Tajikistan ID Card (Karta) OCR Python SDK

Instantly extract data and MRZ from Tajik IDs using our native Python library.

AI extracting data from a Tajikistan ID card
StructOCR engine analyzing a Tajik document and MRZ lines in real-time.

Parsing ID Card (Karta) Challenges

Tajikistan ID cards pose unique challenges. Firstly, the use of Cyrillic script alongside Latin script requires specialized character recognition. Secondly, variations in layout and formatting across different card versions can lead to parsing errors if not handled carefully.

Why StructOCR for Tajikistan

Our OCR model is specifically trained on a diverse dataset of Tajik ID cards, ensuring high accuracy even with Cyrillic script and layout variations. This advanced national id ocr capability is crucial for information parsing in kyc automation processes. Additionally, it fully supports reading the Machine Readable Zone (MRZ) for strict global compliance. The StructOCR Python SDK provides a simple and intuitive API, making integration seamless and reducing development time. We handle pre-processing and data extraction, delivering clean, structured data.

Common Use Cases in Tajikistan

  • Digital Onboarding: Verify users for Fintech apps in Tajikistan.
  • Telecom Registration: Automate SIM card registration with ID Card (Karta).
  • Hotel Check-in: Speed up guest registration workflows.

Live Demo: ID card scanner

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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_tajikistan_id():
    # Note: Supports JPG, PNG, WebP (Max 4.5MB)
    # Target: ID Card (Karta)
    image_path = "tajikistan_national_id.jpg"

    try:
        print(f"Scanning {image_path}...")
        
        # The SDK handles file upload and API communication
        # It automatically detects that this is a Tajik 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("✅ Tajikistan 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')}")

            # Machine Readable Zone (MRZ)
            additional = data.get('additional_fields', {})
            if additional.get('mrz_line_1'):
                print("\n--- MRZ Data ---")
                print(additional.get('mrz_line_1'))
                print(additional.get('mrz_line_2'))
                if additional.get('mrz_line_3'):
                    print(additional.get('mrz_line_3'))
        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_tajikistan_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 Parsing: Accurately extracts and validates the Machine Readable Zone lines for cross-checking.
  • Blur Detection: Automatically rejects blurry images.
  • Fraud Check: Validates ID Card (Karta) 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": "TJK",
    "nationality": "TAJIKISTAN",
    "document_number": "123456789",
    "card_series": "A",
    "personal_number": "123456789",
    "surname": "ШАРИПОВ",
    "given_names": "РУСТАМ",
    "sex": "M",
    "date_of_birth": "1990-05-15",
    "place_of_birth": "DUSHANBE",
    "address": "пр. Рудаки 10, кв. 5, Душанбе",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2030-01-01",
    "issuing_authority": "IIV 01",
    "additional_fields": {
      "phone_number": null,
      "tramite_number": null,
      "ejemplar": null,
      "mrz_line_1": "IDTJK1234567895<<<<<<<<<<<<<<<",
      "mrz_line_2": "9005156M3001014TJK123456789<<8",
      "mrz_line_3": "SHARIPOV<<RUSTAM<<<<<<<<<<<<<<"
    }
  }
}

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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