Ethiopia Fayda ID OCR Python SDK
Instantly extract data from Ethiopian IDs using our native Python library.
Parsing Fayda ID Challenges
Parsing Ethiopia's Fayda ID presents unique challenges. Firstly, the presence of both Amharic script and Latin characters within the same document requires a sophisticated OCR engine capable of accurately interpreting both. Secondly, variations in print quality and layout across different ID cards can significantly impact the accuracy of data extraction.
Why StructOCR for Ethiopia
Our model is specifically trained on a vast dataset of Ethiopian Fayda IDs, addressing the intricacies of both Amharic and Latin script recognition. This advanced national id ocr solution is optimized for the 14 digits structure commonly found in these documents. The StructOCR Python SDK offers a streamlined integration process, abstracting away the complexities of OCR and delivering accurate, structured data in a user-friendly format.
Common Use Cases in Ethiopia
- Digital Onboarding: Verify users for Fintech apps in Ethiopia.
- Telecom Registration: Automate SIM card registration with Fayda ID.
- 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.
from structocr import StructOCR
# 🔑 Need a key for Ethiopia? Get 200 free credits instantly:
# 👉 https://structocr.com/register
# Initialize with your API Key
client = StructOCR("YOUR_API_KEY_HERE")
def scan_ethiopia_id():
# Note: Supports JPG, PNG, WebP (Max 4.5MB)
# Target: Fayda ID
image_path = "ethiopia_national_id.jpg"
try:
print(f"Scanning {image_path}...")
# The SDK handles file upload and API communication
# It automatically detects that this is a Ethiopian 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("✅ Ethiopia 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_ethiopia_id()Technical Specs
- •Latency: < 4s (Average)
- •Availability: Served from Cloudflare's global edge network
- •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 Fayda ID 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": "ETH",
"nationality": "ETHIOPIAN",
"document_number": "1234 5678 9012",
"card_series": "",
"personal_number": "1234 5678 9012",
"surname": "ABEBE",
"given_names": "DAWIT",
"sex": "M",
"date_of_birth": "1990-05-15",
"place_of_birth": "ADDIS ABABA",
"address": "Bole Sub-city, Woreda 03, Addis Ababa",
"date_of_issue": "2020-01-01",
"date_of_expiry": "2030-01-01",
"issuing_authority": "NIDP"
}
}Frequently Asked Questions
Does the Python SDK handle image uploads?
Yes, the SDK automatically handles base64 encoding and file uploads.
Is data stored?
Only briefly. Uploaded images and results are kept for at most 24 hours for quality spot-checks, then deleted.
How to handle errors?
The SDK result dictionary contains a 'success' boolean and an 'error' message if failed.
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