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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 20 new columns ({'31', '57', '62', '125', '28', '195', '43', '28.1', '87', '581', '63', '185', '14723', '277', '13970', '8247', '6801', '32', '19639', '164'}) and 20 missing columns ({'11656', '51', '37', '11022', '160', '46', '76', '67', '530', '34', '108', '15980', '121', '16421', '34.1', '54', '60', '8084', '42', '295'}). This happened while the csv dataset builder was generating data using hf://datasets/MadNad/Real-Time-Gesture-Control-System-for-Precision-Control/dynamic_gestures/session-02_01_25/gabriel/fft/fft_gabriel_down.csv (at revision d92b6864f535aac18f20d242998c441dd8356f7d) 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 6801: int64 125: int64 62: int64 63: int64 8247: int64 57: int64 31: int64 32: int64 13970: int64 277: int64 185: int64 28: int64 19639: int64 28.1: int64 87: int64 43: int64 14723: int64 581: int64 195: int64 164: int64 -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2325 to {'15980': Value(dtype='int64', id=None), '76': Value(dtype='int64', id=None), '60': Value(dtype='int64', id=None), '54': Value(dtype='int64', id=None), '11022': Value(dtype='int64', id=None), '160': Value(dtype='int64', id=None), '46': Value(dtype='int64', id=None), '34': Value(dtype='int64', id=None), '8084': Value(dtype='int64', id=None), '530': Value(dtype='int64', id=None), '121': Value(dtype='int64', id=None), '67': Value(dtype='int64', id=None), '11656': Value(dtype='int64', id=None), '42': Value(dtype='int64', id=None), '108': Value(dtype='int64', id=None), '37': Value(dtype='int64', id=None), '16421': Value(dtype='int64', id=None), '295': Value(dtype='int64', id=None), '34.1': Value(dtype='int64', id=None), '51': Value(dtype='int64', 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 1438, 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 1050, 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 20 new columns ({'31', '57', '62', '125', '28', '195', '43', '28.1', '87', '581', '63', '185', '14723', '277', '13970', '8247', '6801', '32', '19639', '164'}) and 20 missing columns ({'11656', '51', '37', '11022', '160', '46', '76', '67', '530', '34', '108', '15980', '121', '16421', '34.1', '54', '60', '8084', '42', '295'}). This happened while the csv dataset builder was generating data using hf://datasets/MadNad/Real-Time-Gesture-Control-System-for-Precision-Control/dynamic_gestures/session-02_01_25/gabriel/fft/fft_gabriel_down.csv (at revision d92b6864f535aac18f20d242998c441dd8356f7d) 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.
15980
int64 | 76
int64 | 60
int64 | 54
int64 | 11022
int64 | 160
int64 | 46
int64 | 34
int64 | 8084
int64 | 530
int64 | 121
int64 | 67
int64 | 11656
int64 | 42
int64 | 108
int64 | 37
int64 | 16421
int64 | 295
int64 | 34.1
int64 | 51
int64 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
15,126 | 80 | 74 | 19 | 11,022 | 160 | 46 | 34 | 8,084 | 530 | 121 | 67 | 12,757 | 97 | 111 | 45 | 15,809 | 136 | 33 | 12 |
15,126 | 80 | 74 | 19 | 9,618 | 71 | 84 | 25 | 8,084 | 530 | 121 | 67 | 12,757 | 97 | 111 | 45 | 15,809 | 136 | 33 | 12 |
15,126 | 80 | 74 | 19 | 9,618 | 71 | 84 | 25 | 8,214 | 544 | 162 | 78 | 12,757 | 97 | 111 | 45 | 15,809 | 136 | 33 | 12 |
15,126 | 80 | 74 | 19 | 9,618 | 71 | 84 | 25 | 8,214 | 544 | 162 | 78 | 13,870 | 131 | 167 | 118 | 15,809 | 136 | 33 | 12 |
15,126 | 80 | 74 | 19 | 9,618 | 71 | 84 | 25 | 8,214 | 544 | 162 | 78 | 13,870 | 131 | 167 | 118 | 15,341 | 145 | 11 | 11 |
13,822 | 100 | 26 | 18 | 9,618 | 71 | 84 | 25 | 8,214 | 544 | 162 | 78 | 13,870 | 131 | 167 | 118 | 15,341 | 145 | 11 | 11 |
13,822 | 100 | 26 | 18 | 8,827 | 45 | 63 | 21 | 8,214 | 544 | 162 | 78 | 13,870 | 131 | 167 | 118 | 15,341 | 145 | 11 | 11 |
13,822 | 100 | 26 | 18 | 8,827 | 45 | 63 | 21 | 7,760 | 426 | 108 | 21 | 13,870 | 131 | 167 | 118 | 15,341 | 145 | 11 | 11 |
13,822 | 100 | 26 | 18 | 8,827 | 45 | 63 | 21 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 15,341 | 145 | 11 | 11 |
13,822 | 100 | 26 | 18 | 8,827 | 45 | 63 | 21 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 14,246 | 194 | 78 | 62 |
12,861 | 150 | 10 | 56 | 8,827 | 45 | 63 | 21 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 14,246 | 194 | 78 | 62 |
12,861 | 150 | 10 | 56 | 8,150 | 108 | 24 | 4 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 14,246 | 194 | 78 | 62 |
12,861 | 150 | 10 | 56 | 8,150 | 108 | 24 | 4 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 13,358 | 273 | 52 | 75 |
12,394 | 81 | 24 | 51 | 8,150 | 108 | 24 | 4 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 13,358 | 273 | 52 | 75 |
12,394 | 81 | 24 | 51 | 7,623 | 52 | 25 | 21 | 7,760 | 426 | 108 | 21 | 14,875 | 195 | 155 | 71 | 13,358 | 273 | 52 | 75 |
12,394 | 81 | 24 | 51 | 7,623 | 52 | 25 | 21 | 8,028 | 365 | 208 | 74 | 14,875 | 195 | 155 | 71 | 13,358 | 273 | 52 | 75 |
12,394 | 81 | 24 | 51 | 7,623 | 52 | 25 | 21 | 8,028 | 365 | 208 | 74 | 16,493 | 254 | 66 | 42 | 13,358 | 273 | 52 | 75 |
12,394 | 81 | 24 | 51 | 7,623 | 52 | 25 | 21 | 8,028 | 365 | 208 | 74 | 16,493 | 254 | 66 | 42 | 12,137 | 263 | 97 | 81 |
11,621 | 116 | 68 | 50 | 7,623 | 52 | 25 | 21 | 8,028 | 365 | 208 | 74 | 16,493 | 254 | 66 | 42 | 12,137 | 263 | 97 | 81 |
11,621 | 116 | 68 | 50 | 7,149 | 86 | 34 | 11 | 8,028 | 365 | 208 | 74 | 16,493 | 254 | 66 | 42 | 12,137 | 263 | 97 | 81 |
11,621 | 116 | 68 | 50 | 7,149 | 86 | 34 | 11 | 8,516 | 408 | 321 | 147 | 16,493 | 254 | 66 | 42 | 12,137 | 263 | 97 | 81 |
11,621 | 116 | 68 | 50 | 7,149 | 86 | 34 | 11 | 8,516 | 408 | 321 | 147 | 17,294 | 158 | 89 | 15 | 12,137 | 263 | 97 | 81 |
11,621 | 116 | 68 | 50 | 7,149 | 86 | 34 | 11 | 8,516 | 408 | 321 | 147 | 17,294 | 158 | 89 | 15 | 11,370 | 98 | 91 | 37 |
10,814 | 93 | 77 | 44 | 7,149 | 86 | 34 | 11 | 8,516 | 408 | 321 | 147 | 17,294 | 158 | 89 | 15 | 11,370 | 98 | 91 | 37 |
10,814 | 93 | 77 | 44 | 7,099 | 51 | 19 | 10 | 8,516 | 408 | 321 | 147 | 17,294 | 158 | 89 | 15 | 11,370 | 98 | 91 | 37 |
10,814 | 93 | 77 | 44 | 7,099 | 51 | 19 | 10 | 8,823 | 338 | 225 | 130 | 17,294 | 158 | 89 | 15 | 11,370 | 98 | 91 | 37 |
10,814 | 93 | 77 | 44 | 7,099 | 51 | 19 | 10 | 8,823 | 338 | 225 | 130 | 17,871 | 132 | 66 | 19 | 11,370 | 98 | 91 | 37 |
10,814 | 93 | 77 | 44 | 7,099 | 51 | 19 | 10 | 8,823 | 338 | 225 | 130 | 17,871 | 132 | 66 | 19 | 11,062 | 395 | 48 | 25 |
10,116 | 82 | 37 | 55 | 7,099 | 51 | 19 | 10 | 8,823 | 338 | 225 | 130 | 17,871 | 132 | 66 | 19 | 11,062 | 395 | 48 | 25 |
10,116 | 82 | 37 | 55 | 7,343 | 89 | 56 | 5 | 8,823 | 338 | 225 | 130 | 17,871 | 132 | 66 | 19 | 11,062 | 395 | 48 | 25 |
10,116 | 82 | 37 | 55 | 7,343 | 89 | 56 | 5 | 9,627 | 139 | 255 | 283 | 17,871 | 132 | 66 | 19 | 11,062 | 395 | 48 | 25 |
10,116 | 82 | 37 | 55 | 7,343 | 89 | 56 | 5 | 9,627 | 139 | 255 | 283 | 18,263 | 122 | 88 | 58 | 11,062 | 395 | 48 | 25 |
10,116 | 82 | 37 | 55 | 7,343 | 89 | 56 | 5 | 9,627 | 139 | 255 | 283 | 18,263 | 122 | 88 | 58 | 9,618 | 37 | 8 | 11 |
9,504 | 96 | 11 | 29 | 7,343 | 89 | 56 | 5 | 9,627 | 139 | 255 | 283 | 18,263 | 122 | 88 | 58 | 9,618 | 37 | 8 | 11 |
9,504 | 96 | 11 | 29 | 7,642 | 58 | 44 | 27 | 9,627 | 139 | 255 | 283 | 18,263 | 122 | 88 | 58 | 9,618 | 37 | 8 | 11 |
9,504 | 96 | 11 | 29 | 7,642 | 58 | 44 | 27 | 10,176 | 152 | 123 | 55 | 18,263 | 122 | 88 | 58 | 9,618 | 37 | 8 | 11 |
9,504 | 96 | 11 | 29 | 7,642 | 58 | 44 | 27 | 10,176 | 152 | 123 | 55 | 18,340 | 163 | 62 | 31 | 9,618 | 37 | 8 | 11 |
9,504 | 96 | 11 | 29 | 7,642 | 58 | 44 | 27 | 10,176 | 152 | 123 | 55 | 18,340 | 163 | 62 | 31 | 8,960 | 88 | 26 | 21 |
9,141 | 74 | 27 | 31 | 7,642 | 58 | 44 | 27 | 10,176 | 152 | 123 | 55 | 18,340 | 163 | 62 | 31 | 8,960 | 88 | 26 | 21 |
9,141 | 74 | 27 | 31 | 8,565 | 12 | 37 | 14 | 10,176 | 152 | 123 | 55 | 18,340 | 163 | 62 | 31 | 8,960 | 88 | 26 | 21 |
9,141 | 74 | 27 | 31 | 8,565 | 12 | 37 | 14 | 11,257 | 94 | 125 | 91 | 18,340 | 163 | 62 | 31 | 8,960 | 88 | 26 | 21 |
9,141 | 74 | 27 | 31 | 8,565 | 12 | 37 | 14 | 11,257 | 94 | 125 | 91 | 18,269 | 142 | 53 | 57 | 8,960 | 88 | 26 | 21 |
9,141 | 74 | 27 | 31 | 8,565 | 12 | 37 | 14 | 11,257 | 94 | 125 | 91 | 18,269 | 142 | 53 | 57 | 8,542 | 92 | 79 | 34 |
8,984 | 54 | 13 | 41 | 8,565 | 12 | 37 | 14 | 11,257 | 94 | 125 | 91 | 18,269 | 142 | 53 | 57 | 8,542 | 92 | 79 | 34 |
8,984 | 54 | 13 | 41 | 9,332 | 49 | 16 | 29 | 11,257 | 94 | 125 | 91 | 18,269 | 142 | 53 | 57 | 8,542 | 92 | 79 | 34 |
8,984 | 54 | 13 | 41 | 9,332 | 49 | 16 | 29 | 12,179 | 69 | 148 | 48 | 18,269 | 142 | 53 | 57 | 8,542 | 92 | 79 | 34 |
8,984 | 54 | 13 | 41 | 9,332 | 49 | 16 | 29 | 12,179 | 69 | 148 | 48 | 18,031 | 99 | 105 | 52 | 8,542 | 92 | 79 | 34 |
8,984 | 54 | 13 | 41 | 9,332 | 49 | 16 | 29 | 12,179 | 69 | 148 | 48 | 18,031 | 99 | 105 | 52 | 7,773 | 148 | 87 | 60 |
8,798 | 8 | 18 | 11 | 9,332 | 49 | 16 | 29 | 12,179 | 69 | 148 | 48 | 18,031 | 99 | 105 | 52 | 7,773 | 148 | 87 | 60 |
8,798 | 8 | 18 | 11 | 10,382 | 38 | 43 | 15 | 12,179 | 69 | 148 | 48 | 18,031 | 99 | 105 | 52 | 7,773 | 148 | 87 | 60 |
8,798 | 8 | 18 | 11 | 10,382 | 38 | 43 | 15 | 13,394 | 145 | 154 | 66 | 18,031 | 99 | 105 | 52 | 7,773 | 148 | 87 | 60 |
8,798 | 8 | 18 | 11 | 10,382 | 38 | 43 | 15 | 13,394 | 145 | 154 | 66 | 17,469 | 109 | 5 | 52 | 7,773 | 148 | 87 | 60 |
8,798 | 8 | 18 | 11 | 10,382 | 38 | 43 | 15 | 13,394 | 145 | 154 | 66 | 17,469 | 109 | 5 | 52 | 8,081 | 285 | 104 | 78 |
8,879 | 52 | 30 | 12 | 10,382 | 38 | 43 | 15 | 13,394 | 145 | 154 | 66 | 17,469 | 109 | 5 | 52 | 8,081 | 285 | 104 | 78 |
8,879 | 52 | 30 | 12 | 11,543 | 105 | 21 | 11 | 13,394 | 145 | 154 | 66 | 17,469 | 109 | 5 | 52 | 8,081 | 285 | 104 | 78 |
8,879 | 52 | 30 | 12 | 11,543 | 105 | 21 | 11 | 14,660 | 335 | 88 | 64 | 17,469 | 109 | 5 | 52 | 8,081 | 285 | 104 | 78 |
8,879 | 52 | 30 | 12 | 11,543 | 105 | 21 | 11 | 14,660 | 335 | 88 | 64 | 16,756 | 128 | 24 | 5 | 8,081 | 285 | 104 | 78 |
8,879 | 52 | 30 | 12 | 11,543 | 105 | 21 | 11 | 14,660 | 335 | 88 | 64 | 16,756 | 128 | 24 | 5 | 8,200 | 221 | 24 | 45 |
9,381 | 48 | 15 | 8 | 11,543 | 105 | 21 | 11 | 14,660 | 335 | 88 | 64 | 16,756 | 128 | 24 | 5 | 8,200 | 221 | 24 | 45 |
9,381 | 48 | 15 | 8 | 12,854 | 61 | 15 | 29 | 14,660 | 335 | 88 | 64 | 16,756 | 128 | 24 | 5 | 8,200 | 221 | 24 | 45 |
9,381 | 48 | 15 | 8 | 12,854 | 61 | 15 | 29 | 15,253 | 372 | 131 | 51 | 16,756 | 128 | 24 | 5 | 8,200 | 221 | 24 | 45 |
9,381 | 48 | 15 | 8 | 12,854 | 61 | 15 | 29 | 15,253 | 372 | 131 | 51 | 15,752 | 149 | 55 | 36 | 8,200 | 221 | 24 | 45 |
9,381 | 48 | 15 | 8 | 12,854 | 61 | 15 | 29 | 15,253 | 372 | 131 | 51 | 15,752 | 149 | 55 | 36 | 8,624 | 406 | 36 | 29 |
9,847 | 97 | 64 | 49 | 12,854 | 61 | 15 | 29 | 15,253 | 372 | 131 | 51 | 15,752 | 149 | 55 | 36 | 8,624 | 406 | 36 | 29 |
9,847 | 97 | 64 | 49 | 13,961 | 84 | 43 | 43 | 15,253 | 372 | 131 | 51 | 15,752 | 149 | 55 | 36 | 8,624 | 406 | 36 | 29 |
9,847 | 97 | 64 | 49 | 13,961 | 84 | 43 | 43 | 16,399 | 369 | 188 | 36 | 15,752 | 149 | 55 | 36 | 8,624 | 406 | 36 | 29 |
9,847 | 97 | 64 | 49 | 13,961 | 84 | 43 | 43 | 16,399 | 369 | 188 | 36 | 14,495 | 114 | 59 | 29 | 8,624 | 406 | 36 | 29 |
9,847 | 97 | 64 | 49 | 13,961 | 84 | 43 | 43 | 16,399 | 369 | 188 | 36 | 14,495 | 114 | 59 | 29 | 9,678 | 105 | 21 | 11 |
10,282 | 58 | 50 | 25 | 13,961 | 84 | 43 | 43 | 16,399 | 369 | 188 | 36 | 14,495 | 114 | 59 | 29 | 9,678 | 105 | 21 | 11 |
10,282 | 58 | 50 | 25 | 14,973 | 130 | 73 | 25 | 16,399 | 369 | 188 | 36 | 14,495 | 114 | 59 | 29 | 9,678 | 105 | 21 | 11 |
10,282 | 58 | 50 | 25 | 14,973 | 130 | 73 | 25 | 17,371 | 361 | 178 | 44 | 14,495 | 114 | 59 | 29 | 9,678 | 105 | 21 | 11 |
10,282 | 58 | 50 | 25 | 14,973 | 130 | 73 | 25 | 17,371 | 361 | 178 | 44 | 13,238 | 129 | 58 | 29 | 9,678 | 105 | 21 | 11 |
10,282 | 58 | 50 | 25 | 14,973 | 130 | 73 | 25 | 17,371 | 361 | 178 | 44 | 13,238 | 129 | 58 | 29 | 10,045 | 85 | 58 | 38 |
11,024 | 120 | 92 | 40 | 14,973 | 130 | 73 | 25 | 17,371 | 361 | 178 | 44 | 13,238 | 129 | 58 | 29 | 10,045 | 85 | 58 | 38 |
11,024 | 120 | 92 | 40 | 16,042 | 99 | 86 | 50 | 17,371 | 361 | 178 | 44 | 13,238 | 129 | 58 | 29 | 10,045 | 85 | 58 | 38 |
11,024 | 120 | 92 | 40 | 16,042 | 99 | 86 | 50 | 18,148 | 355 | 95 | 37 | 13,238 | 129 | 58 | 29 | 10,045 | 85 | 58 | 38 |
11,024 | 120 | 92 | 40 | 16,042 | 99 | 86 | 50 | 18,148 | 355 | 95 | 37 | 12,125 | 152 | 41 | 21 | 10,045 | 85 | 58 | 38 |
11,024 | 120 | 92 | 40 | 16,042 | 99 | 86 | 50 | 18,148 | 355 | 95 | 37 | 12,125 | 152 | 41 | 21 | 11,346 | 87 | 23 | 14 |
11,941 | 133 | 34 | 20 | 16,042 | 99 | 86 | 50 | 18,148 | 355 | 95 | 37 | 12,125 | 152 | 41 | 21 | 11,346 | 87 | 23 | 14 |
11,941 | 133 | 34 | 20 | 16,845 | 22 | 81 | 47 | 18,148 | 355 | 95 | 37 | 12,125 | 152 | 41 | 21 | 11,346 | 87 | 23 | 14 |
11,941 | 133 | 34 | 20 | 16,845 | 22 | 81 | 47 | 18,270 | 400 | 230 | 17 | 12,125 | 152 | 41 | 21 | 11,346 | 87 | 23 | 14 |
11,941 | 133 | 34 | 20 | 16,845 | 22 | 81 | 47 | 18,270 | 400 | 230 | 17 | 10,777 | 209 | 68 | 29 | 11,346 | 87 | 23 | 14 |
11,941 | 133 | 34 | 20 | 16,845 | 22 | 81 | 47 | 18,270 | 400 | 230 | 17 | 10,777 | 209 | 68 | 29 | 12,349 | 258 | 106 | 35 |
12,785 | 81 | 30 | 34 | 16,845 | 22 | 81 | 47 | 18,270 | 400 | 230 | 17 | 10,777 | 209 | 68 | 29 | 12,349 | 258 | 106 | 35 |
12,785 | 81 | 30 | 34 | 17,522 | 88 | 27 | 33 | 18,270 | 400 | 230 | 17 | 10,777 | 209 | 68 | 29 | 12,349 | 258 | 106 | 35 |
12,785 | 81 | 30 | 34 | 17,522 | 88 | 27 | 33 | 18,501 | 292 | 135 | 55 | 10,777 | 209 | 68 | 29 | 12,349 | 258 | 106 | 35 |
12,785 | 81 | 30 | 34 | 17,522 | 88 | 27 | 33 | 18,501 | 292 | 135 | 55 | 9,621 | 120 | 63 | 12 | 12,349 | 258 | 106 | 35 |
12,785 | 81 | 30 | 34 | 17,522 | 88 | 27 | 33 | 18,501 | 292 | 135 | 55 | 9,621 | 120 | 63 | 12 | 13,281 | 175 | 50 | 44 |
13,682 | 56 | 72 | 51 | 17,522 | 88 | 27 | 33 | 18,501 | 292 | 135 | 55 | 9,621 | 120 | 63 | 12 | 13,281 | 175 | 50 | 44 |
13,682 | 56 | 72 | 51 | 18,264 | 47 | 4 | 16 | 18,501 | 292 | 135 | 55 | 9,621 | 120 | 63 | 12 | 13,281 | 175 | 50 | 44 |
13,682 | 56 | 72 | 51 | 18,264 | 47 | 4 | 16 | 18,469 | 321 | 233 | 41 | 9,621 | 120 | 63 | 12 | 13,281 | 175 | 50 | 44 |
13,682 | 56 | 72 | 51 | 18,264 | 47 | 4 | 16 | 18,469 | 321 | 233 | 41 | 8,505 | 216 | 89 | 16 | 13,281 | 175 | 50 | 44 |
13,682 | 56 | 72 | 51 | 18,264 | 47 | 4 | 16 | 18,469 | 321 | 233 | 41 | 8,505 | 216 | 89 | 16 | 14,753 | 88 | 71 | 21 |
14,459 | 16 | 51 | 22 | 18,264 | 47 | 4 | 16 | 18,469 | 321 | 233 | 41 | 8,505 | 216 | 89 | 16 | 14,753 | 88 | 71 | 21 |
14,459 | 16 | 51 | 22 | 18,556 | 97 | 14 | 17 | 18,469 | 321 | 233 | 41 | 8,505 | 216 | 89 | 16 | 14,753 | 88 | 71 | 21 |
14,459 | 16 | 51 | 22 | 18,556 | 97 | 14 | 17 | 17,797 | 324 | 286 | 137 | 8,505 | 216 | 89 | 16 | 14,753 | 88 | 71 | 21 |
14,459 | 16 | 51 | 22 | 18,556 | 97 | 14 | 17 | 17,797 | 324 | 286 | 137 | 7,461 | 196 | 69 | 45 | 14,753 | 88 | 71 | 21 |
14,459 | 16 | 51 | 22 | 18,556 | 97 | 14 | 17 | 17,797 | 324 | 286 | 137 | 7,461 | 196 | 69 | 45 | 15,174 | 76 | 52 | 42 |
15,328 | 19 | 71 | 43 | 18,556 | 97 | 14 | 17 | 17,797 | 324 | 286 | 137 | 7,461 | 196 | 69 | 45 | 15,174 | 76 | 52 | 42 |
15,328 | 19 | 71 | 43 | 18,530 | 50 | 30 | 6 | 17,797 | 324 | 286 | 137 | 7,461 | 196 | 69 | 45 | 15,174 | 76 | 52 | 42 |
Real Time Gesture Recognition Dataset
This repository contains the dataset for the Real-Time-Gesture-Control-System-for-Precision-Control project that focuses on the development of a real-time gesture control system using the uMyo EMG sensors.
Description
The dataset is divided into two folders: dynamic_gestures
and static_gestures
. The first contains loosely-timed sessions of gesture recordings where the gesture is repeated several times between intervals of rest. The second contains a single recording of each gesture, where the gesture is held for a few seconds. The gestures are: baseline
, fist
, up
, down
, peace
, and lift
. New gesture recordings and more gestures will be uploaded soon.
Every subject has two types of recordings: the raw EMG data in the raw
folder and the FFT data in the fft
folder.
Each individual recording is a CSV file dedicated to a single gesture performed by a subject.
Structure
dynamic_gestures
βββ session-DD_MM_YY
β βββ subject1
β β βββ fft
β β β βββ fft_subject1_baseline.csv
β β β βββ fft_subject1_fist.csv
β β β βββ fft_subject1_up.csv
β β β βββ ...
β β βββ raw
β β β βββ subject1_baseline.csv
β β β βββ subject1_fist.csv
β β β βββ subject1_up.csv
β β β βββ ...
β βββ subject2
β βββ ...
βββ session-DD_MM_YY
βββ ...
static_gestures
βββ session-DD_MM_YY
β βββ subject1
β β βββ fft
β β β βββ fft_subject1_baseline.csv
β β β βββ fft_subject1_fist.csv
β β β βββ fft_subject1_up.csv
β β β βββ ...
β β βββ raw
β β β βββ subject1_baseline.csv
β β β βββ subject1_fist.csv
β β β βββ subject1_up.csv
β β β βββ ...
β βββ subject2
β βββ ...
βββ session-DD_MM_YY
βββ ...
Contents
Raw EMG Data
The raw EMG data is a header-less CSV file with the columns containing 8 successive EMG readings from the corresponding sensor:
[sensor 1] [sensor 2] [sensor 3] [sensor 4] [sensor 5]
[0]: [8 readings][8 readings][8 readings][8 readings][8 readings]
[1]: [8 readings][8 readings][8 readings][8 readings][8 readings]
[2]: [8 readings][8 readings][8 readings][8 readings][8 readings]
[3]: [8 readings][8 readings][8 readings][8 readings][8 readings]
...
Each row can be treated as a single 5-dimensional data unit in time.
FFT EMG Data
The FFT EMG data is a header-less CSV file with the columns containing 4 FFT bins with ~143 Hz resolution from the corresponding sensor:
[sensor 1] [sensor 2] [sensor 3] [sensor 4] [sensor 5]
[0]: [4 bins] [4 bins] [4 bins] [4 bins] [4 bins]
[1]: [4 bins] [4 bins] [4 bins] [4 bins] [4 bins]
[2]: [4 bins] [4 bins] [4 bins] [4 bins] [4 bins]
[3]: [4 bins] [4 bins] [4 bins] [4 bins] [4 bins]
...
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