The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label BullyingAct@c713531fbe029faadb16d434ba6660de73dbdd89
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2365, in __iter__
example = _apply_feature_types_on_example(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2282, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label BullyingAct@c713531fbe029faadb16d434ba6660de73dbdd89Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Data Description
BullyingAct dataset was created to train models for detecting bullying behavior in school environments. Due to the lack of publicly available datasets focused on bullying detection, we generated this data ourselves by simulating various scenarios in a controlled school environment. The dataset contains images depicting different school activities, with a subset specifically illustrating instances of bullying or not, labeled accordingly for classification tasks.
Data Collection Process
The images were collected by enacting different scenarios within a school setting, involving actors who simulated bullying and non-bullying situations. These scenarios were designed to capture various forms of bullying, including physical confrontations, intimidation, and exclusion, as well as normal school activities without any bullying behavior for training tasks.
Dataset Contents
There are two categories in the dataset. One is bullying and the other one is normal.
Bullying: This category includes over [86] images of staged school interactions.
Normal: This category includes [17] images. The reason we have no many images in this category is that users can add any normal images as they want.
Usage
This dataset is intended for training and evaluating image classification models for bullying detection. It can also be used for related tasks such as object detection or scene understanding in a school context. The goal is to help develop technologies that can assist in early detection and intervention in bullying incidents.
Ethical Considerations
The data collection was conducted in a responsible manner, with consent from all participants involved in the simulations. No real bullying was conducted during data collection. This dataset should be used with ethical considerations in mind, particularly in regard to privacy and the potential implications of deploying AI models for surveillance in educational environments.
Citation
If you use this dataset, please cite it as follows:
[Zoooora/BullyingAct]
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