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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:    FileNotFoundError
Message:      datasets/leitro/Copiale_Lines@5dcdadc84ed5b9453c3f3bff3a8efee19e8dbba9/train/1-1.png
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 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2159, in _apply_feature_types_on_example
                  decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2204, in decode_example
                  column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 188, in decode_example
                  with xopen(path, "rb", download_config=download_config) as f:
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 977, in xopen
                  file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
                  return self.__enter__()
                         ^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
                  f = self.fs.open(self.path, mode=mode)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
                  f = self._open(
                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 275, in _open
                  return HfFileSystemFile(self, path, mode=mode, revision=revision, block_size=block_size, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 947, in __init__
                  self.details = fs.info(self.resolved_path.unresolve(), expand_info=False)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 716, in info
                  _raise_file_not_found(path, None)
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 1138, in _raise_file_not_found
                  raise FileNotFoundError(msg) from err
              FileNotFoundError: datasets/leitro/Copiale_Lines@5dcdadc84ed5b9453c3f3bff3a8efee19e8dbba9/train/1-1.png

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Copiale Lines

Copiale Lines is a line-level image-to-text dataset for historical cipher decipherment. It contains cropped line images from the Copiale manuscript paired with plaintext ground truth.

This dataset is used in the paper Learning to Decipher from Pixels: A Case Study of Copiale (HistoCrypt 2026).

Dataset Structure

The dataset is split into:

  • train: 1,269 samples
  • valid: 175 samples
  • test: 370 samples

Each split contains:

  • images/*.png: cropped line images
  • metadata.csv: filename and plaintext transcription

The corresponding source split files are train.gt, valid.gt, and test.gt, where each line is:

image_id<TAB>groundtruth

Example

1-2.png,gesetz buchs

corresponds to the image:

train/images/1-2.png

Intended Use

This dataset is intended for research on handwritten cipher recognition, image-to-text modeling, and transcription-free decipherment.

Citation

@inproceedings{kang2026learning,
  title     = {Learning to Decipher from Pixels: A Case Study of Copiale},
  author    = {Kang, Lei and De Gregorio, Giuseppe and Heil, Raphaela and Fornés, Alicia and Megyesi, Beáta},
  booktitle = {International Conference on Historical Cryptology (HistoCrypt)},
  year      = {2026}
}

Acknowledgements

This dataset is derived in part from materials related to Decipherment of Historical Manuscripts, a historical manuscript studied within the project "The Copiale Cipher" at Stockholm University. We acknowledge and thank the original project for making these resources available.

We also gratefully acknowledge financial support from Riksbankens Jubileumsfond under grant M24-0028, "Echoes of History: Analysis and Decipherment of Historical Writings (DESCRYPT)", which supported the development of this dataset.

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