Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: IndexError
Message: list index out of range
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1811, in _prepare_split_single
original_shard_lengths[original_shard_id] += len(table)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
IndexError: list index out of range
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, 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 1832, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
text string |
|---|
0 0.2669538558651848 0.04693140794223827 0.06201194385536873 0.03971119133574008 |
0 0.4280336612455937 0.10379061371841156 0.2782975041314108 0.03790613718411553 |
0 0.1951107501790869 0.1561371841155235 0.3206471243253211 0.037906137184115514 |
0 0.6881813281510429 0.2148014440433213 0.4325711205520841 0.04332129963898915 |
0 0.12629261736398262 0.26624548736462095 0.17393594008213176 0.04151624548736464 |
0 0.5974321420212351 0.2680505415162455 0.48399565935897526 0.03790613718411556 |
0 0.3343744322176493 0.7382671480144404 0.055283239459984694 0.03249097472924177 |
0 0.4752575263253522 0.7824909747292418 0.2443162518070291 0.02707581227436819 |
0 0.2674995457741194 0.825812274368231 0.28533284882572735 0.02707581227436819 |
0 0.6732071901982004 0.8664259927797835 0.47258253086761093 0.028880866425992763 |
0 0.19081634265220518 0.9097472924187726 0.1426664244128637 0.025270758122743757 |
0 0.5760156885669372 0.48646209386281586 0.057066569765145445 0.03068592057761741 |
0 0.82566091889589 0.3474729241877256 0.08009507365966329 0.034296028880866414 |
0 0.36894858398546987 0.3962093862815884 0.4856828934681705 0.03068592057761741 |
0 0.844406574433258 0.4954873646209386 0.0630535686256924 0.030685920577617338 |
0 0.27010785478843874 0.6940433212996391 0.05623696661210399 0.03429602888086649 |
0 0.4703455389375968 0.7906137184115525 0.05112451510191271 0.032490974729241916 |
0 0.3289010471556384 0.7436823104693141 0.061349418122295205 0.032490974729241916 |
0 0.2543587160327988 0.3628158844765343 0.06254722525396687 0.032490974729241916 |
0 0.26165589231242825 0.4151624548736462 0.310651218761369 0.025270758122743615 |
0 0.6963591078274983 0.41425992779783394 0.42949094674390614 0.030685920577617338 |
0 0.1553256093806845 0.4684115523465704 0.21474547337195307 0.027075812274368262 |
0 0.4889108107351747 0.4684115523465704 0.1938963982872975 0.027075812274368262 |
0 0.28250496739708386 0.5749097472924188 0.060462317745501294 0.027075812274368262 |
0 0.2960568662021101 0.6308664259927798 0.2960568662021101 0.023465703971119113 |
0 0.7109534603867573 0.6281588447653429 0.391962611591526 0.028880866425992836 |
0 0.13030671927909776 0.6823104693140795 0.16887750818571068 0.025270758122743615 |
0 0.43991548428623395 0.684115523465704 0.1834718607449696 0.025270758122743615 |
0 0.7766280469034226 0.9440433212996391 0.05629250272857021 0.028880866425992763 |
0 0.2761035021772303 0.12454873646209386 0.07060180877591271 0.050541516245487375 |
0 0.38137584204845737 0.21841155234657036 0.7198863001972535 0.05054151624548733 |
0 0.2912324612006401 0.305956678700361 0.32275112583274407 0.04151624548736457 |
0 0.4519776508243701 0.39440433212996395 0.06934106219062855 0.05595667870036102 |
0 0.8484824518962373 0.6723826714801444 0.06555882243477626 0.05234657039711195 |
0 0.3521376708716992 0.08483754512635379 0.05947213996944257 0.039711191335740074 |
0 0.29814322800470533 0.3113718411552347 0.18624170148325422 0.03790613718411553 |
0 0.6933199475385012 0.3095667870036101 0.06260225259941322 0.04512635379061372 |
0 0.2590168201300721 0.36642599277978344 0.06416730891439851 0.043321299638989216 |
0 0.23162833461782883 0.5333935018050542 0.35057261455671396 0.030685920577617338 |
0 0.492992739220379 0.536101083032491 0.06260225259941316 0.03610108303249092 |
0 0.26840715801998405 0.9314079422382672 0.06103719628442789 0.03610108303249092 |
0 0.3865689098013765 0.9287003610108303 0.05008180207953053 0.03790613718411549 |
0 0.5039481334252762 0.927797833935018 0.05947213996944257 0.043321299638989216 |
0 0.6181972444192053 0.9296028880866426 0.06260225259941322 0.043321299638989216 |
0 0.5935646596183599 0.04512635379061372 0.04294524669073404 0.032490974729241874 |
0 0.6863570676465532 0.050541516245487375 0.0444790055011174 0.03249097472924188 |
0 0.7760819580539797 0.04693140794223827 0.04601276431150083 0.03971119133574008 |
0 0.25537084192882925 0.30054151624548736 0.05061404074265084 0.030685920577617303 |
0 0.29831608861956327 0.34386281588447654 0.2592052389547876 0.030685920577617366 |
0 0.6917252234828948 0.34657039711191323 0.4202499140450402 0.03249097472924164 |
0 0.19018609248753648 0.3898916967509025 0.24846892728210412 0.032490974729241916 |
0 0.25613772133402096 0.4305054151624549 0.04908028193226745 0.030685920577617338 |
0 0.31595431493897197 0.47021660649819497 0.24846892728210418 0.02707581227436819 |
0 0.674853876568678 0.47202166064981954 0.3834397025958397 0.03068592057761727 |
0 0.2546039625236376 0.516245487364621 0.04908028193226748 0.032490974729241916 |
0 0.2983160886195633 0.5586642599277978 0.25613772133402096 0.034296028880866344 |
0 0.6809889118102113 0.5577617328519855 0.3987772906996733 0.028880866425992788 |
0 0.1825172984356197 0.914259927797834 0.024540140966133776 0.03790613718411564 |
0 0.2136793833544736 0.5767148014440433 0.06331240988280698 0.03790613718411549 |
0 0.5310328378920436 0.5740072202166064 0.21684500384861394 0.03971119133574007 |
0 0.29123708546091215 0.6416967509025271 0.09180299433007018 0.03790613718411556 |
0 0.6996021292050173 0.6389891696750902 0.37670883880270156 0.03971119133574 |
0 0.5880140067865699 0.7048736462093862 0.06806084062401752 0.04151624548736464 |
0 0.8974534100887891 0.7021660649819494 0.0886373738359299 0.036101083032491064 |
0 0.18518879890721046 0.7644404332129965 0.31023080842575423 0.03790613718411549 |
0 0.8824167127416225 0.7707581227436823 0.05856397914159658 0.03610108303249092 |
0 0.3482182543554384 0.8339350180505414 0.33872139287301745 0.032490974729241916 |
0 0.7164517792676638 0.5081227436823105 0.30049853876568683 0.03790613718411556 |
0 0.3629706034038165 0.509927797833935 0.06800756403644492 0.034296028880866414 |
0 0.6816572116211106 0.44314079422382674 0.1423414130995358 0.034296028880866414 |
0 0.2948729950060847 0.36101083032490977 0.06593433428707485 0.03249097472924184 |
0 0.44322524715200307 0.4052346570397112 0.25274828143378686 0.030685920577617338 |
0 0.22619139679038178 0.4467509025270758 0.3095250692921014 0.027075812274368262 |
0 0.5952405178694257 0.4909747292418773 0.5384637300111111 0.03249097472924184 |
0 0.4322361914374906 0.5315884476534296 0.5238116557250947 0.030685920577617338 |
0 0.5467055217969955 0.10920577617328518 0.060439806429818645 0.02346570397111913 |
0 0.5137383546534582 0.9151624548736461 0.06410282500132283 0.028880866425992763 |
0 0.5046942414369991 0.5081227436823105 0.8449194329488421 0.9584837545126355 |
0 0.3458128743862316 0.0351985559566787 0.05395661869856095 0.03068592057761733 |
0 0.3482654479634389 0.1759927797833935 0.05886176585297559 0.030685920577617303 |
0 0.7047061411842356 0.45758122743682306 0.05232156964708949 0.03068592057761727 |
0 0.6703701111033331 0.5036101083032491 0.06213186395591883 0.028880866425992836 |
0 0.4635364060921827 0.6435018050541517 0.060496814904447194 0.034296028880866414 |
0 0.34744792343770314 0.740072202166065 0.053956618698560985 0.032490974729241916 |
0 0.5550991529745892 0.5983754512635379 0.024525735772073176 0.030685920577617338 |
0 0.6662824884746541 0.5983754512635379 0.053956618698560915 0.034296028880866414 |
0 0.3114768443053292 0.5505415162454874 0.06049681490444716 0.03610108303249092 |
0 0.49214976449293474 0.3167870036101083 0.4480034401032031 0.03429602888086649 |
0 0.7472174165224956 0.361913357400722 0.26487794633839024 0.030685920577617338 |
0 0.1324389731691951 0.40974729241877256 0.1765852975589268 0.028880866425992763 |
0 0.2896512935883014 0.1750003605318566 0.05061867266591673 0.04896383144414642 |
0 0.8008998875140605 0.1750003605318566 0.10798650168728913 0.05259078192149058 |
0 0.35095613048368945 0.25116632055608434 0.48818897637795267 0.04533688096680226 |
0 0.22328458942632168 0.3273322805803121 0.2305961754780652 0.038082980012113875 |
0 0.8337795369344729 0.6379310344827587 0.02476610392093903 0.041742286751361206 |
0 0.5345768581211943 0.6787003610108303 0.2344323763189289 0.025270758122743615 |
0 0.5301368509939418 0.7779783393501805 0.16872027083559288 0.028880866425992906 |
0 0.2726164376133 0.7274368231046933 0.05150408267612832 0.028880866425992763 |
0 0.2717284361878496 0.7779783393501805 0.05683209122883131 0.028880866425992906 |
0 0.3303365302675818 0.9314079422382671 0.05328008552702936 0.025270758122743615 |
End of preview.
Sensitive Words Detection Dataset
This dataset contains 101 images annotated for object detection of sensitive words. The annotations use YOLO text format, where each row is:
class_id x_center y_center width height
All coordinates are normalized to the image width and height. The only class is:
0 sensitive_words
Files
images/: image files.labels/: YOLO annotation files with the same basename as each image.classes.txt: class list.data.yaml: YOLO dataset configuration.metadata.csv: per-image metadata, including image size, label path, split, and box count.notes.json: Label Studio export metadata.
Dataset Statistics
- Images: 101
- Label files: 101
- Classes: 1
- Bounding boxes: 830
- Images with no annotated sensitive words: 8
Empty label files indicate images with no annotated sensitive-word target.
Intended Use
This dataset is intended for research on visual detection of sensitive words in images, including object detection experiments and evaluation of OCR-adjacent content moderation systems.
Limitations
The dataset is small and should not be treated as representative of all languages, fonts, layouts, platforms, or sensitive-word policies. The class definition depends on the annotation guideline used during labeling, and downstream use should include additional validation before deployment.
Responsible AI Notes
Potential risks include false positives, false negatives, over-filtering of benign content, and policy bias if the dataset is used directly for automated moderation. This dataset should be used for research and evaluation rather than as the sole basis for high-stakes moderation decisions.
License
This dataset is released under the Creative Commons Attribution 4.0 International license (CC BY 4.0).
- Downloads last month
- 273