Datasets:
male list | female list |
|---|---|
[
{
"pass_num": "VJ1003552",
"surname": "MARTINEZ",
"given_name": "Bernard, Sylvain",
"signature": "Bernard\rMartinez",
"date_of_birth": "22 02 1992",
"date_of_issue": "15 06 2020",
"date_of_expiry": "15 06 2030",
"sex": "M",
"place_of_birth": "MARSEILLE",
"authority": "Préfect... | [
{
"pass_num": "XH4504370",
"surname": "COLIN",
"given_name": "Emmanuelle, Christiane",
"signature": "Emmanuelle\rColin",
"date_of_birth": "01 10 2001",
"date_of_issue": "17 09 2020",
"date_of_expiry": "17 09 2030",
"sex": "F",
"place_of_birth": "TOULOUSE",
"authority": "Préfe... |
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
The Synthetic France Passports Dataset features over 1,000 AI-generated passport images crafted for training OCR and computer vision models on identity documents. Because every record is fully synthetic — containing no real personal information or biometric data — the dataset offers a privacy-compliant foundation for developing identity verification workflows and fraud detection systems. - Get the data This collection is fully scalable: extra images and metadata can be produced according to your specifications, with new batches typically delivered within one week. The images come with both clean white backgrounds and a wide range of realistic settings — desks, walls, and other everyday surfaces — which helps models generalize more effectively to real-world conditions.
Coverage spans 50+ countries (including Germany, Spain, Belgium, Netherlands, Switzerland, and more). Please submit a request on the website to learn more.
Every image is accompanied by detailed structured metadata, covering personal document fields such as passport number, full name, signature, date of birth, sex, place of birth, issuing authority, nationality, document type, and machine-readable zone (MRZ), in addition to technical attributes including 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 (Germany, Spain, Belgium, Netherlands, Switzerland, and more — on request) |
| Image format | JPG |
| Data generation | AI-generated |
| Source of images | AI-generated |
The dataset consists of 1000+ synthetic passport images, each associated with complete identity-like records and structured annotations. Additional data can be generated upon request within one week. The images cover both clean white and diverse background scenarios.
Metadata fields include:
Metadata fields include:
| Field | Example |
|---|---|
| Passport number | VJ1003552 |
| Passport number (split) | V J 1 0 0 3 5 5 2 |
| Surname and given name | MARTINEZ BERNARD, SYLVAIN |
| Signature | Bernard Martinez |
| Date of birth | 22 02 1992 |
| Date of issue | 15 06 2020 |
| Date of expiry | 15 06 2030 |
| Sex | M |
| Place of birth | MARSEILLE |
| Issuing authority | Préfecture de Seine-Maritime |
| Nationality | FRANCE |
| Nationality code | FRA |
| Document type | P |
| Machine-readable zone (MRZ) | P<FRAMARTINEZ<<<RIC<<<<<<<<<<<<<<<<<<<<<<<<< |
Use cases
Training document verification systems Financial institutions, fintech providers, and border-control authorities can leverage this dataset to teach models how to validate identity documents across a wide variety of real-world conditions. The structured metadata supports precise field extraction and verification, while the diverse background settings strengthen overall model robustness.
Building fraud detection pipelines Security and compliance teams can rely on these synthetic samples to assemble realistic training datasets without the legal exposure of using authentic documents. With every passport field and MRZ string available, both legitimate records and anomalous patterns can be simulated for thorough fraud-detection coverage.
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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