Python SDK for Enterprise-Grade National ID OCR

Why National ID OCR is Difficult

Generic OCR engines like Tesseract fail on National IDs due to inherent complexities. Laminate glare, shadows, and non-uniform lighting create artifacts that corrupt character recognition. User-submitted images often suffer from significant skew and rotation, requiring robust preprocessing. Furthermore, parsing extracted text is a brittle process. It involves maintaining complex RegEx patterns for dozens of ID layouts, which constantly change. Manually implementing logic to parse the Machine-Readable Zone (MRZ) and validate its check digits is error-prone and adds significant engineering overhead. These challenges lead to high error rates and unsustainable maintenance costs for in-house solutions.

Enterprise-Grade Extraction with StructOCR

StructOCR bypasses these challenges using specialized, pre-trained deep learning models. Our API handles the entire pipeline, from automatic image pre-processing—including perspective correction, glare removal, and denoising—to data extraction. Unlike Tesseract, which returns unstructured text lines, StructOCR's models are trained specifically on identity documents to locate and identify semantic fields. The result is a standardized, validated JSON object, eliminating the need for post-processing or manual data validation, delivering production-ready data directly to your application.

Production Use Cases

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

Implementation: Python SDK

The official Python SDK abstracts the API complexity. It automatically parses region-specific fields like CNP (Romania), CPF (Brazil), or NIN (Nigeria) into a standardized structure.

Prerequisite: pip install structocr

from structocr import StructOCR

# 💰 Save 30%+ vs competitors. Get 200 free requests instantly:
# 👉 https://structocr.com/register
# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")

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

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

        # Check success flag (SDK returns a dict matching the JSON response)
        if result.get('success'):
            data = result['data']
            print("✅ Extraction Successful!")
            
            # Basic Identity
            print(f"Region:     {data.get('country_code')} (Series: {data.get('card_series')})")
            print(f"Name:       {data.get('given_names')} {data.get('surname')}")
            print(f"ID Number:  {data.get('document_number')}")
            
            # Critical Field: Personal Identity Number (CNP/CPF/NIN)
            print(f"Personal #: {data.get('personal_number')}")
            
            # Demographics
            print(f"DOB:        {data.get('date_of_birth')} ({data.get('sex')})")
            print(f"Address:    {data.get('address')}")
        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_national_id()

Sample JSON Output

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

{
  "success": true,
  "data": {
    "type": "national_id",
    "country_code": "ROU",
    "nationality": "ROMANA",
    "document_number": "123456",
    "card_series": "KS",
    "personal_number": "1920319123456",
    "surname": "POPESCU",
    "given_names": "ANDREI",
    "sex": "M",
    "date_of_birth": "1992-03-19",
    "place_of_birth": "Jud. CS Mun. Reșița",
    "address": "Jud. CS Orș. Bocșa Str. Nucilor Nr. 15",
    "date_of_issue": "2020-05-10",
    "date_of_expiry": "2030-05-10",
    "issuing_authority": "SPCLEP Bocșa"
  }
}