Container OCR API for Canadian Terminals

The Reality of Terminal Gate OCR in Canada

Capturing container codes at active Canadian terminal gates presents severe physical challenges. From the freezing coastal winds of Halifax to the heavy snowfalls in Montreal, traditional optical scanners frequently fail when container text is obscured by frost, ice patches, or low-light winter conditions. Maintaining high throughput in these environments requires an AI engine that sees past the weather. For a deeper dive into overcoming these specific environmental hurdles, see our core Container OCR capabilities.

StructOCR: Engineered for Extreme Environments

Designed strictly as a high-performance REST API to ensure seamless integration into any language without heavy SDK dependencies, this endpoint is powered by our resilient Logistics Container OCR engine. It features complete rotation invariance—automatically reading upside-down text from top-down cranes covered in snow. The engine applies strict ISO 6346 validation to mathematically verify the check digit, guaranteeing data integrity even if a character is partially obscured by ice.

Core Applications for the Canadian Market

Integration & AI Prompts

Call the endpoint directly via HTTP. The API flexibly accepts standard image URLs, direct multipart file uploads, or Base64-encoded strings to minimize network latency on edge networks.

import requests
import base64

# Prepare Base64 Image from local CCTV capture
with open("vancouver_gate_winter.jpg", "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

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

try:
    print("Scanning Canadian Gate Capture...")
    response = requests.post(url, headers=headers, json=payload)
    result = response.json()

    if result.get('success'):
        data = result['data']['parsed']
        print("✅ Container Code Extracted!")
        print(f"Full Number:  {data.get('owner_code')}{data.get('category')}{data.get('serial_number')}-{data.get('check_digit')}")
    else:
        print(f"❌ Extraction Failed: {result.get('message')}")
except Exception as e:
    print(f"An error occurred: {e}")

{
  "success": true,
  "data": {
    "container_number": "ZCSU8921655",
    "is_valid": true,
    "confidence": "High",
    "parsed": {
      "owner_code": "ZCS",
      "category": "U",
      "serial_number": "892165",
      "check_digit": "5"
    }
  }
}