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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 4 new columns ({'pm10', 'illuminance (Lux)', 'tsp', 'pm2.5'}) and 4 missing columns ({'color', 'polarity', 'y', 'x'}).
This happened while the csv dataset builder was generating data using
zip://global/global dust strom1/seq49_gt.csv::/tmp/hf-datasets-cache/medium/datasets/63228869847347-config-parquet-and-info-Miniecho-EVMars-Anomaly-v-1b6acb1f/hub/datasets--Miniecho--EVMars-Anomaly-v2/snapshots/c018b80abdc56946eb265d91c530819034f81e24/EVMars-Anomaly-v2.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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
timestamp: int64
illuminance (Lux): double
tsp: double
pm2.5: double
pm10: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 838
to
{'timestamp': Value('int64'), 'x': Value('int64'), 'y': Value('int64'), 'polarity': Value('int64'), 'color': Value('string')}
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 1339, 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 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 4 new columns ({'pm10', 'illuminance (Lux)', 'tsp', 'pm2.5'}) and 4 missing columns ({'color', 'polarity', 'y', 'x'}).
This happened while the csv dataset builder was generating data using
zip://global/global dust strom1/seq49_gt.csv::/tmp/hf-datasets-cache/medium/datasets/63228869847347-config-parquet-and-info-Miniecho-EVMars-Anomaly-v-1b6acb1f/hub/datasets--Miniecho--EVMars-Anomaly-v2/snapshots/c018b80abdc56946eb265d91c530819034f81e24/EVMars-Anomaly-v2.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.
timestamp
int64 | x
int64 | y
int64 | polarity
int64 | color
string |
|---|---|---|---|---|
1,760,583,297,755,038
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,756,451
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,756,587
| 101
| 144
| 0
|
GREEN
|
1,760,583,297,756,904
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,762,110
| 191
| 20
| 1
|
GREEN
|
1,760,583,297,762,782
| 242
| 39
| 1
|
GREEN
|
1,760,583,297,763,338
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,770,226
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,770,248
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,771,447
| 136
| 24
| 1
|
RED
|
1,760,583,297,776,260
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,777,222
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,781,400
| 101
| 144
| 0
|
GREEN
|
1,760,583,297,781,708
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,782,676
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,783,571
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,784,658
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,785,833
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,788,430
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,790,287
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,795,567
| 101
| 144
| 0
|
GREEN
|
1,760,583,297,797,146
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,808,757
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,813,881
| 36
| 80
| 1
|
RED
|
1,760,583,297,821,249
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,821,931
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,825,073
| 339
| 1
| 1
|
BLUE
|
1,760,583,297,825,613
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,827,086
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,830,758
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,831,747
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,832,513
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,833,252
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,837,867
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,838,508
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,838,583
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,840,503
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,841,914
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,843,094
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,844,096
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,849,615
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,850,085
| 283
| 141
| 1
|
BLUE
|
1,760,583,297,852,884
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,857,607
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,862,432
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,863,929
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,865,039
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,865,162
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,866,540
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,866,756
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,869,349
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,871,375
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,873,395
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,875,047
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,888,078
| 101
| 144
| 0
|
GREEN
|
1,760,583,297,889,688
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,890,688
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,891,223
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,891,256
| 262
| 160
| 1
|
RED
|
1,760,583,297,891,565
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,892,458
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,893,064
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,895,172
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,895,637
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,896,548
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,897,217
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,899,434
| 101
| 144
| 1
|
GREEN
|
1,760,583,297,900,188
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,900,984
| 39
| 176
| 1
|
GREEN
|
1,760,583,297,902,067
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,918,078
| 219
| 217
| 1
|
BLUE
|
1,760,583,297,918,151
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,920,435
| 262
| 23
| 1
|
GREEN
|
1,760,583,297,922,313
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,922,596
| 60
| 31
| 1
|
GREEN
|
1,760,583,297,924,044
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,929,023
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,930,358
| 151
| 94
| 1
|
GREEN
|
1,760,583,297,934,848
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,942,025
| 312
| 247
| 1
|
GREEN
|
1,760,583,297,943,057
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,946,060
| 284
| 45
| 1
|
GREEN
|
1,760,583,297,947,748
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,952,301
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,953,957
| 289
| 107
| 1
|
BLUE
|
1,760,583,297,958,643
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,961,786
| 44
| 47
| 1
|
GREEN
|
1,760,583,297,970,005
| 68
| 20
| 1
|
RED
|
1,760,583,297,974,125
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,975,147
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,977,302
| 339
| 1
| 1
|
BLUE
|
1,760,583,297,980,198
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,980,987
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,981,803
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,983,111
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,983,623
| 289
| 107
| 0
|
BLUE
|
1,760,583,297,983,644
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,984,650
| 147
| 105
| 0
|
BLUE
|
1,760,583,297,985,337
| 147
| 105
| 1
|
BLUE
|
1,760,583,297,987,166
| 147
| 105
| 0
|
BLUE
|
End of preview.
EVMars-Anomaly-v2: A Multimodal Color Event Dataset for Martian Anomaly Detection and Dust Storm Estimation
EVMars-Anomaly-v2, an updated and expanded version of the original EVMars-Anomaly dataset (a specialized subset of EVMars), remains a multimodal dataset dedicated to anomaly detection in simulated Martian dust storm scenarios using a color event camera. This version introduces significant enhancements to address sensing challenges in extremely low-visibility environments, thereby supporting more reliable particulate matter estimation and anomaly detection under severe dust storm conditions.
The dataset consists of 68 sequences captured with a DAVIS346 color event camera(346×260 resolution, 1 µs temporal precision) in a outdoor data collection test field. High-power industrial fans simulate three canonical dust storm intensities:
- Local Dust Storm: Mild particle suspension
- Regional Dust Storm: Moderate occlusion
- Global Dust Storm: Extreme low-visibility
The data format is as follows:
Event Streams: Stored as CSV files with the following columns: timestamp (microseconds), x (pixel column, 0–345), y (pixel row, 0–259), polarity (±1), color (RED/GREEN/BLUE). Each file corresponds to one continuous sequence.
Ground Truth: Provided in a separate synchronized CSV per sequence: timestamp (ms), TSP (µg/m³), PM2.5 (µg/m³), PM10 (µg/m³)
Key Updates in v2 (Released January 2026)
- Added numerous new sequences with substantially higher dust concentrations, enabling better modeling and evaluation of performance in extreme dust storm environments.
- Expanded the total number of event data points to approximately 680 million, providing richer temporal and spatial event distributions.
- Introduced standardized dataset splits divided into three dust storm intensity intervals: global (planet-encircling storms with highest dust loading), regional (large-scale but localized storms), and local (smaller, confined dust events). This partitioning facilitates consistent benchmarking and analysis across varying severity levels.
Historical Version
EVMars-Anomaly-v1: The original release containing sequences covering a baseline range of dust conditions and approximately 150 million event data points.Available at: Hugging Face Dataset v1
License
This repository is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
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