ByteScout Data Extraction Suite – VB.NET – Ocr with mean dataset with pdf extractor sdk

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ByteScout Data Extraction Suite – VB.NET – Ocr with mean dataset with pdf extractor sdk

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ByteScout-Data-Extraction-Suite-VB-NET-Ocr-with-mean-dataset-with-pdf-extractor-sdk.pdf

ocr with mean dataset with pdf extractor sdk in VB.NET using ByteScout Data Extraction Suite

Build ocr with mean dataset with pdf extractor sdk in VB.NET

Step-by-step instructions on how to do ocr with mean dataset with pdf extractor sdk in VB.NET

The documentation is crafted to assist you to apply the features on your side easily. ByteScout Data Extraction Suite was created to assist ocr with mean dataset with pdf extractor sdk in VB.NET. ByteScout Data Extraction Suite is the bundle that includes three SDK tools for data extraction from PDF, scans, images and from spreadsheets: PDF Extractor SDK, Data Extraction SDK, Barcode Reader SDK.

Want to speed up the application development? Then this VB.NET, code samples for VB.NET, developers help to speed up the application development and writing a code when using ByteScout Data Extraction Suite. If you want to know how it works, then this VB.NET sample code should be copied and pasted into your application’s code editor. Then just compile and run it. Check these VB.NET sample code examples to see if they acknowledge to your needs and requirements for the project.

Visit our website to get a free trial version of ByteScout Data Extraction Suite. Free trial contains many of source code samples to help you with your VB.NET project.

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Program.vb

      Imports 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".

Class Program

    Friend Shared Sub Main(args As String())

        ' Create Bytescout.PDFExtractor.TextExtractor instance
        Dim extractor As 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 OCRAnalyzer 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 output file in default associated application
        System.Diagnostics.Process.Start("output.txt")

    End Sub
    
End Class