Weighbridge Automation: Container OCR API

The Weighbridge Data Bottleneck

Weighbridges are critical chokepoints in logistics yards. When trucks mount the scale, manual data entry of the container number creates unnecessary delays, increases driver dwell time, and introduces human error that corrupts VGM (Verified Gross Mass) records. Standard OCR solutions often fail here due to skewed camera angles from scale-side pillars and heavy shadowing. To see how our engine cuts through these baseline visual challenges, you can upload a test image to explore our core Container OCR capabilities completely free.

Instant Extraction, Zero SDK Bloat

Delivered strictly as a high-performance REST API to ensure seamless integration into any language without heavy SDK dependencies, this endpoint is powered by our Logistics Container OCR engine[cite: 2]. It processes incoming weighbridge captures in milliseconds across our global Cloudflare infrastructure. The engine applies strict ISO 6346 validation to verify the owner code and calculate the check digit, guaranteeing data integrity before it reaches your scale management software[cite: 2].

Weighbridge & Scale 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 to minimize network latency on edge networks[cite: 2].

import requests
import base64

# Prepare Base64 Image from local weighbridge CCTV capture
with open("scale_lane_2_capture.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 Weighbridge 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"
    }
  }
}