Container OCR API for United States Logistics

Tackling Congestion at US Terminal Gates

US ports and inland logistics hubs face unprecedented cargo volumes and severe labor shortages. Relying on manual gate checks or legacy on-premise hardware creates massive trucking bottlenecks. Cameras must endure harsh sunlight, and capture systems frequently fail when reading inverted text from overhead cranes or worn-out container markings. Modernizing US supply chains requires agile, high-concurrency cloud infrastructure. For a deeper dive into overcoming these environmental hurdles, see our core Container OCR capabilities.

StructOCR: Scalable Cloud Infrastructure for the US Market

Engineered purely as a high-performance REST API to bypass the integration friction of bulky software SDKs, this endpoint is powered by our Logistics Container OCR engine. It features complete rotation invariance—automatically reading upside-down text from automated yard cranes without pre-processing. The system applies strict ISO 6346 validation algorithms to calculate the check digit, ensuring bad data never bottlenecks your Terminal Operating System (TOS).

Core Applications for American Supply Chains

Integration & AI Prompts

Call the endpoint directly via standard HTTP protocols. The API natively supports raw Base64 strings, direct multipart file uploads, or image URLs to minimize latency on edge networks.

import requests
import base64

# Prepare Base64 Image from local US port CCTV capture
with open("gate_capture_lane7.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 US 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"
    }
  }
}