Ukraine National ID OCR Python SDK

Instantly extract data and MRZ from Ukrainian IDs using our native Python library.

AI extracting data from a Ukraine ID card
StructOCR engine analyzing a Ukrainian document and MRZ lines in real-time.

Parsing National ID Challenges

Ukrainian National IDs present unique challenges. First, the combination of Cyrillic and Latin script requires robust character recognition. Second, variations in layout across different issuing authorities can lead to parsing inconsistencies.

Why StructOCR for Ukraine

Our model is specifically trained on a large dataset of Ukrainian National IDs, ensuring high accuracy for both Cyrillic and Latin characters, making it ideal for national id ocr tasks. It also fully supports reading the Machine Readable Zone (MRZ) located on the reverse side for strict global identity verification. The Python SDK provides a simple and intuitive interface for information parsing, enabling seamless integration into your existing systems with minimal code to support kyc automation.

Common Use Cases in Ukraine

  • Digital Onboarding: Verify users for Fintech apps in Ukraine.
  • Telecom Registration: Automate SIM card registration with National ID.
  • Hotel Check-in: Speed up guest registration workflows.

Live Demo: ID card scanner

No registration required. Upload a file to test the extraction.

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Python SDK Integration

Install the SDK via pip: `pip install structocr`. Then use the following code.

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

from structocr import StructOCR

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

def scan_ukraine_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: National ID
    image_path = "ukraine_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is a Ukrainian document
        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("✅ Ukraine 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')}")

            # Machine Readable Zone (MRZ)
            additional = data.get('additional_fields', {})
            if additional.get('mrz_line_1'):
                print("\n--- MRZ Data ---")
                print(additional.get('mrz_line_1'))
                print(additional.get('mrz_line_2'))
                if additional.get('mrz_line_3'):
                    print(additional.get('mrz_line_3'))
        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_ukraine_id()

Technical Specs

  • Latency: < 4s (Average)
  • Uptime: 99.9% SLA
  • Security: AES-256 Encryption & SOC2 Compliant
  • Input: JPG, PNG, WebP (Max 4.5MB)
  • Output: JSON (Structured Data)

Key Features

  • Native Script Support: Reads English and local characters.
  • MRZ Parsing: Accurately extracts and validates the Machine Readable Zone lines for cross-checking.
  • Blur Detection: Automatically rejects blurry images.
  • Fraud Check: Validates National ID number format.
  • Smart Crop: Removes background noise automatically.

JSON Response Example

The SDK returns a Python dictionary matching this JSON structure.

{
  "success": true,
  "data": {
    "type": "national_id",
    "country_code": "UKR",
    "nationality": "УКРАЇНА / UKR",
    "document_number": "000123456",
    "card_series": "",
    "personal_number": "19900101-12345",
    "surname": "ШЕВЧЕНКО",
    "given_names": "ОЛЕКСАНДР",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "КИЇВ / KYIV",
    "address": "вул. Хрещатик, буд. 22, кв. 10, Київ",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "1234",
    "additional_fields": {
      "phone_number": null,
      "tramite_number": null,
      "ejemplar": null,
      "mrz_line_1": "I<UKR0001234560<<<<<<<<<<<<<<<",
      "mrz_line_2": "9005156M3001014UKR199001011234",
      "mrz_line_3": "SHEVCHENKO<<OLEKSANDR<<<<<<<<<"
    }
  }
}

Frequently Asked Questions

Does the Python SDK handle image uploads?

Yes, the SDK automatically handles base64 encoding and file uploads.

Is data stored?

No. Images are processed in-memory and deleted immediately.

How to handle errors?

The SDK result dictionary contains a 'success' boolean and an 'error' message if failed.

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