The Definitive Python SDK for Passport Data Extraction

Why Passport OCR is Difficult

Standard open-source OCR engines like Tesseract fail on real-world passport scans due to inherent complexities. Image defects such as camera glare, shadows, and non-uniform lighting degrade character recognition. Geometric distortions, including skew and rotation, misalign text regions, breaking parsing logic. The Machine Readable Zone (MRZ) itself, while standardized by ICAO 9303, requires precise parsing and checksum validation—a non-trivial task. Manually validating MRZ check digits or maintaining brittle RegEx patterns for dozens of international passport variations creates a significant engineering overhead that is both costly and error-prone.

Enterprise-Grade Extraction with StructOCR

StructOCR simplifies fragile, multi-step OCR pipelines into a single API call, ideal for processing identity documents. Our solution leverages pre-trained deep learning models optimized for specific document types, unlike generic OCR engines. The passport mrz ocr api automatically handles image pre-processing, including deskewing, denoising, and glare correction. Unlike Tesseract, which outputs unstructured text, StructOCR provides a standardized JSON with validated fields, eliminating manual parsing and format normalization. This robust solution is designed to support operations across international borders.

Production Use Cases

• Digital Onboarding (KYC): Reduce drop-off rates by pre-filling user data from Passports in < 2 seconds.
• Fraud Prevention: Detect tampered fonts or mismatched MRZ checksums automatically.
• Global Compliance: Handle Passports from 200+ jurisdictions without custom rules.

Implementation: Python SDK

The official Python SDK supports both MRZ and Visual Inspection Zone (VIZ) extraction. It automatically handles file encoding and parses fields like 'Place of Birth' that aren't available in the MRZ.

Prerequisite: pip install structocr

from structocr import StructOCR

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# 👉 https://structocr.com/register
# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")

def scan_passport():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    image_path = "passport.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        result = client.scan_passport(image_path)

        if result.get('success'):
            data = result['data']
            print("✅ Extraction Successful!")
            
            # Identity Data
            print(f"Passport #: {data.get('passport_number')}")
            print(f"Name:       {data.get('given_names')} {data.get('surname')}")
            print(f"Nation:     {data.get('nationality')} ({data.get('country_code')})")
            
            # Visual Zone Specifics (Not in MRZ)
            print(f"Birth Place:{data.get('place_of_birth')}")
            print(f"Issued At:  {data.get('place_of_issue')}")
            
            # Dates
            print(f"DOB:        {data.get('date_of_birth')} ({data.get('sex')})")
            print(f"Expiry:     {data.get('date_of_expiry')}")
        else:
            print(f"❌ Extraction Failed: {result.get('error')}")

    except Exception as e:
        # Handle SDK or Network errors
        print(f"An error occurred: {e}")

if __name__ == "__main__":
    scan_passport()

Sample JSON Output

StructOCR returns a normalized JSON object, regardless of the input image angle or quality.

{
  "success": true,
  "data": {
    "type": "passport",
    "country_code": "USA",
    "nationality": "UNITED STATES",
    "passport_number": "E12345678",
    "surname": "DOE",
    "given_names": "JOHN",
    "sex": "M",
    "date_of_birth": "1990-01-01",
    "place_of_birth": "NEW YORK, USA",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "place_of_issue": "PASSPORT AGENCY"
  }
}