Colombia Cédula OCR Python SDK
Instantly extract data from Colombian Identity Cards (Cédula de Ciudadanía) using our native Python library.

Parsing Cédula de Ciudadanía Challenges
The Colombian Cédula de Ciudadanía poses unique OCR challenges. Accurately extracting the Número Único de Identificación Personal (NUIP), parsing complex Spanish multi-line structures, and handling holographic overlays require highly specialized computer vision models to ensure accurate data capture.
Why StructOCR for Colombia
StructOCR's model is specifically trained on a large dataset of Latin American ID images, ensuring high accuracy for national id ocr extraction. The v1.4.0 Python SDK simplifies the integration process, while our Cloudflare Workers infrastructure ensures ultra-low latency processing. With just a few lines of code, you can extract structural data, including the NUIP mapped directly to the personal number field, to fully automate your verification workflows.
Common Use Cases in Colombia
- Digital Onboarding: Verify users for Fintech apps, digital wallets, and banking services across Colombia.
- Telecom & Utility Registration: Automate document parsing for mobile SIM card sales and essential service applications.
- Notary & Legal Tech: Speed up identity verification for contract signing and legal document processing.
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
# 💰 Note: Deposit via Crypto (USDT/USDC) to automatically receive a 10% credit bonus.
# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")
def scan_colombia_id():
# Note: Supports JPG, PNG, WebP (Max 4.5MB)
# Target: Cédula de Ciudadanía
image_path = "colombia_national_id.jpg"
try:
print(f"Scanning {image_path}...")
# The SDK handles file upload and API communication
# It automatically detects that this is a Colombian 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("✅ Colombia Extraction Successful!")
# Basic Identity
print(f"Region: {data.get('country_code')}")
print(f"Name: {data.get('given_names')} {data.get('surname')}")
# Critical Field: NUIP (Personal Identification Number)
print(f"NUIP: {data.get('personal_number')}")
# Demographics
print(f"DOB: {data.get('date_of_birth')} ({data.get('sex')})")
print(f"Birthplace: {data.get('place_of_birth')}")
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_colombia_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 Spanish Support: Reads Spanish names, special characters, and regional formatting seamlessly.
- •NUIP Extraction: Automatically extracts and validates the Número Único de Identificación Personal (NUIP).
- •Date Normalization: Standardizes issue dates and birth dates into a consistent `YYYY-MM-DD` format.
- •Smart Crop & Blur Detection: Rejects blurry images and removes background noise automatically to ensure high precision.
JSON Response Example
The SDK returns a Python dictionary matching this JSON structure.
{
"success": true,
"data": {
"type": "national_id",
"country_code": "COL",
"nationality": "COLOMBIANA",
"document_number": "1098765432",
"card_series": "",
"personal_number": "1098765432",
"surname": "GARCÍA PÉREZ",
"given_names": "CARLOS ARTURO",
"sex": "M",
"date_of_birth": "1992-08-15",
"place_of_birth": "BOGOTÁ, D.C.",
"address": null,
"date_of_issue": "2010-08-20",
"date_of_expiry": null,
"issuing_authority": "REGISTRADURÍA NACIONAL DEL ESTADO CIVIL",
"additional_fields": {
"phone_number": null,
"tramite_number": null,
"ejemplar": null,
"mrz_line_1": null,
"mrz_line_2": null,
"mrz_line_3": null
}
}
}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 global data privacy regulations and Latin American data protection standards.
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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