Bulgaria Lichna karta (Лична карта) OCR Python SDK

Instantly extract data from Bulgarian IDs using our native Python library.

Steve HarringtonUpdated 2026-01-22
AI extracting data from a Bulgaria ID card
StructOCR engine analyzing a Bulgarian document in real-time.

Parsing Lichna karta (Лична карта) Challenges

Bulgarian Lichna karta presents unique OCR challenges. First, the mix of Cyrillic and Latin characters within the same document necessitates robust character recognition. Second, variations in font types and document layouts across different issuing periods can affect parsing accuracy.

Why StructOCR for Bulgaria

Our model is specifically trained on a large dataset of Bulgarian Lichna karta, ensuring high accuracy with both Cyrillic and Latin scripts. The Python SDK streamlines integration with a simple API, abstracting away complex OCR configurations and pre/post-processing steps.

Common Use Cases in Bulgaria

  • Digital Onboarding: Verify users for Fintech apps in Bulgaria.
  • Telecom Registration: Automate SIM card registration with Lichna karta (Лична карта).
  • Hotel Check-in: Speed up guest registration workflows.

Python SDK Integration

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

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

PYTHON EXAMPLE
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_bulgaria_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: Lichna karta (Лична карта)
    image_path = "bulgaria_national_id.jpg"

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

Technical Specs

  • Latency: < 5s (Average)
  • Uptime: 98.5% 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.
  • Blur Detection: Automatically rejects blurry images.
  • Fraud Check: Validates Lichna karta (Лична карта) 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": "BGR",
    "nationality": "БЪЛГАРИЯ",
    "document_number": "640123456",
    "card_series": "",
    "personal_number": "9001011234",
    "surname": "ИВАНОВ",
    "given_names": "ДИМИТЪР",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "СОФИЯ",
    "address": "ж.к. Младост 1, бл. 10, вх. А, ап. 3, София",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "МВР София"
  }
}

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.

More OCR Tutorials

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