Italy Carta di Identità OCR Python SDK

Instantly extract data from Italian IDs (CIE) using our native Python library.

AI extracting data from an Italy ID card
StructOCR engine analyzing an Italian Carta di Identità in real-time.

Parsing Carta di Identità Challenges

The Italian Carta di Identità, particularly the newer electronic version (CIE) and the legacy paper formats, poses unique OCR challenges. Accurately extracting the complex Codice Fiscale (tax code), multi-line addresses, and scanning the 3-line MRZ on the reverse side require highly specialized computer vision models.

Why StructOCR for Italy

StructOCR's model is specifically trained on a large dataset of Italian ID images, ensuring high accuracy for national id ocr extraction. The Python SDK simplifies the integration process with just a few lines of code, allowing you to instantly extract structural data, including the Codice Fiscale mapped to the personal number field, and automate your verification workflows.

Common Use Cases in Italy

  • Digital Onboarding: Verify users for Fintech apps and banking services in Italy.
  • SPID Integration: Automate document parsing for Italian digital identity frameworks.
  • Hotel Check-in: Speed up guest registration workflows complying with Italian security laws.

Live Demo: ID card scanner

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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_italy_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: Carta di Identità (CIE)
    image_path = "italy_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is an Italian 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("✅ Italy Extraction Successful!")
            
            # Basic Identity
            print(f"Region:      {data.get('country_code')}")
            print(f"Name:        {data.get('given_names')} {data.get('surname')}")
            print(f"ID Number:   {data.get('document_number')}")
            
            # Critical Field: Codice Fiscale
            print(f"Codice Fisc: {data.get('personal_number')}")
            
            # Demographics
            print(f"DOB:         {data.get('date_of_birth')} ({data.get('sex')})")
            print(f"Address:     {data.get('address')}")
            
            # MRZ Extraction (Present on the back of Italian CIE)
            additional = data.get('additional_fields', {})
            if additional.get('mrz_line_1'):
                print("\n🔍 MRZ Data Found:")
                print(additional.get('mrz_line_1'))
                print(additional.get('mrz_line_2'))
                print(additional.get('mrz_line_3') or "")
        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_italy_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 Italian special characters seamlessly.
  • MRZ Extraction: Automatically parses the 3-line Machine Readable Zone (MRZ) on the reverse of the electronic ID.
  • Codice Fiscale Extraction: Automatically extracts and validates the Italian tax code layout.
  • Multi-line Address Support: Capable of reconstructing complex multi-line addresses common on Italian cards.
  • Smart Crop & Blur Detection: Rejects blurry images and 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": "ITA",
    "nationality": "ITALIANA",
    "document_number": "CA00000AA",
    "card_series": "",
    "personal_number": "RSSMRA80A01H501U",
    "surname": "ROSSI",
    "given_names": "MARIO",
    "sex": "M",
    "date_of_birth": "1980-01-01",
    "place_of_birth": "ROMA",
    "address": "VIA ROMA 1, 00100 ROMA (RM)",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "COMUNE DI ROMA",
    "additional_fields": {
      "phone_number": null,
      "tramite_number": null,
      "ejemplar": null,
      "mrz_line_1": "I<ITACA00000AA6<<<<<<<<<<<<<<<",
      "mrz_line_2": "8001014M3001012ITA<<<<<<<<<<<4",
      "mrz_line_3": "ROSSI<<MARIO<<<<<<<<<<<<<<<<<<"
    }
  }
}

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 to comply with GDPR and Italian data protection laws.

How to handle errors?

The SDK result dictionary contains a 'success' boolean and an 'error' code (e.g., FILE_TOO_LARGE) if failed.

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