The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Buffer overflow caught - possible malformed input file.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Buffer overflow caught - possible malformed input file.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Disclaimer: All passport images and associated data in this dataset are synthetically generated and do not correspond to real individuals. Any names, numbers, or personal details are fictional and used solely for research and development purposes.
Introduction - Russia
The Synthetic Russia Passports Dataset features over 1,000 AI-generated passport images crafted for training OCR and computer vision models on identity documents. Since every entry is fully synthetic, the dataset includes no genuine personal data or biometric details, offering a privacy-safe basis for building identity verification, KYC, and fraud-prevention workflows. - Get the data
The dataset can be expanded on request — extra images and metadata can be tailored to your specifications, usually within one week.
Images are taken on either a plain white backdrop or a variety of lifelike settings — such as desks, walls, and other common surfaces — allowing models to adapt more reliably to real-world deployments.
Coverage extends to 50+ countries (including Ukraine, Poland, Czech Republic, Hungary, Romania, and more). Submit a request via the website to learn more.
Every record is accompanied by detailed structured metadata covering the document's personal fields — passport number, full name, signature, date of birth, sex, place of birth, issuing authority, nationality, document type, and the machine-readable zone (MRZ) — alongside technical attributes such as resolution and category.
Dataset general info
| Characteristic | Data |
|---|---|
| Description | Synthetic passport images with detailed metadata for ML model training in PII extraction |
| Data types | Image + structured metadata |
| Tasks | OCR, Computer Vision |
| Total number of files | 1000+ (scalable on request) |
| Labeling | Passport Number, Passport Number (split), Surname, Given Name, Signature, Date of Birth, Date of Issue, Date of Expiry, Sex, Place of Birth, Issuing Authority, Nationality, Nationality Code, Document Type, MRZ |
| Gender | Male, Female |
| Backgrounds | White and varied (desk, wall, and other surfaces) |
| Countries | 50+ available (Ukraine, Poland, Czech Republic, Hungary, Romania, and more — on request) |
| Image format | JPG |
| Data generation | AI-generated |
| Source of images | AI-generated |
The dataset comprises 1,000+ synthetic passport images, each tied to a complete identity-style record and structured annotations. Additional samples can be produced on request within one week, and the imagery covers both clean white scenes and varied background environments.
Metadata fields include:
| Field | Example |
|---|---|
| Passport number | 773781858 |
| Passport number (split) | 7 7 3 7 8 1 8 5 8 |
| Surname and given name | IVANOV ALEKSEY |
| Signature | A. Ivanov |
| Date of birth | 23 JAN 1980 |
| Date of issue | 28 FEB 2019 |
| Date of expiry | 28 FEB 2029 |
| Sex | M |
| Place of birth | CHELYABINSK |
| Issuing authority | MVD 16001 |
| Nationality | RUSSIA |
| Nationality code | RUS |
| Document type | P |
| Machine-readable zone (MRZ) | P<RUSIVANOV<<ALEKSEY<<<<<<<<<<<<<<<<<<<<<<<<77<3781856RUS8001232M2902289<<<<<<<<<<<<<<08 |
Use cases - Russia
Training document verification systems
Banks, fintech providers, and border-control units can use this dataset to train models that authenticate identity papers across diverse real-world conditions. Structured metadata enables accurate field extraction and validation, while varied backgrounds boost robustness in production deployments.
Building fraud detection pipelines
Compliance and security groups can draw on these synthetic records to build high-quality training corpora without involving genuine travel documents. Full passport field coverage and complete MRZ strings make it possible to model and stress-test both valid records and edge-case anomalies.
FAQ
Is this real-world or synthetic data?
All images are AI-generated and contain no biometric data or personal information tied to real individuals.
Can I request a custom dataset size?
Yes — the dataset is scalable, and additional samples can be generated based on your requirements within one week.
Can I request country-specific data?
Yes — support for 50+ countries is available. Please submit a request to get detailed coverage and samples.
Can I request a sample before purchasing?
Yes — free samples are available so you can evaluate image quality, metadata structure, and variation coverage before committing.
How is the dataset delivered?
After purchase, the dataset is delivered via secure AWS cloud infrastructure compliant with ISO 27001 and ISO 27701.
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