Skip to main content

A robust Python library for extracting information from passports using OCR (Tesseract) and MRZ parsing.

Project description

This is a mockup library used for OCR of identity documents.

Passport

A Python library for extracting information from passports using OCR (Tesseract). It supports parsing MRZ (Machine Readable Zone) and extracting additional fields like "Place of Issue" and "Date of Issue" from the visual zone.

Features

  • Robust MRZ Parsing: Handles common OCR errors, corrects line lengths, and supports various MRZ formats (TD1, TD2, TD3).
  • Full Text Extraction: Extracts non-MRZ fields like Place of Issue and Date of Issue.
  • Data Formatting:
    • Dates are standardized to dd-MM-YYYY.
    • Country codes are converted to full country names (e.g., VNM -> Vietnam).
    • Names are converted to Title Case (e.g., NGUYEN VAN A -> Nguyen Van A).
  • Input Flexibility: Accepts image file paths or Base64 encoded strings.
  • Fallback Logic: If Date of Issue is missing, it can infer it from Expiry Date (Expiry - 10 years).

Prerequisites

You need to have Tesseract OCR installed on your system.

Linux (Ubuntu/Debian)

sudo apt-get update
sudo apt-get install tesseract-ocr libtesseract-dev

Linux (Rocky/RHEL/CentOS)

sudo dnf install epel-release
sudo dnf install tesseract

[!NOTE] If you encounter version conflicts with language packs, installing just tesseract is often sufficient as it usually includes English data. If you need other languages, ensure the version matches the installed tesseract version.

macOS

brew install tesseract

Windows

Download and install the installer from UB-Mannheim/tesseract.

Installation

  1. Clone this repository.
  2. Install Python dependencies:
pip install m-ocr-mockup

Usage

Basic Usage (File Path)

from m_identify_ocr import read_passport

# Path to your passport image
image_path = "path/to/passport.jpg"

result = read_passport(image_path)

print(result)

Advanced Usage (Base64)

You can pass a Base64 string directly (with or without the data:image/...;base64, header).

from m_identify_ocr import read_passport

# Your base64 string
base64_string = "data:image/jpeg;base64,/9j/4AAQSkZJRg..."

result = read_passport(base64_string)

print(result)

Output Format

The library returns a dictionary with the extracted fields:

{
    'fullname': '',       # Combined Surname + Name (Title Case)
    'surname': '',
    'name': '',
    'sex': 'M',                      # M or F
    'birth_date': '',      # dd-MM-YYYY
    'expiry_date': '',     # dd-MM-YYYY
    'date_of_issue': '',   # dd-MM-YYYY (Extracted or Calculated)
    'place_of_issue': '', # Extracted from visual zone
    'document_number': '',
    'nationality': '',        # Full country name
    'country': '',            # Issuing country
    'type': '',                   # Passport type (TD3 is standard)
    'valid': True,                   # True if MRZ checksums are valid
    'raw_mrz': [...]                 # List of MRZ lines (for debugging)
}

Notes

  • Image Quality: High-resolution, glare-free images work best.
  • Language Support: The library uses Tesseract's English model (eng) by default. It works well for most passports (including Vietnamese) as they are bilingual.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

m_identify_ocr-1.0.0.tar.gz (16.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

m_identify_ocr-1.0.0-py3-none-any.whl (15.4 kB view details)

Uploaded Python 3

File details

Details for the file m_identify_ocr-1.0.0.tar.gz.

File metadata

  • Download URL: m_identify_ocr-1.0.0.tar.gz
  • Upload date:
  • Size: 16.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for m_identify_ocr-1.0.0.tar.gz
Algorithm Hash digest
SHA256 9e9876cded09bb7adee56189c4df1fc7fbc9ded9687c7e28ea2dab187351afdc
MD5 3055ed82ade38dda75586563db202fb3
BLAKE2b-256 a52f470f5c87b4365c25783d09f4dbdb253f504a8ea1ebcc50299dfc5f5787f6

See more details on using hashes here.

File details

Details for the file m_identify_ocr-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: m_identify_ocr-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 15.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for m_identify_ocr-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fbfdd8e75d92ef23ea743ae4fdafb0ff77613431e57ce1845992c0d7de616c8f
MD5 335cd0388c81560365cb05243ba83d07
BLAKE2b-256 d4a5f4487bcd9bc7e9e6460489f1bb9f6cd435992191ce7a83bfe7e11d32ab7e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page