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Synthetic USA Driver License Dataset

Synthetic USA Driver License Dataset features 5,000 high-quality, AI-generated images of U.S. driver licenses from multiple states, including California, Texas, and New York. Designed for OCR, data extraction, and identity verification model training, this synthetic dataset ensures realistic detail, balanced demographics, and secure handling of personally identifiable information.

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  • Images
    5 000
USA driver license dataset
  • PII
  • Data generation
  • Security
  • Anti-spoofing
  • Computer Vision

Synthetic USA Driver License Dataset features 5,000 high-quality, AI-generated images of U.S. driver licenses from multiple states, including California, Texas, and New York. Designed for OCR, data extraction, and identity verification model training, this synthetic dataset ensures realistic detail, balanced demographics, and secure handling of personally identifiable information.

Get in touch Download sample
  • PII
  • Data generation
  • Security
  • Anti-spoofing
  • Computer Vision
  • Images
    5 000

Dataset Info

Characteristic Data
Description Printed synthetic driver license images for training ML models in PII extraction
Data types Image
Tasks OCR, Computer Vision
Total number of files 5 000
Number of files in a set 96 (Angles - 3, Lighting - 4, Backgrounds - 4, Distances - 2)
States California, Florida, New York, Pennsylvania, Texas
Angles 0°, 25°, 45°
Lighting Natural-daylight, Office-LED, Warm-indoor, Dim-light
Backgrounds Neutral wall, Textured desk, Outdoor pavement, Docs-on-docs
Distance Close (80-90 % frame), Medium (50-60 %)
Labeling Metadata (License ID, Sample ID, Class, Gender, Age Group, Angle, Distance, Category, Resolution, Camera, Light Condition, Background, Timestamp)
Gender Male, Female
USA driver license dataset
USA driver license dataset
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Technical
Characteristics

Characteristic Data
Image Extensions JPNG
Data Type generated
Source and collection methodology: Data was AI-generated.

Dataset Use Cases

  • Financial Services

    Identity Verification for KYC Systems

    Synthetic USA Driver License Dataset provides realistic driver license images from multiple U.S. states to enhance Know Your Customer (KYC) and anti-fraud systems. Financial institutions can train OCR and verification models to accurately extract license numbers, names, and dates while maintaining full data security through synthetic generation.

  • Government & Transportation

    Automated License Processing and Record Management

    This dataset supports agencies and vehicle registration services in automating document verification and data extraction. Models trained on these synthetic driver license images can recognize document layouts, validate identification details, and improve accuracy in digital licensing systems without using personal information.

  • Technology & AI Development

    Training OCR and Data Extraction Models

    AI developers use this dataset to build and test machine learning algorithms for text extraction and identification. The variation in lighting, angles, and backgrounds helps train OCR systems to read license data accurately under real-world conditions, improving document scanning and mobile verification apps.

  • E-commerce & Digital Services

    Age and Identity Verification for Online Platforms

    Online marketplaces and digital service providers use synthetic driver license datasets to develop and test age verification tools. The data supports building reliable, privacy-safe systems for verifying users’ identities, ensuring compliance with regulations while enhancing user trust and onboarding security. 

FAQs

What is included in this dataset?
This dataset includes 5,000 high-resolution synthetic driver license images representing five U.S. states - California, Florida, New York, Pennsylvania, and Texas. Each image varies by lighting, background, distance, and viewing angle, providing robust training data for deep learning applications.
What types of annotations are provided?
Each image includes metadata fields such as License ID, Gender, Class, Age Group, Angle, Distance, and Lighting Condition. These detailed annotations improve model performance for OCR, text recognition, and data extraction tasks involving driver license imagery.
Can I request a sample of the dataset before purchasing?
Yes. Unidata provides free dataset samples for evaluation and testing purposes. These samples allow developers to assess data quality, structure, and labeling consistency before purchasing a dataset.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model. Free samples are available for preliminary testing, while full versions of our datasets are sold for commercial and research use, ensuring both accessibility and responsible data management.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. Unidata datasets comply with GDPR and international data protection laws. Since this dataset is synthetic, it contains no real personal data and adheres to ethical standards for privacy and data safety.
How are Unidata datasets stored?
All datasets are securely stored on AWS cloud servers to ensure high availability and compliance with ISO 27001 and ISO 27701 standards. This guarantees data integrity, scalability, and secure access for customers handling sensitive AI training material.
How long does it take to receive the dataset?
After submitting a purchase request, our team confirms details and provides documentation for approval. Once payment and agreement are complete, the dataset is delivered securely within 3–10 business days.
Is this a real-world dataset or synthetic data?
This is a synthetic dataset created to replicate real driver licenses while maintaining full data privacy. It enables safe model training for identity recognition, document verification, and text extraction without using sensitive or personal information.
Still have questions about using Unidata datasets? Read our user-guides

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