User Guide > How to Work with... > OCR > How to... > Perform Multi-Threaded OCR |
This topic provides some background information about using ImageGear OCR in a multi-threaded application and walks you through creating a new multi-threaded application using OCR.
The Recognition API can be used in a multi-threaded application. However, it is generally the application's responsibility to ensure that the different recognition activities (e.g., pre-processing, decomposition, recognition, etc.) occur sequentially for any given image or page.
Multiple instances of the ImGearRecognition object are now supported in a single process. While all instances of this object will access the same underlying native Recognition engine, each instance operates on its own set of pages and documents.
Each instance can use the shared global collection of Recognition settings if instantiated with the default constructor. This means that changing settings (e.g., ImGearRecOutputManager.Format) in one instance will affect all other instances using the global settings. To isolate the Recognition settings for each instance, use the overloaded constructor, ImGearRecognition(bool). This will force each instance to use its own collection of unique settings. |
Using multiple instances of the ImGearRecognition object in separate threads enables the application to perform recognition activities on different images and pages in parallel. However, it is important to remember that for each page, the recognition process must occur sequentially, meaning that a page must first be imported and pre-processed before it can be recognized and exported. Also, access to the underlying formatted output module is synchronized, so only one instance can export to a formatted output document at a time.
No re-entrance is allowed within the same thread. This can occur when the API is firing an event. When the focus of control is in the application-defined event handler, no methods of the Recognition API can be called. |
The ImageGear Recognition assembly provides you with the ability to perform recognition activities on multiple images in parallel. However, you will want to ensure that the amount of memory being consumed by this process does not exceed the limitations of the system. This can occur if, for example, all pages of a large PDF are opened at once and then sent to the Recognition assembly for processing.
The following points should always be considered when using the Recognition API, but especially when calling it within multiple threads or when large images are to be recognized:
An alternative to the “all-at-once” processing style mentioned above is a processing technique where smaller chunks of images are opened, processed, exported and closed in an assembly line style. This technique ensures that only a specified number of images are opened and being processed at one time, keeping a consistent and manageable memory footprint throughout the process.
The following walkthrough describes this technique using the System.Threading.Tasks.Parallel class included in the .NET 4.0 Framework. In this walkthrough, you will create a .NET 4 Windows application that processes all pages of a PDF file while ensuring a controlled memory footprint throughout the task.
This section describes how to create the project for this sample:
This section describes how to create the class that will perform the parsing and recognition of the PDF file using multiple threads:
C# |
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using System; using System.IO; using System.Threading.Tasks; using ImageGear.Core; using ImageGear.Evaluation; using ImageGear.Formats; using ImageGear.Formats.PDF; using ImageGear.Recognition; |
VB.NET |
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Imports System Imports System.IO Imports System.Threading.Tasks Imports ImageGear.Core Imports ImageGear.Evaluation Imports ImageGear.Formats Imports ImageGear.Formats.PDF Imports ImageGear.Recognition |
C# |
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public PageProcessorTest() { // Initialize evaluation manager. ImGearEvaluationManager.Initialize(); // ***The SetSolutionName, SetSolutionKey and possibly the SetOEMLicenseKey // methods must be called to distribute the runtime.*** // ImGearLicense.SetSolutionName("YourSolutionName"); // ImGearLicense.SetSolutionKey(12345, 12345, 12345, 12345); // Manually Reported Runtime licenses also require the following method // call to SetOEMLicenseKey. // ImGearLicense.SetOEMLicenseKey("2.0.AStringForOEMLicensing..."); ImGearCommonFormats.Initialize(); ImGearFileFormats.Filters.Insert(0, ImGearPDF.CreatePDFFormat()); ImGearFileFormats.Filters.Insert(0, ImGearPDF.CreatePSFormat()); ImGearPDF.Initialize(); } |
VB.NET |
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Public Sub Initialize() ' Initialize evaluation manager. ImGearEvaluationManager.Initialize() ' ***The SetSolutionName, SetSolutionKey and possibly the SetOEMLicenseKey ' methods must be called to distribute the runtime.*** ' ImGearLicense.SetSolutionName("YourSolutionName") ' ImGearLicense.SetSolutionKey(12345, 12345, 12345, 12345) ' Manually Reported Runtime licenses also require the following method ' call to SetOEMLicenseKey. ' ImGearLicense.SetOEMLicenseKey("2.0.AStringForOEMLicensing..."); ImGearCommonFormats.Initialize () ImGearFileFormats.Filters.Insert(0, ImGearPDF.CreatePDFFormat()) ImGearFileFormats.Filters.Insert(0, ImGearPDF.CreatePSFormat()) ImGearPDF.Initialize() End Sub |
C# |
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private void ProcessPageChunk(ImGearRecPage[] recPagesChunk, ImGearRecDocument document) { Parallel.ForEach(recPagesChunk, pg => { if (pg != null) { pg.Image.Preprocess(); pg.Recognize(); } }); for (int i = 0; i < recPagesChunk.Length; i++) { if (recPagesChunk[i] != null) { document.InsertPage(recPagesChunk[i], -1); // Dispose of the rec page from this last chunk. It has // already been added to an output document at this point // so the recognized page data will be included in the // output document. // Processing the document in "chunks" also allows the // application to maintain a predictable memory footprint. recPagesChunk[i].Dispose(); recPagesChunk[i] = null; } } } |
VB.NET |
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Private Sub ProcessPageChunk(ByRef recPagesChunk As ImGearRecPage(), ByRef document As ImGearRecDocument) Parallel.ForEach(recPagesChunk, Sub(pg) If pg IsNot Nothing Then Dim recPage As ImGearRecPage = DirectCast(pg, ImGearRecPage) If recPage IsNot Nothing Then recPage.Image.Preprocess() recPage.Recognize() End If End If End Sub) For i As Integer = 0 To recPagesChunk.Length - 1 If recPagesChunk(i) IsNot Nothing Then document.InsertPage(recPagesChunk(i), -1) ' Dispose of the rec page from this last chunk. It has ' already been added to an output document at this point ' so the recognized page data will be included in the ' output document. ' Processing the document in "chunks" also allows the ' application to maintain a predictable memory footprint. recPagesChunk(i).Dispose() recPagesChunk(i) = Nothing End If Next End Sub |
C# |
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public void Process(FileInfo file) { string xmlFile = "output.xml"; int numberOfCores = 4; // Create an ImGearRecognition object to initialize the Recognition engine. To isolate its // setting collection from all other ImGearRecognition objects, construct with the parameter // createUnique set to true. using (var igRecognition = new ImGearRecognition(true)) { using (var document = igRecognition.OutputManager.CreateDocument(null)) { using (var content = new FileStream(file.FullName, FileMode.Open, FileAccess.Read)) { int numberOfPages = ImGearFileFormats.GetPageCount(content, ImGearFormats.UNKNOWN); var recPagesChunk = new ImGearRecPage[numberOfCores]; for (int i = 0; i < numberOfPages; i++) { // Index to track the current index within the smaller // chunk of pages int chunkIndex = i % numberOfCores; ImGearPage igPage = ImGearFileFormats.LoadPage(content, i); // Rasterize the page if it's a vector page if (igPage is ImGearVectorPage) { ImGearPage tempPage = ((ImGearVectorPage)igPage).Rasterize(); if (igPage is IDisposable) { (igPage as IDisposable).Dispose(); } igPage = tempPage; } recPagesChunk[chunkIndex] = igRecognition.ImportPage((ImGearRasterPage)igPage); if (((i != 0) && (chunkIndex == numberOfCores - 1)) || (i == numberOfPages - 1)) { ProcessPageChunk(recPagesChunk, document); } } } igRecognition.OutputManager.CodePage = "UTF-8"; igRecognition.OutputManager.Level = ImGearRecOutputLevel.AUTO; igRecognition.OutputManager.Format = "Converters.Text.XML"; igRecognition.OutputManager.WriteDocument(document, xmlFile); } } } |
VB.NET |
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Public Sub Process(ByVal file As FileInfo) Dim xmlFile As String = "output.xml" Dim numberOfCores As Integer = 4 ' Create an ImGearRecognition object to initialize the Recognition engine. To isolate its ' setting collection from all other ImGearRecognition objects, construct with the parameter ' createUnique set to true. Using igRecognition As New ImGearRecognition(true) Using document As ImGearRecDocument = igRecognition.OutputManager.CreateDocument(Nothing) Using content As New FileStream(file.FullName, FileMode.Open, FileAccess.Read) Dim numberOfPages As Int32 = ImGearFileFormats.GetPageCount(content, ImGearFormats.UNKNOWN) Dim recPagesChunk(numberOfCores) As ImGearRecPage For i As Int32 = 0 To numberOfPages - 1 ' Index to track the current index within the smaller ' chunk of pages Dim chunkIndex As Int32 = i Mod numberOfCores Dim igPage As ImGearPage = ImGearFileFormats.LoadPage(content, i) ' Rasterize the page if it's a vector page If TypeOf igPage Is ImGearVectorPage Then Dim tempPage As ImGearPage = DirectCast(igPage, ImGearVectorPage).Rasterize() If TypeOf igPage Is IDisposable Then DirectCast(igPage, IDisposable).Dispose() End If igPage = tempPage End If recPagesChunk(chunkIndex) = igRecognition.ImportPage(DirectCast(igPage, ImGearRasterPage)) If ((i <> 0 AndAlso chunkIndex = numberOfCores - 1) Or i = numberOfPages - 1) Then ProcessPageChunk(recPagesChunk, document) End If Next End Using igRecognition.OutputManager.CodePage = "UTF-8" igRecognition.OutputManager.Level = ImGearRecOutputLevel.AUTO igRecognition.OutputManager.Format = "Converters.Text.XML" igRecognition.OutputManager.WriteDocument(document, xmlFile) End Using End Using End Sub |
This section describes how to call the PageProcessorTest class that you created above: