Czech Republic Občanský průkaz OCR Python SDK

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

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

Parsing Občanský průkaz Challenges

Czech Občanský průkaz presents unique challenges. First, the presence of diacritics (ěščřžýáíé) requires robust character recognition. Second, the layout varies between different versions of the card, making fixed-template OCR unreliable.

Why StructOCR for Czech Republic

Our model is specifically trained on a large dataset of Czech Občanský průkaz images. The Python SDK provides a simple interface for sending images and receiving structured data, minimizing development time.

Common Use Cases in Czech Republic

  • Digital Onboarding: Verify users for Fintech apps in Czech Republic.
  • Telecom Registration: Automate SIM card registration with Občanský průkaz.
  • 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_czech_republic_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: Občanský průkaz
    image_path = "czech_republic_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is a Czech 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("✅ Czech Republic 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_czech_republic_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 Občanský průkaz 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": "CZE",
    "nationality": "ČESKÁ",
    "document_number": "123456789",
    "card_series": "",
    "personal_number": "900101/1234",
    "surname": "NOVÁK",
    "given_names": "PETR",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "PRAHA",
    "address": "Václavské náměstí 812/19, 110 00 Praha 1",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "Městský úřad Praha 1"
  }
}

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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