The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label invoice-checkmark-annotations@59b27098f177e455f6638b4cc87a9520a27ca039
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2368, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2285, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/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/python3.14/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/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label invoice-checkmark-annotations@59b27098f177e455f6638b4cc87a9520a27ca039Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Invoice Checkmark Annotations
Multilingual dataset of real invoices with human-drawn visual checkmarks/circles indicating verified key fields.
This dataset contains ~600 annotated invoice images (≈200 per language) in Ukrainian, Chinese, and Swedish. Each image shows real-world invoices where a human has manually added checkmarks (✓) or circles to highlight correctly extracted or verified fields (e.g. invoice number, buyer name, line totals, tax rate).
Every sample includes:
- The original scanned/photographed invoice image (with visible pen/circle markings)
- A JSON annotation file with:
file_name: path to the imagedata: list of extracted fields, each with:field: field name (e.g. "Unique Invoice Identifier", "Vendor Business Address", "Customer/Buyer Name", "Invoice Table Row 1: Line Total Amount", "Applied Tax Percentage")checked: boolean (trueif the field was marked)text: the extracted text string
Example annotation snippet:
{
"file_name": "UK/187.jpeg",
"data": [
{"field": "Unique Invoice Identifier", "checked": true, "text": "#213253"},
{"field": "Vendor Business Address", "checked": true, "text": "Аллея Беринга 494"},
{"field": "Customer/Buyer Name", "checked": true, "text": "Владилена Басок"},
{"field": "Invoice Table Row 1: Line Total Amount", "checked": true, "text": "1,314.17 грн"},
{"field": "Applied Tax Percentage", "checked": true, "text": "15"}
]
}
Why this dataset? Current public invoice datasets (e.g. FATURA, SROIE, CORD, etc.) focus mainly on clean text extraction or layout parsing. This is (to our knowledge) the first public dataset that includes explicit visual human verification signals — checkmarks and circles drawn directly on the invoice images. These visual cues are extremely valuable for training next-generation Document AI / VLM / KIE models that need to:
Understand human feedback/confirmation signals Detect visual annotations (underlines, circles, ticks) Improve reliability in high-stakes invoice processing (finance, logistics, auditing)
The idea was inspired by discussions on visual marking detection in complex documents (see the Hacker News thread on GLM-OCR, where users highlighted the need for better handling of pen/pencil marks like checkmarks in contract/invoice analysis pipelines).
Languages & Size
Ukrainian: ~200 images (UAH currency, Cyrillic addresses, typical UA invoice layouts)
Chinese: ~200 images
Swedish: ~200 images
Total: ≈600 images + corresponding JSON annotations.
Structure
textinvoice-checkmark-annotations/
├── Ukrainian/
│ ├── 001.jpeg
│ ├── 002.jpeg
│ ├── ...
│ └── label.txt
├── Chinese/
│ └── ...
├── Swedish/
│ └── ...
└── README.md
(You can load it easily with datasets.load_dataset("AlroWilde/invoice-checkmark-annotations") — split by language subfolders or add a language column if you prefer a flat/parquet structure later.) License Apache License 2.0 — feel free to use, modify, and build commercial models on top of this dataset. Attribution is appreciated but not required.
Related Project
This dataset pairs well with ocr-producer - a synthetic generator focused on documents.
Use real + synthetic data together with this checkmark-annotated set to train more robust KIE / visual-verification models.
Contact Questions, collaborations, other language support, or bug reports? Reach out at hi@support.alrowilde.com
Happy training! 🚀
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