The Best C# API for Shipping Container OCR
Stop using regex. Extract structured data from Shipping Containers with 99% accuracy using C# and .NET.

The Problem with Shipping Container Parsing in .NET
Developing robust C# OCR pipelines for shipping containers using tools like Tesseract.NET is highly challenging. Enterprise logistics systems face real-world variables: container IDs printed vertically, extreme rust, physical damage, low-light terminal environments, and skewed camera angles. Relying on basic text extraction combined with complex C# regular expressions for ISO 6346 validation results in brittle applications, high error rates, and increased manual exception handling.
The StructOCR Solution
StructOCR enables your .NET applications to bypass complex computer vision configurations by utilizing our specialized deep learning API. Our service automatically handles perspective deskewing and vertical text reading, guaranteeing ISO 6346 compliant extraction. We return parsed, validated JSON directly to your C# backend, making it incredibly simple to integrate accurate container tracking into your logistics and port automation platforms.
Common Use Cases
- Terminal Automation: Speed up gate operations and yard management by instantly capturing container numbers via .NET services.
- Customs & Compliance: Automate cross-border document verification and manifesting within enterprise ERPs.
- Asset Tracking: Monitor shipping container movements across the global supply chain with real-time data ingestion.
Implementation: Raw API Request
Complete, runnable C# code using HttpClient to extract data from a Shipping Container via direct file upload.
Prerequisite: .NET Core 3.1+ / .NET 6+
// š° Save 30%+ vs competitors. Get 20 free credits instantly:
// š https://structocr.com/register
using System;
using System.IO;
using System.Net.Http;
using System.Text.Json;
using System.Threading.Tasks;
public class ContainerOcrExample
{
public static async Task Main(string[] args)
{
string apiKey = "YOUR_API_KEY"; // Replace with your actual API key
string imagePath = "path/to/your/container_image.jpg"; // Replace with the path to your container image
try
{
Console.WriteLine($"Reading image from {imagePath}...");
// 1. Open the file stream directly for efficient upload
using var fileStream = File.OpenRead(imagePath);
using var streamContent = new StreamContent(fileStream);
streamContent.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/octet-stream");
// 2. Configure the HTTP client
using var httpClient = new HttpClient();
httpClient.DefaultRequestHeaders.Add("x-api-key", apiKey);
httpClient.DefaultRequestHeaders.Accept.Add(new System.Net.Http.Headers.MediaTypeWithQualityHeaderValue("application/json"));
Console.WriteLine("Uploading to StructOCR API...");
// 3. Send the POST request (Direct File Upload)
HttpResponseMessage response = await httpClient.PostAsync("https://api.structocr.com/v1/container", streamContent);
// 4. Handle the response
if (response.IsSuccessStatusCode)
{
string responseBody = await response.Content.ReadAsStringAsync();
// Parse the JSON response
using (JsonDocument document = JsonDocument.Parse(responseBody))
{
JsonElement root = document.RootElement;
if (root.GetProperty("success").GetBoolean())
{
JsonElement data = root.GetProperty("data");
Console.WriteLine("\nā
Extraction Successful!");
Console.WriteLine($"Container Number: {data.GetProperty("container_number").GetString()}");
Console.WriteLine($"Is Valid (ISO 6346): {data.GetProperty("is_valid").GetBoolean()}");
Console.WriteLine($"Confidence: {data.GetProperty("confidence").GetString()}\n");
if (data.TryGetProperty("parsed", out JsonElement parsed))
{
Console.WriteLine("--- Parsed Details ---");
Console.WriteLine($"Owner Code: {parsed.GetProperty("owner_code").GetString()}");
Console.WriteLine($"Category: {parsed.GetProperty("category").GetString()}");
Console.WriteLine($"Serial Number: {parsed.GetProperty("serial_number").GetString()}");
Console.WriteLine($"Check Digit: {parsed.GetProperty("check_digit").GetString()}");
}
}
else
{
Console.WriteLine($"ā API Error: {root.GetProperty("error").GetString()}");
}
}
}
else
{
Console.WriteLine($"ā HTTP Error: Status Code {response.StatusCode}");
}
}
catch (Exception ex)
{
Console.WriteLine($"Exception: {ex.Message}");
}
}
}
Technical Specs
- ā¢Latency: < 5s (Average)
- ā¢Uptime: 98.5% SLA
- ā¢Security: AES-256 Encryption & SOC2 Compliant
- ā¢Input: JPG, PNG, WebP (Max 4.5MB) via Direct File Upload
- ā¢Output: JSON (Structured Data)
Key Features
- ā¢Smart Crop: Auto-detects container boundaries.
- ā¢ISO 6346 Validation: Cross-validates owner codes and checksums automatically.
- ā¢Specialized Models: Trained specifically on vertical and degraded Shipping Container text.
Sample JSON Response
The API returns a clean JSON object with normalized, parsed container fields.
{
"success": true,
"data": {
"container_number": "TTNU5194822",
"is_valid": true,
"confidence": "High",
"parsed": {
"owner_code": "TTN",
"category": "U",
"serial_number": "519482",
"check_digit": "2"
}
}
}Frequently Asked Questions
What file formats are supported?
JPG, PNG, and WebP images up to 4.5MB.
Is data stored?
No. Images are processed in-memory and deleted immediately.
How to handle errors?
Check the 'success' flag and 'error' message in the response.
More OCR Tutorials
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C# National ID OCR API
Eliminate manual data entry for national IDs. This C# OCR API delivers structured JSON in <5s average latency, backed by 98.5% uptime SLA and AES-256 encryption.
Precise Data Extraction and Seamless
Integration with AI-powered OCR API.
Empower your solutions with automated data extraction by
integrating best-in class StructOCR via API seamlessly.
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