Datasets:
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: ValueError
Message: Invalid string class label musnad-letter-classification@4d36afe40fbd51cb6c765ef1cf214d3c54bdde59
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 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 musnad-letter-classification@4d36afe40fbd51cb6c765ef1cf214d3c54bdde59Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Musnad Letter Classification Dataset
A synthetic dataset for Ancient South Arabian (Yemeni Musnad) letter recognition.
Dataset Overview
- 32 Musnad letter classes
- 1,000 images per class
- 32,000 total images
- Image size: 96×96 pixels
- Grayscale PNG images
Generation Method
The dataset was generated using Unicode Musnad characters rendered with Noto Sans Old South Arabian font.
Augmentations include:
- Rotation
- Translation
- Gaussian blur
- Noise injection
- Font size variation
- Stroke thickness variation
Baseline CNN Results
A baseline CNN classifier was trained on this dataset.
- Classes: 32
- Total images: 32,000
- Training images: 25,600
- Validation images: 6,400
- Image size: 96×96 grayscale
- Best validation accuracy: 99.87%
- Final validation accuracy: 99.84%
Intended Uses
- Musnad OCR research
- Ancient script recognition
- Image classification
- Cultural heritage AI
- Low-resource language technologies
Limitations
This dataset is synthetic and does not represent real stone inscriptions, carving variations, weathering, lighting conditions, or archaeological artifacts.
Citation
If you use this dataset, please cite the dataset page and repository.
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