055
| 0.411428
| -0.029023
| 0
| 1
| 0.013
| 0
| 0
| 0
| 53,000,000
| -0.045204
| -0.039095
| -0.015883
| 0.000965
| 0.001774
| 0.000685
| 0.07422
| 0.13647
| 0.052672
| -0.919559
| 1.915404
| 9.573716
| 0.995327
| 0.095731
| -0.091375
| 0.976108
| 0.031227
| -0.195061
| -0.004459
| 0
| 1
|
0.03227
| 0.322468
| 0.237484
| -0.98659
| 0.119518
| 0.152389
| 0.918437
| -0.058461
| 0.377079
| -0.203985
| 0.358958
| 0.22348
| 0.18338
| -0.260797
| 0.1994
| 0.953992
| -0.962607
| 0.147933
| -0.155871
| 0.411275
| -0.029082
| 0
| 1
| 0.014
| 0
| 0
| 0
| 67,000,000
| -0.046426
| -0.0281
| -0.012217
| 0.001341
| 0.001341
| -0.001073
| 0.095768
| 0.095768
| -0.076614
| -0.91088
| 1.910755
| 9.575474
| 0.99539
| 0.095106
| -0.090814
| 0.976187
| 0.030857
| -0.194973
| -0.004459
| 0
| 1
|
0.032313
| 0.322551
| 0.237426
| -0.986669
| 0.119205
| 0.151949
| 0.918575
| -0.058275
| 0.376842
| -0.203959
| 0.358935
| 0.223466
| 0.183228
| -0.26099
| 0.199485
| 0.953928
| -0.962618
| 0.148007
| -0.155885
| 0.411275
| -0.029098
| 0
| 1
| 0.012
| 0
| 0
| 0
| 79,000,000
| -0.046426
| -0.024435
| -0.008552
| 0.000776
| 0.002557
| -0.000718
| 0.064643
| 0.213084
| -0.059855
| -0.907641
| 1.907681
| 9.576394
| 0.995419
| 0.094807
| -0.090529
| 0.976171
| 0.030745
| -0.195198
| -0.004459
| 0
| 1
|
0.03234
| 0.322653
| 0.237312
| -0.986763
| 0.118834
| 0.151368
| 0.919104
| -0.058195
| 0.375668
| -0.203954
| 0.358898
| 0.223371
| 0.183186
| -0.261143
| 0.199567
| 0.953878
| -0.962609
| 0.14806
| -0.15589
| 0.411258
| -0.029191
| 0
| 1
| 0.01
| 0
| 0
| 0
| 89,000,000
| -0.047647
| -0.024435
| -0.00733
| 0.00067
| 0.001077
| -0.00067
| 0.067038
| 0.107739
| -0.067038
| -0.903842
| 1.898678
| 9.578543
| 0.995448
| 0.094502
| -0.090229
| 0.976153
| 0.030677
| -0.195435
| -0.004459
| 0
| 1
|
0.032338
| 0.322633
| 0.237226
| -0.986727
| 0.119126
| 0.151666
| 0.918899
| -0.058023
| 0.376077
| -0.204165
| 0.358983
| 0.223314
| 0.183423
| -0.262662
| 0.199331
| 0.953561
| -0.962613
| 0.147408
| -0.156039
| 0.411282
| -0.029249
| 0
| 1
| 0.013
| 0
| 0
| 0
| 102,000,000
| -0.041539
| -0.025656
| -0.004887
| 0.000311
| 0.000622
| -0.000965
| 0.023942
| 0.047884
| -0.07422
| -0.904396
| 1.898513
| 9.578523
| 0.995476
| 0.094212
| -0.089943
| 0.976155
| 0.030612
| -0.195563
| -0.004459
| 0
| 1
|
0.03238
| 0.322493
| 0.237098
| -0.986718
| 0.119404
| 0.151817
| 0.919028
| -0.057779
| 0.375674
| -0.204144
| 0.358882
| 0.223243
| 0.183424
| -0.262225
| 0.199393
| 0.953656
| -0.9626
| 0.147573
| -0.156019
| 0.411197
| -0.029317
| 0
| 1
| 0.012
| 0
| 0
| 0
| 114,000,000
| -0.025656
| -0.025656
| -0.001222
| -0.000632
| -0.000747
| -0.000804
| -0.052672
| -0.062249
| -0.067038
| -0.89964
| 1.892339
| 9.580193
| 0.995499
| 0.093977
| -0.089718
| 0.976191
| 0.030546
| -0.1955
| 0.004541
| 0
| 1
|
0.032428
| 0.322447
| 0.237027
| -0.986736
| 0.119478
| 0.151807
| 0.918961
| -0.057505
| 0.375813
| -0.204114
| 0.358837
| 0.223236
| 0.183287
| -0.262112
| 0.199586
| 0.953648
| -0.962586
| 0.147824
| -0.156024
| 0.411203
| -0.029321
| 0
| 1
| 0.01
| 0
| 0
| 0
| 124,000,000
| -0.018326
| -0.0281
| 0.002443
| 0.000359
| 0.000359
| -0.000168
| 0.035913
| 0.035913
| -0.016759
| -0.898704
| 1.894854
| 9.579783
| 0.995527
| 0.093676
| -0.089422
| 0.976221
| 0.030496
| -0.195493
| 0.004541
| 0
| 1
|
0.032446
| 0.322408
| 0.236973
| -0.98675
| 0.119471
| 0.151769
| 0.918891
| -0.057371
| 0.375987
| -0.204099
| 0.358788
| 0.223215
| 0.183296
| -0.262105
| 0.199774
| 0.953622
| -0.962545
| 0.14801
| -0.156007
| 0.411203
| -0.02933
| 0
| 1
| 0.01
| 0
| 0
| 0
| 134,000,000
| -0.0281
| -0.032987
| 0.00733
| 0.000311
| 0.001221
| -0.000622
| 0.031125
| 0.122104
| -0.062249
| -0.895839
| 1.893742
| 9.580272
| 0.995548
| 0.093451
| -0.089188
| 0.976197
| 0.030505
| -0.195721
| 0.004541
| 0
| 1
|
0.032475
| 0.322376
| 0.236831
| -0.986871
| 0.118956
| 0.151099
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| 0.015
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| 149,000,000
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0.032423
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0.032339
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0.032334
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0.032319
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0.032394
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0.032411
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0.032499
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0.032437
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| 1
| 0.012
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0.032617
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| 1
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0.03262
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| 0.012
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0.032599
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| 1
| 0.012
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0.032635
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| 1
| 0.021
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0.032792
| 0.322001
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| 1
| 0.011
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| 0
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| 402,000,000
| -0.092852
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| 1
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0.032759
| 0.321918
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| 0.114245
| 0.144118
| 0.917932
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| 0.410921
| -0.028977
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| 1
| 0.011
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| 0
| 0
| 413,000,000
| -0.090408
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| -0.001159
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| 9.61416
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0.033902
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0.033912
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0.034273
| 0.316282
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0.032615
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0.032439
| 0.270975
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| 1
| 0.011
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| 0
| 0
| 945,000,000
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0.032011
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0.031243
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| 1
| 0.015
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| 0.188939
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0.030944
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| -0.98613
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| 1
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0.029779
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0.028014
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0.027271
| 0.248958
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| 1
| 0.013
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| 29,000,000
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| -0.011559
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| 1
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0.02491
| 0.242494
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| -0.983037
| 0.107487
| 0.17719
| 0.765764
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| -0.211538
| 0.285114
| 0.195743
| 0.213938
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| -0.85598
| 0.404606
| -0.155407
| 0.408604
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| 1
| 0.011
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| 0
| 1
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| 1.732414
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| -0.319489
| 0.924701
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| 0.272752
| -0.011559
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0.023767
| 0.238898
| 0.206136
| -0.981941
| 0.106876
| 0.182067
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| -0.051416
| 0.643334
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| 0.217842
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| 0.412146
| -0.155319
| 0.408331
| -0.029378
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| 1
| 0.011
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| 0
| 1
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| 1.760514
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| 8.829228
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| -0.011559
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| 1
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0.022552
| 0.235073
| 0.20513
| -0.980566
| 0.106658
| 0.188105
| 0.749567
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| 0.653279
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| 0.191703
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| 0.859558
| -0.844332
| 0.419235
| -0.155173
| 0.408258
| -0.029827
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| 1
| 0.011
| 0
| 0
| 1
| 62,000,000
| -1.025032
| 1.771509
| 1.505172
| -0.005425
| 0.012194
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| 1.108515
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| 8.740199
| 0.905435
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| -0.373649
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| 0.201429
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| -0.011559
| 0
| 1
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0.019964
| 0.226766
| 0.203255
| -0.977448
| 0.105612
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| 0.729557
| -0.064378
| 0.675717
| -0.215861
| 0.275291
| 0.187716
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| -0.830847
| 0.43383
| -0.155195
| 0.408102
| -0.030276
| 0
| 1
| 0.012
| 0
| 0
| 1
| 74,000,000
| -1.170418
| 1.767844
| 1.59558
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| 0.013963
| -0.00612
| -0.830788
| 1.163582
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| 8.641647
| 0.895628
| 0.314572
| -0.391951
| 0.892398
| 0.210297
| 0.323527
| -0.011559
| 0
| 1
|
0.018498
| 0.222391
| 0.202329
| -0.975596
| 0.104605
| 0.2082
| 0.720009
| -0.069753
| 0.686035
| -0.217051
| 0.272661
| 0.185481
| 0.235933
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| 0.515741
| 0.844269
| -0.823618
| 0.441755
| -0.155148
| 0.407977
| -0.030614
| 0
| 1
| 0.011
| 0
| 0
| 1
| 85,000,000
| -1.331686
| 1.738523
| 1.725083
| -0.013405
| 0.010956
| -0.003503
| -1.218649
| 0.995988
| -0.318429
| -4.312708
| -2.55435
| 8.428893
| 0.883923
| 0.3272
| -0.412211
| 0.882545
| 0.220821
| 0.337719
| -0.011559
| 0
| 1
|
0.015671
| 0.212974
| 0.200143
| -0.970779
| 0.105116
| 0.226377
| 0.699457
| -0.079639
| 0.706902
| -0.219111
| 0.267724
| 0.180876
| 0.244613
| -0.309145
| 0.532891
| 0.834699
| -0.810056
| 0.455749
| -0.154932
| 0.40754
| -0.031661
| 0
| 1
| 0.011
| 0
| 0
| 1
| 96,000,000
| -1.518611
| 1.682323
| 1.847257
| -0.016091
| 0.006821
| -0.00216
| -1.462857
| 0.620098
| -0.196325
| -4.508919
| -2.596454
| 8.312549
| 0.873511
| 0.336621
| -0.428684
| 0.874208
| 0.23067
| 0.349924
| -0.011559
| 0
| 1
|
0.013993
| 0.208083
| 0.199237
| -0.968221
| 0.103898
| 0.23517
| 0.687757
| -0.085102
| 0.718467
| -0.220325
| 0.264998
| 0.178635
| 0.248762
| -0.311692
| 0.542715
| 0.829066
| -0.802233
| 0.464217
| -0.155056
| 0.407392
| -0.031849
| 0
| 1
| 0.011
| 0
| 0
| 1
| 107,000,000
| -1.620015
| 1.598024
| 1.997529
| -0.018093
| 0.003055
| 0.001185
| -1.644817
| 0.277727
| 0.107739
| -4.697663
| -2.639034
| 8.193769
| 0.861048
| 0.345769
| -0.446862
| 0.864457
| 0.242715
| 0.364909
| -0.011559
| 0
| 1
|
0.012398
| 0.203033
| 0.198191
| -0.965092
| 0.10432
| 0.245931
| 0.67643
| -0.090081
| 0.729081
| -0.221486
| 0.262634
| 0.176353
| 0.253109
| -0.315821
| 0.551139
| 0.823906
| -0.795098
| 0.47057
| -0.155077
| 0.407239
| -0.032259
| 0
| 1
| 0.011
| 0
| 0
| 1
| 118,000,000
| -1.547933
| 1.545489
| 2.112372
| -0.020068
| -0.008691
| 0.004688
| -1.824382
| -0.790087
| 0.426168
| -4.883006
| -2.66322
| 8.076751
| 0.847724
| 0.353318
| -0.464671
| 0.854373
| 0.255823
| 0.381068
| 0.017941
| 0
| 1
|
0.009446
| 0.192773
| 0.195906
| -0.958259
| 0.105822
| 0.268438
| 0.652725
| -0.098393
| 0.750168
| -0.223415
| 0.258005
| 0.171989
| 0.260898
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| 0.568123
| 0.813036
| -0.780493
| 0.483284
| -0.154963
| 0.407066
| -0.032791
| 0
| 1
| 0.016
| 0
| 0
| 1
| 134,000,000
| -1.540602
| 1.43309
| 2.30174
| -0.039073
| 0.007891
| -0.000421
| -2.442086
| 0.493206
| -0.026336
| -5.071754
| -2.662331
| 7.959881
| 0.81829
| 0.366925
| -0.500395
| 0.833515
| 0.282855
| 0.41306
| 0.017941
| 0
| 1
|
0.00784
| 0.187169
| 0.194871
| -0.95416
| 0.107182
| 0.28107
| 0.641747
| -0.102854
| 0.75939
| -0.224261
| 0.25554
| 0.169846
| 0.264734
| -0.326623
| 0.576773
| 0.807673
| -0.772818
| 0.490899
| -0.154801
| 0.40687
| -0.032921
| 0
| 1
| 0.011
| 0
| 0
| 1
| 145,000,000
| -1.954769
| 1.329243
| 2.293188
| -0.019252
| -0.003134
| 0.01596
| -1.750161
| -0.28491
| 1.450886
| -5.412844
| -2.695153
| 7.7206
| 0.800138
| 0.373206
| -0.518969
| 0.823272
| 0.30075
| 0.427715
| 0.017941
| 0
| 1
|
0.00456
| 0.176116
| 0.193
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| 0.106768
| 0.306211
| 0.61545
| -0.11208
| 0.780911
| -0.226176
| 0.250857
| 0.165637
| 0.272075
| -0.335468
| 0.594421
| 0.795651
| -0.756729
| 0.504381
| -0.154791
| 0.406817
| -0.032907
| 0
| 1
| 0.011
| 0
| 0
| 1
| 156,000,000
| -2.037847
| 1.213178
| 2.302962
| -0.023466
| 0.000421
| 0.022702
| -2.133234
| 0.038307
| 2.063802
| -5.413891
| -2.695001
| 7.719918
| 0.78574
| 0.37423
| -0.533538
| 0.812899
| 0.312969
| 0.446259
| 0.017941
| 0
| 1
|
0.001287
| 0.165053
| 0.190848
| -0.935429
| 0.10715
| 0.331936
| 0.594065
| -0.121618
| 0.797249
| -0.227519
| 0.246247
| 0.161094
| 0.277339
| -0.338885
| 0.61146
| 0.78402
| -0.74108
| 0.520067
| -0.154753
| 0.406678
| -0.033346
| 0
| 1
| 0.016
| 0
| 0
| 1
| 172,000,000
| -2.029294
| 0.982271
| 2.366492
| -0.037311
| -0.019767
| 0.03237
| -2.331953
| -1.235408
| 2.0231
| -5.719311
| -2.745772
| 7.478007
| 0.752828
| 0.370714
| -0.563127
| 0.790568
| 0.34079
| 0.487415
| 0.017941
| 0
| 1
|
-0.000393
| 0.15951
| 0.189557
| -0.929811
| 0.106716
| 0.345853
| 0.580598
| -0.125843
| 0.807166
| -0.228171
| 0.244238
| 0.158722
| 0.27981
| -0.343089
| 0.618566
| 0.778696
| -0.734222
| 0.525283
| -0.154757
| 0.406532
| -0.033917
| 0
| 1
| 0.012
| 0
| 0
| 1
| 184,000,000
| -2.070833
| 0.827112
| 2.394592
| -0.036401
| -0.009768
| 0.022381
| -3.033453
| -0.814029
| 1.865083
| -5.985169
| -2.770175
| 7.257704
| 0.736038
| 0.366733
| -0.576563
| 0.780063
| 0.354715
| 0.506959
| 0.017941
| 0
| 1
|
-0.00402
| 0.14828
| 0.18756
| -0.917149
| 0.10483
| 0.374441
| 0.557079
| -0.136497
| 0.823817
| -0.229219
| 0.240224
| 0.154038
| 0.285148
| -0.349152
| 0.633797
| 0.767309
| -0.719022
| 0.537894
| -0.154403
| 0.406515
| -0.034614
| 0
| 1
| 0.018
| 0
| 0
| 1
| 202,000,000
| -2.241875
| 0.707382
| 2.394592
| -0.032408
| -0.027452
| 0.008016
| -1.80044
| -1.525106
| 0.445322
| -6.223044
| -2.802639
| 7.041968
| 0.700329
| 0.351248
| -0.601271
| 0.759474
| 0.384725
| 0.547562
| 0.017941
| 0
| 1
|
End of preview.
WearMoCap Dataset
TLDR: This dataset comprises optical motion capture data of left arm motions and body orientations, which are paired with smartwatch and phone sensor measurements. All synced, calibrated, and preprocessed time series data is stored as CSVs.
We collected this data to develop and test the open-source library WearMoCap, a system facilitating multimodal pose tracking from smartwatch and smartphone data. Its source code and tutorials are available on github. Details about data composition and collection setups are described in a published technical report here. A video showcasing the WearMoCap system is available here.
Repository Structure
As described in the technical report, we partitioned data for operating WearMoCap in three modes: Watch Only, Phone Uarm, and Phone Pocket. Each mode is one subfolder, which contains a README with more information and subfolders spliting the data by human subjects.
Simplified directory structure overview:
mode
|-- README.md
|-- subj01
|-- data01.csv
|-- [..]
|-- subj02
|-- [..]
[..]
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