UniDataPro/synthetic-printed-usa-passports-dataset
Passport Dataset - 9 600 Images The dataset comprises 9,600 high-quality synthetically generated passport images, providing a robust resource for training and verifying document analysis systems. Every passport is presented across 3 angles (0°, 25°, 45°), 4 lighting conditions (Natural-daylight, Office-LED, Warm-indoor, Dim-light), 4 backgrounds (Neutral wall, Textured desk, Outdoor pavement, Docs-on-docs), and 2 distances (Close, Medium), creating a rich and challenging dataset… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/synthetic-printed-usa-passports-dataset.
Passport Dataset - 9 600 Images
The dataset comprises 9,600 high-quality synthetically generated passport images, providing a robust resource for training and verifying document analysis systems. Every passport is presented across 3 angles (0°, 25°, 45°), 4 lighting conditions (Natural-daylight, Office-LED, Warm-indoor, Dim-light), 4 backgrounds (Neutral wall, Textured desk, Outdoor pavement, Docs-on-docs), and 2 distances (Close, Medium), creating a rich and challenging dataset for training robust machine learning models.
By utilizing this dataset, researchers can significantly advance their machine learning models for OCR, biometric verification, and identity verification systems. - [Get the data](https://unidata.pro/datasets/synthetic-printed-usa-passports-dataset/?utm_source=huggingface&utm_medium=referral&utm_campaign=synthetic-printed-usa-passports-dataset)
The dataset includes images generated to represent the main biographical information page from passports. Each file features synthetic personal information, including names, dates, and passport numbers, simulating real-world documents for analysis.
Frequently Asked Questions
Why are synthetic passport images valuable for OCR and identity verification research?
Unlike real identity documents, this synthetic passport dataset enables researchers to develop and evaluate OCR and document AI systems without exposing sensitive personal information.
How can the metadata improve machine learning experiments?
Beyond supporting OCR, the metadata enables controlled experiments that isolate factors affecting model performance. Researchers can compare recognition accuracy across lighting conditions, camera angles, capture distances, backgrounds, and demographic attributes to identify systematic failure cases. This level of annotation makes the USA passport dataset valuable for benchmarking document AI models, optimizing preprocessing pipelines, and evaluating robustness under realistic mobile document capture scenarios.
Who can benefit from this USA passport dataset?
This USA passport dataset is valuable for OCR developers, computer vision engineers, fintech companies, identity verification providers, cybersecurity teams, document AI researchers, academic institutions, and organizations building automated KYC and onboarding solutions.
💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.
Researchers and developers can utilize this dataset to explore detection technology and digital verification algorithms that aim to prevent identity fraud.