How to Integrate OCR in C# GitHub Projects with IronOCR

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If you’re a C# developer exploring Tesseract OCR on GitHub, chances are you’re after more than just code. You want a library that actually works out of the box, comes with examples you can run, and has an active community behind it. Reliable integration and solid version control matter just as much.

That’s where IronOCR steps in. In this guide, I’ll walk you through how to plug IronOCR into your GitHub projects so you can handle text recognition in images and PDFs with ease. Whether your goal is to grab plain text, extract structured words and lines, or even generate searchable PDFs for archiving, IronOCR has you covered.

Getting Started with IronOCR and GitHub

IronOCR stands out as a comprehensive OCR solution that works seamlessly with GitHub-based development workflows and .NET Core projects. Unlike raw Tesseract implementations that require complex configuration, IronOCR provides a refined API that gets you running in minutes. For those new to optical character recognition concepts, IronOCR's comprehensive documentation covers everything from basic text extraction to advanced image processing.

Start by installing IronOCR through NuGet Package Manager:

Install-Package IronOcr

Install with NuGet

PM >  Install-Package IronOcr

Check out IronOCR on NuGet for quick installation. With over 10 million downloads, it’s transforming PDF development with C#. You can also download the DLL or Windows installer.

IronOCR maintains several GitHub repositories with examples and tutorials. The official IronOCR Examples repository provides real-world implementations, while the Image to Text tutorial repository demonstrates practical use cases you can clone and modify. These repositories showcase OCR with barcode reading, multi-language support, and PDF processing. Thanks to frequent packages published on NuGet, you'll always have access the latest stable builds.

Creating Your First OCR Project on GitHub

Let's build a comprehensive OCR application suitable for GitHub sharing. In Visual Studio (or your preferred IDE), create a new console application with this project structure:

MyOcrProject/
├── src/
│   └── OcrProcessor.cs
├── images/
│   └── sample-invoice.jpg
├── .gitignore
├── README.md
└── MyOcrProject.csproj

Here's a complete C# code example of an OCR processor that demonstrates IronOCR's key features:

using IronOcr;
using System;
using System.IO;
namespace MyOcrProject
{
    public class OcrProcessor
    {
        private readonly IronTesseract _ocr;
        public OcrProcessor()
        {
            _ocr = new IronTesseract();
            // Configure for optimal accuracy
            _ocr.Configuration.ReadBarCodes = true;
            _ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.Auto;
            _ocr.Language = OcrLanguage.English;
        }
        public void ProcessDocument(string imagePath)
        {
            using var input = new OcrInput();
            // Load and preprocess the image
            input.LoadImage(imagePath);
            input.Deskew();  // Straighten rotated images
            input.DeNoise(); // Remove digital noise
            input.EnhanceResolution(225); // Optimize DPI for OCR
            // Perform OCR
            var result = _ocr.Read(input);
            // Output results
            Console.WriteLine($"Confidence: {result.Confidence}%");
            Console.WriteLine($"Text Found:\n{result.Text}");
            // Process any barcodes found
            foreach (var barcode in result.Barcodes)
            {
                Console.WriteLine($"Barcode: {barcode.Value} ({barcode.Format})");
            }
            // Save as searchable PDF
            result.SaveAsSearchablePdf("output.pdf");
        }
    }
    class Program
    {
        static void Main(string[] args)
        {
            var processor = new OcrProcessor();
            processor.ProcessDocument("images/sample-invoice.jpg");
        }
    }
}

using IronOcr;
using System;
using System.IO;
namespace MyOcrProject
{
    public class OcrProcessor
    {
        private readonly IronTesseract _ocr;
        public OcrProcessor()
        {
            _ocr = new IronTesseract();
            // Configure for optimal accuracy
            _ocr.Configuration.ReadBarCodes = true;
            _ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.Auto;
            _ocr.Language = OcrLanguage.English;
        }
        public void ProcessDocument(string imagePath)
        {
            using var input = new OcrInput();
            // Load and preprocess the image
            input.LoadImage(imagePath);
            input.Deskew();  // Straighten rotated images
            input.DeNoise(); // Remove digital noise
            input.EnhanceResolution(225); // Optimize DPI for OCR
            // Perform OCR
            var result = _ocr.Read(input);
            // Output results
            Console.WriteLine($"Confidence: {result.Confidence}%");
            Console.WriteLine($"Text Found:\n{result.Text}");
            // Process any barcodes found
            foreach (var barcode in result.Barcodes)
            {
                Console.WriteLine($"Barcode: {barcode.Value} ({barcode.Format})");
            }
            // Save as searchable PDF
            result.SaveAsSearchablePdf("output.pdf");
        }
    }
    class Program
    {
        static void Main(string[] args)
        {
            var processor = new OcrProcessor();
            processor.ProcessDocument("images/sample-invoice.jpg");
        }
    }
}

IRON VB CONVERTER ERROR developers@ironsoftware.com

This comprehensive example showcases several IronOCR capabilities. The constructor configures the OCR engine with barcode reading enabled and automatic page segmentation. The ProcessDocument method demonstrates image preprocessing through deskewing (correcting rotation), denoising (removing artifacts), and resolution enhancement. After processing, it extracts English text with confidence scores, identifies barcodes, and generates a searchable PDF. Developers can also easily configure IronOCR to read other languages, like Chinese, Spanish, or French, making it a versatile choice for multilingual GitHub projects. For references on installing additional language packs, please refer here.

For your .gitignore file, include:

# IronOCR runtime files
runtimes/
# Test images and outputs
*.pdf
test-images/
output/
# License keys
appsettings.*.json

Why Choose IronOCR for Your GitHub Projects

IronOCR offers distinct advantages for developers maintaining OCR projects on GitHub. The library achieves 99.8% accuracy out of the box without requiring manual training or complex configuration files that clutter repositories. With support for 125+ languages, your GitHub project can serve international users without modification.

IronOCR is flexible enough to recognize individual words, lines, and full paragraphs, giving you control over how much detail you extract from each scan.

The commercial license provides legal clarity for public repositories. In that you're explicitly permitted to include IronOCR in commercial applications. The built-in image preprocessing filters.

IronOCR's single-DLL architecture means contributors can clone your repository and start developing immediately, without wrestling with native dependencies or platform-specific configurations that plague other OCR solutions.

Version Control Best Practices for OCR Projects

When managing OCR projects on GitHub, use Git LFS for large test images:

git lfs track "*.jpg" "*.png" "*.tiff"
git add .gitattributes

git lfs track "*.jpg" "*.png" "*.tiff"
git add .gitattributes

IRON VB CONVERTER ERROR developers@ironsoftware.com

Store IronOCR license keys securely using environment variables or user secrets, never committing them directly. Follow the IronOCR license key guide for proper implementation. Document supported image formats and expected accuracy in your README. Include sample images in a test-data folder for contributors to verify OCR functionality. For cross-platform development, refer to the IronOCR Linux setup guide or macOS installation instructions.

Quick Troubleshooting Tips

Common setup issues include missing Visual C++ Redistributables on Windows, and IronOCR requires the 2019 version. For Linux deployments, ensure libgdiplus is installed. If text recognition seems poor, verify your images are at least 200 DPI. The C# OCR community on Stack Overflow also provides helpful solutions for common GitHub project issues.

For detailed troubleshooting, consult the IronOCR troubleshooting guide. The IronOCR support team provides rapid assistance for licensed users working on GitHub-hosted OCR applications.

Conclusion

IronOCR simplifies OCR implementation in C# GitHub projects through its intuitive API, comprehensive preprocessing, and reliable accuracy. Start with the code examples above, explore the official repositories, and build powerful document processing applications that leverage GitHub's collaborative features.

Download IronOCR's free trial for commercial deployment.