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fastmrz

Extracts the Machine Readable Zone (MRZ) data from document images

  • 2.0.1
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Fast MRZ

License Downloads Python CodeQL PyPI

FastMRZ is an open-source Python package that extracts the Machine Readable Zone (MRZ) from passports and other documents. FastMRZ accepts various input formats such as Image, Base64 string, MRZ string, or NumPy array.

FeaturesBuilt WithPrerequisitesInstallationExampleWikiToDoContributing

️✨Features:

  • 👁️Detects and extracts the MRZ region from document images
  • ️🔍Contour detection to accurately identify the MRZ area
  • 🪄Custom trained models using ONNX
  • 🆗Contains checksum logics for data validation
  • 📤Outputs the extracted MRZ region as text/json

🛠️Built With

OpenCV Tesseract OCR NumPy ONNX

🚨Prerequisites

  • Install Tesseract OCR engine. And set PATH variable with the executable and ensure that tesseract can be reached from the command line.

⚙️Installation

  1. Install fastmrz

    pip install fastmrz
    

    This can be done through conda too if you prefer.

    conda create -n fastmrz tesseract -c conda-forge
    conda activate fastmrz
    
  2. Copy the mrz.traineddata file from the tessdata folder of the repository into the tessdata folder of the Tesseract installation on YOUR MACHINE

💡Example

from fastmrz import FastMRZ
import json

fast_mrz = FastMRZ()
# Pass file path of installed Tesseract OCR, incase if not added to PATH variable
# fast_mrz = FastMRZ(tesseract_path=r'/opt/homebrew/Cellar/tesseract/5.3.4_1/bin/tesseract') # Default path in Mac
# fast_mrz = FastMRZ(tesseract_path=r'C:\\Program Files\\Tesseract-OCR\\tesseract.exe') # Default path in Windows
passport_mrz = fast_mrz.get_details("../data/passport_uk.jpg")
print("JSON:")
print(json.dumps(passport_mrz, indent=4))

print("\n")

passport_mrz = fast_mrz.get_details("../data/passport_uk.jpg", ignore_parse=True)
print("TEXT:")
print(passport_mrz)

OUTPUT:

JSON:
{
    "mrz_type": "TD3",
    "document_code": "P",
    "issuer_code": "GBR",
    "surname": "PUDARSAN",
    "given_name": "HENERT",
    "document_number": "707797979",
    "document_number_checkdigit": "2",
    "nationality_code": "GBR",
    "birth_date": "1995-05-20",
    "sex": "M",
    "expiry_date": "2017-04-22",
    "optional_data": "",
    "mrz_text": "P<GBRPUDARSAN<<HENERT<<<<<<<<<<<<<<<<<<<<<<<\n7077979792GBR9505209M1704224<<<<<<<<<<<<<<00",
    "status": "SUCCESS"
}


TEXT:
P<GBRPUDARSAN<<HENERT<<<<<<<<<<<<<<<<<<<<<<<
7077979792GBR9505209M1704224<<<<<<<<<<<<<<00

📃Wiki

MRZ Types & Format

The standard for MRZ code is strictly regulated and has to comply with Doc 9303. Machine Readable Travel Documents published by the International Civil Aviation Organization.

There are currently several types of ICAO standard machine-readable zones, which vary in the number of lines and characters in each line:

  • TD-1 (e.g. citizen’s identification card, EU ID card, US Green Card): consists of 3 lines, 30 characters each.
  • TD-2 (e.g. Romania ID, old type of German ID), and MRV-B (machine-readable visas type B — e.g. Schengen visa): consists of 2 lines, 36 characters each.
  • TD-3 (all international passports, also known as MRP), and MRV-A (machine-readable visas type A — issued by the USA, Japan, China, and others): consist of 2 lines, 44 characters each.

Now, based on the example of a national passport, let us take a closer look at the MRZ composition.

MRZ fields distribution

MRZ GIF

✅ToDo

  • Include mrva and mrvb documents
  • Add wiki page
  • Support numpy array as input
  • Support mrz text as input
  • Support base64 as input
  • Support pdf as input
  • Function to return mrz text as output
  • Bulk process
  • Train Tesseract model with additional data
  • Add function parameter - include_checkdigit
  • Add function - get_mrz_image
  • Add function - validate_mrz
  • Add function - generate_mrz
  • Extract face image
  • Add documentation page

🤝 Contributing

Contributions are welcome! Here's how you can help:

  1. Fork the repository
  2. Create a new branch (git checkout -b feature/amazing-feature)
  3. Make your changes
  4. Commit your changes (git commit -m 'feat: add amazing feature')
  5. Push to the branch (git push origin feature/amazing-feature)
  6. Open a Pull Request

⚖️License

Distributed under the AGPL-3.0 License. See LICENSE for more information.

🙏Show your support

Give a ⭐️ if this project helped you!

🚀Who's Using It?

We’d love to know who’s using fastmrz! If your company or project uses this package, feel free to share your story. You can:

  • Open an issue with the title "We are using fastmrz!" and include your project or company name.

Thank you for supporting fastmrz! 🤟

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