Netherlands Identiteitskaart OCR Python SDK
Instantly extract data from Dutch IDs using our native Python library.

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 for national id ocr extraction. The Python SDK simplifies the integration process with just a few lines of code, allowing you to quickly extract data, including the 14 digits structure of the ID, 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.
Live Demo: ID card scanner
No registration required. Upload a file to test the extraction.
Drop files here or click to browse
JPG · PNG · WebP · up to 500 files · max 4.5 MB each
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_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')}")
# MRZ Extraction
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_netherlands_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 English and local characters.
- •MRZ Extraction: Automatically parses Machine Readable Zone (MRZ) lines for enhanced data validation and identity verification.
- •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",
"additional_fields": {
"phone_number": null,
"tramite_number": null,
"ejemplar": null,
"mrz_line_1": "I<NLDSPECI2014<<<<<<<<<<<<<<<<",
"mrz_line_2": "9005152M3001014NLD123456782<<0",
"mrz_line_3": "DE<VRIES<<JAN<<<<<<<<<<<<<<<<<"
}
}
}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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