TOS Integration: Container OCR API

The Data Integrity Gap in Terminal Operations

Terminal Operating Systems (TOS) are only as effective as the data fed into them. When terminal tractors, cranes, and gate systems rely on manual data entry or outdated OCR, corrupt container numbers enter your TOS database. This leads to lost containers, delayed vessel operations, and massive exception-handling overhead. To see how our engine acts as a firewall against bad data, you can upload a test image to explore our core Container OCR capabilities completely free.

A Clean API Engineered for TOS Ecosystems

Delivered strictly as a high-performance REST API to ensure seamless integration into any proprietary or commercial TOS (such as Navis N4 or CyberLogitec) without heavy SDK dependencies, this endpoint is powered by our Logistics Container OCR engine. It handles complex visual environments effortlessly. The engine applies strict ISO 6346 validation on the fly, instantly calculating check digits to guarantee that only 100% accurate Container Codes trigger your automated TOS workflows.

TOS Workflow Automation

Integration & AI Prompts

Call the endpoint directly via HTTP from your TOS middleware. To maintain maximum security within port intranets, the API flexibly accepts direct multipart file uploads or Base64-encoded strings, avoiding the need to expose camera feeds via public URLs.

import requests
import base64

# Prepare Base64 Image from terminal middleware
with open("tos_event_capture_992.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 Terminal Capture...")
    response = requests.post(url, headers=headers, json=payload)
    result = response.json()

    if result.get('success'):
        data = result['data']
        print("✅ Container Code Extracted!")
        print(f"Full Number:  {data.get('container_number')}")
        print(f"Valid ISO:    {data.get('is_valid')}")
        print(f"Confidence:   {data.get('confidence')}")
    else:
        print(f"❌ Extraction Failed: {result.get('error')} - {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"
    }
  }
}