ByteScout PDF Suite - C# - OCR With Mean Dataset with PDF Extractor SDK - ByteScout

ByteScout PDF Suite – C# – OCR With Mean Dataset with PDF Extractor SDK

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OCR with mean dataset with PDF extractor SDK in C# using ByteScout PDF Suite

OCR with mean dataset with PDF extractor SDK in C#

The samples of source code documentation give a quick and simple method to apply a required functionality into your application. ByteScout PDF Suite helps with OCR with mean dataset with PDF extractor SDK in C#. ByteScout PDF Suite is the set that includes 6 SDK products to work with PDF from generating rich PDF reports to extracting data from PDF documents and converting them to HTML. This bundle includes PDF (Generator) SDK, PDF Renderer SDK, PDF Extractor SDK, PDF to HTML SDK, PDF Viewer SDK and PDF Generator SDK for Javascript.

Want to speed up the application development? Then this C#, code samples for C#, developers help to speed up the application development and writing a code when using ByteScout PDF Suite. Follow the steps-by-step instructions from the scratch to work and copy and paste code for C# into your editor. Check these C# sample code examples to see if they acknowledge to your needs and requirements for the project.

Our website gives free trial version of ByteScout PDF Suite. It includes all these source code samples with the purpose to assist you with your C# application implementation.

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Program.cs
      
using System.Diagnostics; using Bytescout.PDFExtractor; // This example demonstrates the use of Optical Character Recognition (OCR) to extract text // from scanned PDF documents and raster images. // To make OCR work you should add the following references to your project: // 'Bytescout.PDFExtractor.dll', 'Bytescout.PDFExtractor.OCRExtension.dll'. namespace OCRExample { class Program { static void Main(string[] args) { // Create Bytescout.PDFExtractor.TextExtractor instance TextExtractor extractor = new TextExtractor(); extractor.RegistrationName = "demo"; extractor.RegistrationKey = "demo"; // Load sample PDF document extractor.LoadDocumentFromFile("sample_ocr.pdf"); // Enable Optical Character Recognition (OCR) // in .Auto mode (SDK automatically checks if needs to use OCR or not) extractor.OCRMode = OCRMode.Auto; // Set the location of OCR language data files extractor.OCRLanguageDataFolder = @"c:\Program Files\Bytescout PDF Extractor SDK\ocrdata\"; // Set OCR language extractor.OCRLanguage = "eng"; // "eng" for english, "deu" for German, "fra" for French, "spa" for Spanish etc - according to files in "ocrdata" folder // Find more language files at https://github.com/bytescout/ocrdata/tree/master/ocrdata // Set PDF document rendering resolution extractor.OCRResolution = 300; // You can also apply various preprocessing filters // to improve the recognition on low-quality scans. // Automatically deskew skewed scans //extractor.OCRImagePreprocessingFilters.AddDeskew(); // Remove vertical or horizontal lines (sometimes helps to avoid OCR engine's page segmentation errors) //extractor.OCRImagePreprocessingFilters.AddVerticalLinesRemover(); //extractor.OCRImagePreprocessingFilters.AddHorizontalLinesRemover(); // Repair broken letters //extractor.OCRImagePreprocessingFilters.AddDilate(); // Remove noise //extractor.OCRImagePreprocessingFilters.AddMedian(); // Apply Gamma Correction //extractor.OCRImagePreprocessingFilters.AddGammaCorrection(); // Add Contrast //extractor.OCRImagePreprocessingFilters.AddContrast(20); // (!) You can use new OCRAnalyser class to find an optimal set of image preprocessing // filters for your specific document. // See "OCR Analyser" example. // Save extracted text to file extractor.SaveTextToFile("output.txt"); // Cleanup extractor.Dispose(); // Open result document in default associated application (for demo purpose) ProcessStartInfo processStartInfo = new ProcessStartInfo("output.txt"); processStartInfo.UseShellExecute = true; Process.Start(processStartInfo); } } }

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