Netherlands Identiteitskaart OCR Python SDK

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

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

Parsing Identiteitskaart Challenges

Netherlands Identiteitskaart poses OCR challenges due to variations in layout, especially with newer and older card designs. Additionally, the print quality on some cards can be inconsistent, leading to difficulties in accurate text recognition.

Why StructOCR for Netherlands

StructOCR's model is specifically trained on a large dataset of Dutch Identiteitskaart images, ensuring high accuracy. The Python SDK simplifies the integration process with just a few lines of code, allowing you to quickly extract data and automate your workflows.

Common Use Cases in Netherlands

  • Digital Onboarding: Verify users for Fintech apps in Netherlands.
  • Telecom Registration: Automate SIM card registration with Identiteitskaart.
  • 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_netherlands_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: Identiteitskaart
    image_path = "netherlands_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is a Dutch 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("✅ Netherlands 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_netherlands_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 Identiteitskaart 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": "NLD",
    "nationality": "NEDERLANDSE",
    "document_number": "SPECI2014",
    "card_series": "",
    "personal_number": "123456782",
    "surname": "DE VRIES",
    "given_names": "JAN",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "'S-GRAVENHAGE",
    "address": "Kalverstraat 10, 1012 PD Amsterdam",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "Burgemeester van Amsterdam"
  }
}

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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