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

Home
/
Articles
/
ByteScout PDF Extractor SDK – C# – OCR With Fast Dataset

printable version:
ByteScout-PDF-Extractor-SDK-C-sharp-OCR-With-Fast-Dataset.pdf

OCR with fast dataset in C# with ByteScout PDF Extractor SDK

OCR with fast dataset in C#

Sample source codes below will show you how to cope with a difficult task, for example, OCR with fast dataset in C#. ByteScout PDF Extractor SDK helps with OCR with fast dataset in C#. ByteScout PDF Extractor SDK is the Software Development Kit (SDK) that is designed to help developers with 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.

This rich sample source code in C# for ByteScout PDF Extractor SDK includes the number of functions and options you should do calling the API to implement OCR with fast dataset. In order to implement this functionality, you should copy and paste code below into your app using code editor. Then compile and run your application. Enjoy writing a code with ready-to-use sample C# codes to implement OCR with fast dataset using ByteScout PDF Extractor SDK.

On our website you may get trial version of ByteScout PDF Extractor SDK for free. Source code samples are included to help you with your C# application.

On-demand (REST Web API) version:
Web API (on-demand version)

On-premise offline SDK for Windows:
60 Day Free Trial (on-premise)

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_fast\";

            // 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_fast
            
            // 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);
        }
    }
}