Damage Inspection: Container OCR API

The Challenge of M&R Visual Audits

Maintenance and Repair (M&R) operations require meticulous documentation. When inspectors photograph damaged containers, manually linking those images to the correct Equipment Interchange Receipt (EIR) is slow and error-prone. The physical condition of damaged containers—featuring heavy rust, deep dents across corrugated text, peeling paint, and dirt—causes standard optical character recognition to fail completely. To see how our engine cuts through these extreme visual challenges, you can upload a test image to explore our core Container OCR capabilities completely free.

Resilient Extraction for Harsh Conditions

Delivered strictly as a high-performance REST API to ensure seamless integration into any M&R workflow or mobile application without heavy SDK dependencies, this endpoint is powered by our Logistics Container OCR engine. It utilizes advanced deep-learning filters to reconstruct characters obscured by rust or physical distortion. The engine applies strict ISO 6346 validation on the fly, instantly calculating check digits to guarantee perfect data integrity before attaching the photos to your liability audit trail.

Damage & Inspection Scenarios

Integration & AI Prompts

Call the endpoint directly via HTTP. The API flexibly accepts standard image URLs, direct multipart file uploads, or Base64-encoded strings, making it perfect for integration into inspector mobile tablets or automated camera portals.

import requests
import base64

# Prepare Base64 Image from an inspector's mobile tablet
with open("damaged_container_photo.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 Inspection 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"
    }
  }
}