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 1898, 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 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, 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 1919, 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.
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1 0.191547 0.920696 0.088355 0.021509
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1 0.173829 0.920780 0.125379 0.021917
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1 0.865906 0.934582 0.030753 0.013918
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1 0.804910 0.926264 0.048216 0.017635
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1 0.508208 0.957371 0.027861 0.017328
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0 0.510266 0.083027 0.645016 0.029395
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2 0.300207 0.909570 0.214966 0.048811
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1 0.477177 0.942191 0.040187 0.017124
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0 0.789865 0.061456 0.105869 0.024528
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0 0.761800 0.084042 0.164899 0.024816
|
0 0.188008 0.079437 0.163517 0.026085
|
0 0.474183 0.082735 0.028197 0.016199
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0 0.847361 0.059088 0.027268 0.016125
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2 0.330261 0.944458 0.449237 0.027154
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0 0.203846 0.072385 0.248733 0.036978
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0 0.874938 0.053441 0.040620 0.016918
|
2 0.382636 0.915556 0.527349 0.064069
|
0 0.223629 0.058848 0.213450 0.028680
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2 0.306602 0.947418 0.342333 0.024492
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0 0.167326 0.065823 0.040355 0.016338
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0 0.882020 0.075209 0.077400 0.027132
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0 0.418389 0.059073 0.584815 0.039936
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0 0.740837 0.066680 0.219217 0.029558
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1 0.123451 0.945865 0.040518 0.014447
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0 0.472345 0.120456 0.617985 0.032541
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0 0.232849 0.073353 0.203398 0.024148
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1 0.123092 0.895986 0.033802 0.014556
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0 0.745797 0.068114 0.230020 0.020079
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1 0.879396 0.892510 0.033866 0.015684
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0 0.456834 0.125526 0.595747 0.030246
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0 0.771318 0.070135 0.041044 0.016328
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1 0.493608 0.962806 0.077149 0.016028
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0 0.503758 0.073124 0.827571 0.038457
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0 0.527869 0.068749 0.509666 0.022961
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1 0.155498 0.951088 0.126869 0.019716
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1 0.900657 0.936838 0.036127 0.012389
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1 0.089537 0.931751 0.034994 0.014688
|
0 0.498108 0.059812 0.258108 0.038457
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0 0.464748 0.054431 0.179066 0.020125
|
3 0.475380 0.959971 0.041951 0.019570
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0 0.728583 0.089710 0.240162 0.025068
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1 0.506794 0.928941 0.066049 0.016266
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0 0.499622 0.088362 0.297059 0.021410
|
1 0.151841 0.931603 0.032861 0.017828
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0 0.555430 0.074166 0.319287 0.030995
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1 0.103084 0.945643 0.029367 0.013568
|
0 0.491475 0.070166 0.677514 0.035499
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0 0.571872 0.580464 0.856256 0.630108
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2 0.482646 0.817057 0.810395 0.159056
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1 0.926345 0.944180 0.034498 0.015094
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0 0.524567 0.063510 0.727830 0.042895
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1 0.817372 0.929079 0.045223 0.015913
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1 0.474673 0.913407 0.074723 0.014136
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0 0.448245 0.059812 0.144274 0.044374
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1 0.460675 0.944679 0.073080 0.014451
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0 0.443361 0.090874 0.133661 0.035499
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1 0.504986 0.908453 0.090093 0.014121
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0 0.507937 0.056114 0.129221 0.045853
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1 0.816984 0.950735 0.097030 0.015311
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2 0.244685 0.919941 0.257896 0.017519
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0 0.495025 0.131550 0.802448 0.028103
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1 0.536787 0.946546 0.058615 0.021053
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0 0.228078 0.074603 0.151300 0.035499
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0 0.542190 0.078488 0.178163 0.025297
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0 0.156551 0.077965 0.031239 0.016637
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1 0.496029 0.899466 0.437410 0.036426
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0 0.486231 0.095587 0.362214 0.029200
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0 0.888275 0.092335 0.032941 0.016037
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2 0.487989 0.814894 0.763091 0.174839
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0 0.824607 0.096710 0.057741 0.020023
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0 0.273014 0.092353 0.348334 0.038457
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2 0.390577 0.873264 0.558385 0.080203
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0 0.812535 0.100496 0.056874 0.018132
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0 0.261477 0.101004 0.304769 0.024957
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1 0.850673 0.891363 0.028624 0.016286
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0 0.803511 0.085697 0.177979 0.034020
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0 0.258036 0.063445 0.304334 0.023595
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1 0.529844 0.940561 0.032746 0.016069
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0 0.281803 0.049014 0.233891 0.025825
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1 0.477130 0.963894 0.042207 0.017165
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0 0.644043 0.071024 0.323134 0.028105
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0 0.643782 0.070035 0.320194 0.026416
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1 0.492988 0.929249 0.031483 0.013219
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0 0.547967 0.092523 0.139815 0.021455
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1 0.551397 0.905374 0.098680 0.033126
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1 0.206462 0.929172 0.036886 0.017329
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0 0.324571 0.064362 0.330042 0.035851
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1 0.860074 0.495622 0.111510 0.055677
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0 0.732524 0.074603 0.178877 0.041416
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0 0.856606 0.067672 0.073132 0.019412
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0 0.499861 0.068852 0.065877 0.027253
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1 0.514953 0.943306 0.037433 0.014936
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0 0.179312 0.064078 0.174758 0.023068
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1 0.181125 0.918505 0.176272 0.023397
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0 0.148649 0.046638 0.118295 0.024239
|
1 0.495512 0.918402 0.038379 0.016415
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1 0.523112 0.955222 0.054809 0.016345
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0 0.475534 0.104059 0.731108 0.062276
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2 0.272784 0.918804 0.314796 0.021939
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0 0.525526 0.067423 0.107536 0.024511
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End of preview.
YAML Metadata
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Tibetan Header/Footer (YOLO detection dataset)
This dataset contains page images annotated for header/footer-related page layout elements.
Hosted on Hugging Face: openpecha/Tibetan-header-footer.
Contents
- Task: object detection
- Format: YOLO text labels (
class x_center y_center width height, all normalized to[0,1]) - Images:
313total- Train:
251 - Val:
62
- Train:
- Classes (nc=4):
0:header1:footer2:footnote3:page_number
Folder structure
images/
train/ # .jpg
val/ # .jpg
label/
train/ # .txt (YOLO)
val/ # .txt (YOLO)
data.yaml
How it was produced
Annotations were not created purely by hand from scratch.
- Step 1 (model inference): bounding boxes were generated by running inference on the page images using:
- DocLayout-YOLO
- PP-DocLayout
- Step 2 (manual correction): the model outputs were then manually corrected using the Ultralytics annotation web app (Ultralytics Hub).
Notes
- Each image
X.jpghas a corresponding label filelabel/{train|val}/X.txt. - Images may contain multiple boxes across classes.
License
MIT
license: mit
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