ByteScout PDF Extractor SDK - C# - OCR With Best Dataset - ByteScout

ByteScout PDF Extractor SDK – C# – OCR With Best Dataset

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OCR with best dataset in C# using ByteScout PDF Extractor SDK

How to code OCR with best dataset in C#: How-To tutorial

Writing of the code to OCR with best dataset in C# can be done by developers of any level using ByteScout PDF Extractor SDK. ByteScout PDF Extractor SDK was made to help with OCR with best dataset in C#. ByteScout PDF Extractor SDK is the SDK is designed to help developers with pdf tables and pdf data extraction from unstructured documents like pdf, tiff, scans, images, scanned and electronic forms. The library is powered by OCR, computer vision and AI to provide unique functionality like table detection, automatic table structure extraction, data restoration, data restructuring and reconstruction. Supports PDF, TIFF, PNG, JPG images as input and can output CSV, XML, JSON formatted data. Includes full set of utilities like pdf splitter, pdf merger, searchable pdf maker and other utilities.

The SDK samples like this one below explain how to quickly make your application do OCR with best dataset in C# with the help of ByteScout PDF Extractor SDK. To do OCR with best dataset in your C# project or application you may simply copy & paste the code and then run your app! Code testing will allow the function to be tested and work properly with your data.

Trial version can be obtained from our website for free. It includes this and other source code samples for C#.

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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_best\"; // 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_best // 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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