Egypt National ID OCR Python SDK

Parsing National ID Challenges

1. Dual-Language Script: Egyptian IDs contain both right-to-left Arabic script for names and addresses, and left-to-right numerals. Standard OCR models often fail to correctly parse this mixed-script layout. 2. Encoded Data & Quality: The 14-digit National ID number embeds the date of birth, governorate, and gender. Validating this requires specific logic, not just text extraction. Furthermore, physical card wear, tear, and variable print quality can degrade accuracy.

Why StructOCR for Egypt

Our AI model is specifically pre-trained on tens of thousands of Egyptian National ID cards, ensuring exceptional accuracy with Arabic script and complex layouts for national id ocr. The Python SDK eliminates boilerplate code by handling API requests and image encoding, allowing you to seamlessly implement KYC automation into your application in minutes. Want to see it in action? Use the live demo widget below to test our ID OCR engine for free. For production usage, view our flexible pricing.

Common Use Cases in Egypt

• Digital Onboarding: Verify users for Fintech apps, digital banks, and online services in Egypt.
• Telecom Registration: Automate SIM card registration and user verification with National ID data.
• Hotel Check-in: Speed up guest registration and compliance workflows for the hospitality industry.

Python SDK Integration

Install the SDK via pip: `pip install structocr`. Then use the following code to connect to our ID OCR API. Prefer raw HTTP requests? Read the official API documentation.

Prerequisite: Python 3.6+ and `structocr` library installed.

from structocr import StructOCR

# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")

def scan_egypt_id():
    # Target: National ID
    image_path = "egypt_national_id.jpg"

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

        if result.get('success'):
            data = result['data']
            print("✅ Egypt 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
            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:
        print(f"An error occurred: {e}")

if __name__ == "__main__":
    scan_egypt_id()

JSON Response Example

The SDK returns a Python dictionary matching this JSON structure. Note the corrected dates for data consistency.

{
  "success": true,
  "data": {
    "type": "national_id",
    "country_code": "EGY",
    "nationality": "EGYPTIAN",
    "document_number": "JA1234567",
    "card_series": "null",
    "personal_number": "29101011200078",
    "surname": "محمد",
    "given_names": "أحمد حسن",
    "sex": "M",
    "date_of_birth": "1991-01-01",
    "place_of_birth": "null",
    "address": "١٥ ميدان التحرير، القاهرة",
    "date_of_issue": "null",
    "date_of_expiry": "null",
    "issuing_authority": "null"
  }
}