France Carte Nationale d'Identité OCR Python SDK

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

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

Parsing Carte Nationale d'Identité Challenges

Extracting information from French Carte Nationale d'Identité can be challenging due to variations in layout between different card versions and the presence of native French text and special characters, which require robust character recognition.

Why StructOCR for France

Our model is specifically trained on a large dataset of French Carte Nationale d'Identité. The StructOCR Python SDK provides a simple and intuitive interface, allowing you to integrate OCR functionality with just a few lines of code. It automatically handles image preprocessing and data extraction, simplifying the development process.

Common Use Cases in France

  • Digital Onboarding: Verify users for Fintech apps in France.
  • Telecom Registration: Automate SIM card registration with Carte Nationale d'Identité.
  • 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_france_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: Carte Nationale d'Identité
    image_path = "france_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is a French 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("✅ France 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_france_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 Carte Nationale d'Identité 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": "FRA",
    "nationality": "FRANÇAISE",
    "document_number": "180675301234",
    "card_series": "",
    "personal_number": "",
    "surname": "DUPONT",
    "given_names": "JEAN-PIERRE",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "LYON (69)",
    "address": "10 Avenue des Champs-Élysées, 75008 Paris",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "République Française"
  }
}

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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