Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
-b.-kitaj_america-baseball.jpg: binary
__key__: string
__url__: string
jpg: null
to
{'jpg': Image(mode=None, decode=True), '__key__': Value('string'), '__url__': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2092, in _iter_arrow
pa_table = cast_table_to_features(pa_table, self.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2192, in cast_table_to_features
raise CastError(
datasets.table.CastError: Couldn't cast
-b.-kitaj_america-baseball.jpg: binary
__key__: string
__url__: string
jpg: null
to
{'jpg': Image(mode=None, decode=True), '__key__': Value('string'), '__url__': Value('string')}
because column names don't matchNeed 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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Check out the documentation for more information.
Wikiart dataset original and processed
The original dataset is divided into two subfolders (by genres and by styles)
The processed dataset is divided into abstract, figurative and absfig (abstract&figurative) artworks.
These are further divided into spurious, and filtered, where we considered spurious the monochromatic artworks that do not contain any figures, and filtered are all the other paintings.
license: mit
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