Indonesia KTP (e-KTP) OCR Python SDK
Instantly extract data from Indonesian IDs using our native Python library.

Parsing KTP (e-KTP) Challenges
Indonesian KTPs present several OCR challenges. Firstly, inconsistencies in formatting and layout across different regions are common. Secondly, the presence of native Bahasa Indonesia text combined with varying print quality makes accurate text recognition difficult.
Why StructOCR for Indonesia
Our model is specifically trained on a large dataset of Indonesian KTPs, addressing layout variations and native text recognition, making it ideal for id card parsing tasks. The Python SDK simplifies integration by providing a straightforward API for efficient information parsing, allowing you to process images with just a few lines of code.
Common Use Cases in Indonesia
- Digital Onboarding: Verify users for Fintech apps in Indonesia.
- Telecom Registration: Automate SIM card registration with KTP (e-KTP).
- 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.
Prefer another stack? Open the Node.js SDK + Express integration.
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_indonesia_id():
# Note: Supports JPG, PNG, WebP (Max 4.5MB)
# Target: KTP (e-KTP)
image_path = "indonesia_national_id.jpg"
try:
print(f"Scanning {image_path}...")
# The SDK handles file upload and API communication
# It automatically detects that this is a Indonesian 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("✅ Indonesia 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_indonesia_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.
- •Blur Detection: Automatically rejects blurry images.
- •Fraud Check: Validates KTP (e-KTP) 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": "IDN",
"nationality": "WNI",
"document_number": "3171234567890001",
"card_series": "",
"personal_number": "3171234567890001",
"surname": "SANTOSO",
"given_names": "BUDI",
"sex": "M",
"date_of_birth": "1990-05-15",
"place_of_birth": "JAKARTA",
"address": "Jl. Jend. Sudirman No. 5, Jakarta Pusat",
"date_of_issue": "2020-01-01",
"date_of_expiry": "2030-01-01",
"issuing_authority": "Kabupaten Bogor"
}
}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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From tutorial to production in 5 minutes.
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