Uganda Passport OCR with the StructOCR Python SDK

Challenges with Uganda Passport Verification

Extracting accurate information from Ugandan passports can be challenging due to factors like reflective laminate coatings, intricate security background patterns, and potential variations in print quality. Overcoming these hurdles requires sophisticated image processing and machine learning. Our advanced passport extraction api is specifically designed to tackle these issues, ensuring high accuracy and reliability.

Why StructOCR for Uganda Passports

StructOCR excels at extracting data from Ugandan passports with exceptional accuracy, even under difficult conditions. Our cutting-edge technology powers a superior passport extraction api that is trusted by businesses worldwide. It's an integral component of effective fintech identity verification software, streamlining onboarding and compliance processes. For the fastest Python integration, install the official StructOCR SDK and see the Python SDK documentation.

Built for High-Compliance Industries

• Travel & Aviation: Our technology provides a crucial verification solution for travel, enabling faster and more secure passenger processing for Ugandan citizens. This significantly speeds up check-in and boarding procedures, enhancing the overall travel experience.
• Financial Services: Leveraging our fintech identity verification software, financial institutions can automate the Know Your Customer (KYC) onboarding process with Ugandan passport data. This reduces manual effort and improves compliance accuracy.

Uganda Passport OCR with the Python SDK

The official Python SDK handles file encoding, API communication, and structured passport results. Use the SDK directly or open the FastAPI tab for a server endpoint. Keep your API key in STRUCTOCR_API_KEY.

Prerequisite: `pip install structocr`; set the server-side `STRUCTOCR_API_KEY` environment variable.

Prefer another stack? Open the Node.js SDK + Express integration.

import os
from structocr import StructOCR

# Initialize StructOCR Client
client = StructOCR(os.environ["STRUCTOCR_API_KEY"])

def scan_uganda_passport():
    image_path = "uganda_passport_sample.jpg"

    try:
        print(f"Scanning {image_path}...")
        result = client.scan_passport(image_path)

        if result.get('success'):
            data = result['data']
            print("✅ Passport Extraction Successful!")
            print(f"Passport #:  {data.get('passport_number')}")
            print(f"Name:        {data.get('given_names')} {data.get('surname')}")
            print(f"Nationality: {data.get('nationality')}")
            print(f"DOB:         {data.get('date_of_birth')}")
        else:
            print(f"❌ Extraction Failed: {result.get('error')}")

    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    scan_uganda_passport()

JSON Response Example

The Python SDK returns a dictionary matching this normalized JSON structure.

{
  "success": true,
  "data": {
    "type": "passport",
    "country_code": "UGA",
    "nationality": "UGA",
    "passport_number": "B1234567",
    "surname": "MUKASA",
    "given_names": "DAVID",
    "sex": "M",
    "date_of_birth": "1986-09-22",
    "place_of_birth": "KAMPALA",
    "date_of_issue": "2020-01-01",
    "date_of_expiry": "2031-09-21",
    "issuing_authority": "DCIC"
  }
}