Vietnam ALPR & Motorcycle Plate Recognition API

The Challenge of Vietnam ALPR & Two-Line Plates

For system integrators operating in Southeast Asia, implementing robust vietnam alpr presents unique physical and technical hurdles. The sheer volume of traffic requires flawless motorcycle plate recognition. Unlike standard wide plates, Vietnamese motorcycle plates are typically square, two-line layouts that cause standard western-trained models to misread the character sequencing. Furthermore, these plates often suffer from severe nighttime retro-reflective glare. Attempting to train self-hosted models to distinguish these elements often results in scrambled strings or complete recognition failures. Before spending months collecting local datasets, you can test your regional captures against our API for free to experience true dual-line extraction.

A Global Engine for High-Density Traffic

The StructOCR License Plate API is engineered specifically to transcend the limitations of single-line Latin models. Our backend natively understands the square two-line layout, perfectly stitching the top and bottom rows into a logical alphanumeric string while utilizing advanced filters to pierce through severe IR washout. Deployed on Cloudflare's global edge network, the API ensures that whether your camera is in Ho Chi Minh City, Hanoi, or a border checkpoint, the image is processed by the nearest geographic node for ultra-low latency, crucial for fast-moving motorcycle streams.

Empowering Southeast Asian System Integrators

Extracting Two-Line Plates: Just 15 Lines of Code

Call the endpoint directly using Python's standard `requests` library. The engine natively supports flexible inputs: you can utilize standard image URLs, direct file uploads, or raw Base64-encoded strings. Check the API documentation for full payload parameters and schema details.

import requests
import base64

# Prepare Base64 Image to extract License Plate data
with open("hcmc_motorcycle_capture.jpg", "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

url = "https://api.structocr.com/v1/license-plate"
headers = {
    "x-api-key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "img": base64_image
}

try:
    print("Analyzing Southeast Asian vehicle plates...")
    response = requests.post(url, headers=headers, json=payload)
    result = response.json()

    if result.get('success'):
        data = result['data']
        plates = data.get('plates', [])
        print(f"✅ Successfully detected {len(plates)} plate(s)!")
        for idx, plate in enumerate(plates):
            print(f"[{idx+1}] Number: {plate.get('plate_number')} (Normalized: {plate.get('plate_number_normalized')}) | Type: {plate.get('plate_type')} | Color: {plate.get('plate_color')}")
        print(f"Country Guess: {data.get('country_guess')} | Confidence: {data.get('confidence_score')}")
    else:
        print(f"❌ Extraction Failed: {result.get('error') or result.get('message')}")

except Exception as e:
    print(f"An error occurred: {e}")

{
  "success": true,
  "data": {
    "plates": [
      {
        "plate_number": "59A1 12345",
        "plate_number_normalized": "59A112345",
        "plate_color": "white",
        "plate_type": "motorcycle"
      }
    ],
    "region_text": null,
    "country_guess": "Vietnam",
    "confidence_score": 0.99
  }
}