Datasets:
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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/python3.14/site-packages/datasets/builder.py", line 1848, 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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, 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 |
|---|
cabbage |
capitata |
damaged |
1 0.688426 0.347917 0.162037 0.066667 |
1 0.614352 0.588542 0.152778 0.072917 |
1 0.922685 0.641146 0.150926 0.087500 |
1 0.397685 0.771094 0.156481 0.082812 |
1 0.176852 0.767448 0.111111 0.058854 |
1 0.264815 0.579948 0.111111 0.058854 |
1 0.123611 0.466667 0.119444 0.058333 |
1 0.159722 0.298958 0.134259 0.062500 |
0 0.171759 0.301042 0.226852 0.117708 |
0 0.686111 0.351562 0.255556 0.134375 |
0 0.147685 0.463542 0.219444 0.092708 |
0 0.300463 0.585417 0.182407 0.095833 |
0 0.599074 0.598698 0.270370 0.127604 |
0 0.898148 0.638542 0.203704 0.135417 |
0 0.406481 0.774740 0.220370 0.122396 |
0 0.161111 0.771094 0.187037 0.120313 |
2 0.626389 0.670573 0.063889 0.022396 |
2 0.816204 0.695573 0.049074 0.026562 |
2 0.642130 0.460417 0.073148 0.046875 |
2 0.729167 0.463542 0.030556 0.021875 |
2 0.857407 0.439323 0.072222 0.027604 |
2 0.435648 0.451562 0.041667 0.026042 |
2 0.346759 0.541667 0.058333 0.021875 |
2 0.526852 0.178646 0.046296 0.019792 |
2 0.866204 0.329427 0.045370 0.028646 |
2 0.918056 0.122656 0.043519 0.029687 |
1 0.941204 0.634115 0.117593 0.073438 |
1 0.671296 0.590365 0.162963 0.074479 |
1 0.414815 0.768490 0.140741 0.083854 |
1 0.206019 0.774740 0.130556 0.079687 |
1 0.290741 0.579688 0.125926 0.065625 |
1 0.130093 0.466667 0.126852 0.075000 |
1 0.304167 0.264062 0.121296 0.056250 |
1 0.741204 0.337240 0.182407 0.072396 |
0 0.301389 0.268490 0.243519 0.106771 |
0 0.143519 0.467187 0.216667 0.104167 |
0 0.290741 0.588542 0.203704 0.111458 |
0 0.681481 0.601042 0.305556 0.141667 |
0 0.918981 0.639062 0.160185 0.117708 |
0 0.425463 0.774740 0.184259 0.125521 |
0 0.189815 0.780990 0.227778 0.118229 |
0 0.747685 0.341667 0.269444 0.119792 |
2 0.685185 0.455990 0.053704 0.040104 |
2 0.785648 0.462500 0.063889 0.031250 |
2 0.675926 0.672396 0.050000 0.027083 |
2 0.462037 0.457031 0.051852 0.038021 |
2 0.548148 0.148698 0.085185 0.017188 |
2 0.686111 0.188542 0.048148 0.020833 |
2 0.188426 0.824479 0.034259 0.020833 |
1 0.572222 0.449740 0.162963 0.083854 |
1 0.495370 0.640365 0.125926 0.079687 |
1 0.327778 0.600260 0.120370 0.077604 |
1 0.526389 0.210417 0.137963 0.082292 |
1 0.827778 0.649740 0.194444 0.124479 |
1 0.662963 0.872917 0.170370 0.109375 |
0 0.834722 0.653385 0.306481 0.183854 |
0 0.670370 0.870833 0.290741 0.161458 |
0 0.511574 0.640365 0.193519 0.124479 |
0 0.318981 0.598698 0.189815 0.119271 |
0 0.578704 0.451042 0.259259 0.139583 |
0 0.528241 0.210156 0.299074 0.168229 |
1 0.933333 0.419792 0.131481 0.085417 |
0 0.903704 0.422396 0.192593 0.137500 |
0 0.797685 0.097135 0.299074 0.168229 |
2 0.287963 0.298438 0.079630 0.030208 |
2 0.218519 0.447917 0.079630 0.030208 |
2 0.262963 0.094792 0.079630 0.030208 |
2 0.749074 0.164583 0.079630 0.030208 |
2 0.564352 0.348177 0.041667 0.028646 |
2 0.569907 0.662760 0.041667 0.028646 |
2 0.576389 0.740365 0.078704 0.025521 |
0 0.494907 0.131250 0.199074 0.125000 |
0 0.566667 0.254167 0.181481 0.104167 |
0 0.148148 0.206771 0.177778 0.132292 |
0 0.820833 0.219271 0.217593 0.131250 |
0 0.624074 0.584635 0.244444 0.148438 |
0 0.322685 0.621615 0.156481 0.118229 |
0 0.084259 0.590885 0.166667 0.102604 |
0 0.187037 0.414062 0.142593 0.104167 |
0 0.922222 0.571094 0.155556 0.101562 |
0 0.823611 0.798438 0.176852 0.151042 |
0 0.551389 0.773438 0.162037 0.098958 |
0 0.341204 0.772917 0.197222 0.106250 |
0 0.118056 0.931510 0.219444 0.136979 |
0 0.087037 0.743229 0.172222 0.111458 |
2 0.606944 0.104688 0.043519 0.026042 |
1 0.500000 0.135156 0.116667 0.081771 |
1 0.140741 0.209635 0.135185 0.089063 |
1 0.822685 0.215104 0.147222 0.098958 |
1 0.570833 0.253906 0.108333 0.075521 |
0 0.360185 0.347135 0.140741 0.109896 |
1 0.362963 0.341927 0.070370 0.083854 |
1 0.183796 0.417187 0.089815 0.069792 |
2 0.776389 0.077344 0.050926 0.032813 |
2 0.298148 0.120052 0.018519 0.009896 |
2 0.400463 0.284115 0.025000 0.025521 |
2 0.740278 0.297396 0.043519 0.017708 |
End of preview.
White Cabbage Leaf Damage Dataset
Description
This dataset contains images of white cabbage leaves with various types of damage. It is designed for researchers and developers working on agricultural computer vision and plant pathology detection.
Dataset Structure
The dataset is organized into folders representing different classes of leaf damage or healthy states.
Usage
You can use this dataset with the datasets library:
from datasets import load_dataset
dataset = load_dataset("Arko007/white-cabbage-leaf-damage")
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