Brazil Carteira de Identidade (CIN) OCR Python SDK

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

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

Parsing Carteira de Identidade (CIN) Challenges

Brazilian Carteira de Identidade (CIN) presents unique OCR challenges. Firstly, the variable layout across different states introduces inconsistencies in field placement. Secondly, the document's often poor print quality, combined with instances of handwritten annotations, can significantly degrade OCR accuracy. Additionally, the presence of Portuguese language-specific characters requires specialized linguistic processing.

Why StructOCR for Brazil

StructOCR is specifically trained on a vast dataset of Brazilian Carteira de Identidade (CIN) variations to overcome these challenges. Our Python SDK simplifies integration with a straightforward API, allowing developers to quickly and accurately extract data without needing to build complex OCR pipelines. The model is designed to handle variations in print quality and layouts common to Brazilian IDs.

Common Use Cases in Brazil

  • Digital Onboarding: Verify users for Fintech apps in Brazil.
  • Telecom Registration: Automate SIM card registration with Carteira de Identidade (CIN).
  • 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_brazil_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: Carteira de Identidade (CIN)
    image_path = "brazil_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is a Brazilian 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("✅ Brazil 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_brazil_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 Carteira de Identidade (CIN) 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": "BRA",
    "nationality": "BRASILEIRA",
    "document_number": "123.456.789-00",
    "card_series": "",
    "personal_number": "123.456.789-00",
    "surname": "DA SILVA",
    "given_names": "JOÃO PAULO",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "SÃO PAULO - SP",
    "address": "Av. Paulista 1000, Bela Vista, São Paulo - SP",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "Secretaria de Segurança Pública"
  }
}

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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