Hungarian OCR in C# and .NET
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IronOCR is a C# software component allowing .NET coders to read text from images and PDF documents in 126 languages, including Hungarian.
It is an advanced fork of Tesseract, built exclusively for .NET developers and regularly outperforms other Tesseract engines for both speed and accuracy.
Contents of IronOcr.Languages.Hungarian
This package contains 52 OCR languages for .NET:
- Hungarian
- HungarianBest
- HungarianFast
Download
Hungarian Language Pack [magyar]
Installation
The first thing we have to do is install our Hungarian OCR package to your .NET project.
Code Example
This C# code example reads Hungarian text from an image or PDF document.
// First, ensure you have installed the Hungarian OCR language pack
// via NuGet: Install-Package IronOcr.Languages.Hungarian
using IronOcr;
var Ocr = new IronTesseract();
// Set the OCR language to Hungarian.
Ocr.Language = OcrLanguage.Hungarian;
// Load the image file containing Hungarian text
using (var Input = new OcrInput(@"images\Hungarian.png"))
{
// Perform OCR on the input image
var Result = Ocr.Read(Input);
// Retrieve and store the recognized text
var AllText = Result.Text;
// Output the recognized text to the console (for debugging purposes)
Console.WriteLine(AllText);
}' First, ensure you have installed the Hungarian OCR language pack
' via NuGet: Install-Package IronOcr.Languages.Hungarian
Imports IronOcr
Dim Ocr = New IronTesseract()
' Set the OCR language to Hungarian.
Ocr.Language = OcrLanguage.Hungarian
' Load the image file containing Hungarian text
Using Input = New OcrInput("images\Hungarian.png")
' Perform OCR on the input image
Dim Result = Ocr.Read(Input)
' Retrieve and store the recognized text
Dim AllText = Result.Text
' Output the recognized text to the console (for debugging purposes)
Console.WriteLine(AllText)
End UsingThis code snippet demonstrates how to set up an OCR reader using the IronOCR library to recognize Hungarian text from a specified image file. The text extracted is stored in the AllText variable, and can be used as needed within your application. The example also includes an optional console output to verify the OCR results during testing.
Curtis Chau holds a Bachelor’s degree in Computer Science (Carleton University) and specializes in front-end development with expertise in Node.js, TypeScript, JavaScript, and React. Passionate about crafting intuitive and aesthetically pleasing user interfaces, Curtis enjoys working with modern frameworks and creating well-structured, visually appealing manuals.
