Porównanie pomiędzy IronOCR a AWS Textract OCR

What is OCR?

The procedure used to transform an image of text into a machine-readable text format is known as Optical Character Recognition (OCR). For example, if you scan a form, invoices or a receipt, your computer saves the scan as an image file. The data in the image file cannot be edited, searched for, or counted using a text editor. However, you can use OCR solutions to convert the image file into a text document with its contents stored as text data.

In this modern era, most business workflows involve receiving information from print media. Different documents like paper forms, invoices, scanned legal documents, table extraction, and printed text or contracts are all part of business processes. Moreover, digitizing such documentation content creates images with the text hidden within it. Text in images cannot be processed by word processing tools in the same way as text documents. OCR technology solves the problem by converting text images into text data that can be analyzed by other business software.

How OCR Works?

The OCR engine works by using the following steps:

1. Creating Visual Studio Project

This tutorial will use the Visual Studio 2022 version so I assume you must have installed it.

• Open Visual Studio 2022.
• Generate a new .NET Core project and then select Console App.

Aplikacja konsolowa

• Give a name to the project. E.g TextReader.

• The latest and most stable version of the .NET framework is 6.0. We are going to use this.

  

• Click Create button and the project will be created.

Next, we will install the libraries for our use one by one.

2. Installing IronOCR

Bibliotekę IronOCR można pobrać i zainstalować na cztery sposoby. Są to:

1. Using the Visual Studio Menedżer pakietów NuGet.
2. Direct download via the NuGet website.
3. Direct download via the IronOCR webpage.
4. Using the Command Line in Visual Studio.

2.1. Using the Visual Studio NuGet Manager

The Visual Studio Menedżer pakietów NuGet can be used to incorporate IronOCR into a C# project.

1. Expand Tools or by right-clicking solution explorer.
2. Extend the Menedżer pakietów NuGet.
3. Click on Manage NuGet Packages for Solutions or click Manage NuGet Packages in solution explorer.

Manage NuGet Packages

After this, a new window will appear in the search bar: type IronOCR. Check the project box on the right side and click Install.

Browse IronOCR

By using this method, developers can install the IronOCR library and any language pack of the developer's choice.

2.4. Using the Command Line in Visual Studio

1. In Visual Studio, go to Tools-> NuGet Package manager -> Package manager console.
2. Enter the following line in the package manager console tab:

Install-Package IronOcr

The package will now download/install in the current project and is ready to use.

Aplikacja konsolowa

Aplikacja konsolowa

After typing the command, press enter, and it will be installed.

using IronOcr;

using IronOcr;

Imports IronOcr

3. Installing AWS Textract OCR

Before you use Amazon Textract for the first time, complete the following tasks:

1. Sign Up for AWS services.
2. Create an IAM User.

Once you have successfully signed up for the account and created IAM user, you can now set the access keys in the AWS console to access the API programmatically using C#. You will need:

• AccessKeyId
• SecretAccessKey
• RegionEndPoint (Your access area)- In this example case: AFSouth1

3.1. Using Menedżer pakietów NuGet

• You can download and install AWS Textract SDK from Menedżer pakietów NuGet.

Menedżer pakietów NuGet

• Click on Browse and search for AWS Textract:

AWS Textract

using Amazon.Textract;
using Amazon.Textract.Model;

using Amazon.Textract;
using Amazon.Textract.Model;

Imports Amazon.Textract
Imports Amazon.Textract.Model

4. PDF file to Text

Both libraries can extract text from PDF files. Let's have a look at the code one by one.

4.1. Using IronOCR

IronOCR allows recognizing and reading text from PDF document formats using the advanced Tesseract. The following simple code is used for extracting information:

var Ocr = new IronTesseract();
using (var input = new OcrInput())
{
    input.AddPdf("example.pdf", "password");
    // We can also select specific PDF page numbers to OCR
    var Result = Ocr.Read(input);
    Console.WriteLine(Result.Text);
    Console.WriteLine($"{Result.Pages.Count()} Pages");
    // Read every page of the PDF
}

var Ocr = new IronTesseract();
using (var input = new OcrInput())
{
    input.AddPdf("example.pdf", "password");
    // We can also select specific PDF page numbers to OCR
    var Result = Ocr.Read(input);
    Console.WriteLine(Result.Text);
    Console.WriteLine($"{Result.Pages.Count()} Pages");
    // Read every page of the PDF
}

Dim Ocr = New IronTesseract()
Using input = New OcrInput()
	input.AddPdf("example.pdf", "password")
	' We can also select specific PDF page numbers to OCR
	Dim Result = Ocr.Read(input)
	Console.WriteLine(Result.Text)
	Console.WriteLine($"{Result.Pages.Count()} Pages")
	' Read every page of the PDF
End Using

$vbLabelText   $csharpLabel

The code is simple, clean, and very easy to understand and use.

Input PDF File

Example PDF

Wynik

IronOCR Output

4.2. AWS Textract

Amazon Textract makes it easy to add document text detection and analysis to your applications. The following code is used to read PDF and same PDF is passed:

public static async void ReturnResult()
{
    AmazonTextractClient client = new AmazonTextractClient("your_access_key_id", "your_secret_access_key", Amazon.RegionEndpoint.AFSouth1);
    var request = new StartDocumentTextDetectionRequest();
    request.DocumentLocation = new DocumentLocation
    {
        S3Object = new S3Object
        {
            Bucket = "your_bucket_name",
            Name = "your_bucket_key"
        }
    };
    var id = await client.StartDocumentTextDetectionAsync(request);
    var jobId = id.JobId;
    var response = client.GetDocumentTextDetectionAsync(new GetDocumentTextDetectionRequest{
        JobId = jobId
    });
    response.Wait();
    if (response.Result.JobStatus.Equals("SUCCEEDED"))
    {
        foreach (var block in response.Result.Blocks)
        {
            if (block.BlockType == "WORD" || block.BlockType == "PAGE" || block.BlockType == "LINE")
            {
                Console.WriteLine(block.Text);
            }
        }
    }
}

static void Main(String[] args)
{
    ReturnResult();
}

public static async void ReturnResult()
{
    AmazonTextractClient client = new AmazonTextractClient("your_access_key_id", "your_secret_access_key", Amazon.RegionEndpoint.AFSouth1);
    var request = new StartDocumentTextDetectionRequest();
    request.DocumentLocation = new DocumentLocation
    {
        S3Object = new S3Object
        {
            Bucket = "your_bucket_name",
            Name = "your_bucket_key"
        }
    };
    var id = await client.StartDocumentTextDetectionAsync(request);
    var jobId = id.JobId;
    var response = client.GetDocumentTextDetectionAsync(new GetDocumentTextDetectionRequest{
        JobId = jobId
    });
    response.Wait();
    if (response.Result.JobStatus.Equals("SUCCEEDED"))
    {
        foreach (var block in response.Result.Blocks)
        {
            if (block.BlockType == "WORD" || block.BlockType == "PAGE" || block.BlockType == "LINE")
            {
                Console.WriteLine(block.Text);
            }
        }
    }
}

static void Main(String[] args)
{
    ReturnResult();
}

Public Shared Async Sub ReturnResult()
	Dim client As New AmazonTextractClient("your_access_key_id", "your_secret_access_key", Amazon.RegionEndpoint.AFSouth1)
	Dim request = New StartDocumentTextDetectionRequest()
	request.DocumentLocation = New DocumentLocation With {
		.S3Object = New S3Object With {
			.Bucket = "your_bucket_name",
			.Name = "your_bucket_key"
		}
	}
	Dim id = Await client.StartDocumentTextDetectionAsync(request)
	Dim jobId = id.JobId
	Dim response = client.GetDocumentTextDetectionAsync(New GetDocumentTextDetectionRequest With {.JobId = jobId})
	response.Wait()
	If response.Result.JobStatus.Equals("SUCCEEDED") Then
		For Each block In response.Result.Blocks
			If block.BlockType = "WORD" OrElse block.BlockType = "PAGE" OrElse block.BlockType = "LINE" Then
				Console.WriteLine(block.Text)
			End If
		Next block
	End If
End Sub

Shared Sub Main(ByVal args() As String)
	ReturnResult()
End Sub

$vbLabelText   $csharpLabel

The code is a bit tricky, lengthy and needs attention while passing and retrieving objects. First, we have to create an AmazonTextractClient object with 3 parameters: AccessKeyId, SecretAccessKey, and Region. Then we have to initiate a request using StartDocumentTextDetectionRequest() method. The request object then sets the DocumentLocation using the bucket name and key. This request is then passed to StartDocumentTextDetectionAsync() method. As it is an async method, we have to use the await keyword and make the ReturnResult function async. Upon success, the result is returned and jobId is saved. The jobId is passed to GetDocumentTextDetectionAsync() method and wait for SUCCEEDED response. foreach loop is used to loop through each block and check if it is "WORD", "PAGE" or "LINE", then print out the text recognition. Lastly, call this method in the Main method for document processing.

Wynik

The output is pretty similar to IronOCR.

AWS Textract Output

5. Images to Text

Reading data from images is tricky as the quality of image plays a vital role while extracting information. Both the libraries provide the facility to extract text. Here we will use png files.

5.1. Using IronOCR

The code is almost similar to the previous one. Here, AddPDF method is replaced with AddImage method.

var Ocr = new IronTesseract();
using (var Input = new OcrInput())
{
    Input.AddImage("test-files/redacted-employmentapp.png");
    //... you can add any number of images
    var Result = Ocr.Read(Input);
    Console.WriteLine(Result.Text);
}

var Ocr = new IronTesseract();
using (var Input = new OcrInput())
{
    Input.AddImage("test-files/redacted-employmentapp.png");
    //... you can add any number of images
    var Result = Ocr.Read(Input);
    Console.WriteLine(Result.Text);
}

Dim Ocr = New IronTesseract()
Using Input = New OcrInput()
	Input.AddImage("test-files/redacted-employmentapp.png")
	'... you can add any number of images
	Dim Result = Ocr.Read(Input)
	Console.WriteLine(Result.Text)
End Using

$vbLabelText   $csharpLabel

Obraz wejściowy

Redacted Employee Data

Wynik

The output is clean and matches the original image with just a few lines of code without any technicality and perfect output.

Image Output

public static async void ReturnResult()
{
    AmazonTextractClient client = new AmazonTextractClient("your_access_key_id", "your_secret_access_key", Amazon.RegionEndpoint.AFSouth1);
    var request = new DetectDocumentTextRequest();
    request.Document = new Document
    {
        Bytes = new MemoryStream(File.ReadAllBytes(@"test-files/redacted-employmentapp.png"))
    };    
    var result = await client.DetectDocumentTextAsync(request);
    foreach (var block in result.Blocks)
    {
        if (block.BlockType == "WORD")
        {
            Console.WriteLine(block.Text);
        }
    }
}

static void Main(String[] args)
{
    ReturnResult();
}

public static async void ReturnResult()
{
    AmazonTextractClient client = new AmazonTextractClient("your_access_key_id", "your_secret_access_key", Amazon.RegionEndpoint.AFSouth1);
    var request = new DetectDocumentTextRequest();
    request.Document = new Document
    {
        Bytes = new MemoryStream(File.ReadAllBytes(@"test-files/redacted-employmentapp.png"))
    };    
    var result = await client.DetectDocumentTextAsync(request);
    foreach (var block in result.Blocks)
    {
        if (block.BlockType == "WORD")
        {
            Console.WriteLine(block.Text);
        }
    }
}

static void Main(String[] args)
{
    ReturnResult();
}

Public Shared Async Sub ReturnResult()
	Dim client As New AmazonTextractClient("your_access_key_id", "your_secret_access_key", Amazon.RegionEndpoint.AFSouth1)
	Dim request = New DetectDocumentTextRequest()
	request.Document = New Document With {.Bytes = New MemoryStream(File.ReadAllBytes("test-files/redacted-employmentapp.png"))}
	Dim result = Await client.DetectDocumentTextAsync(request)
	For Each block In result.Blocks
		If block.BlockType = "WORD" Then
			Console.WriteLine(block.Text)
		End If
	Next block
End Sub

Shared Sub Main(ByVal args() As String)
	ReturnResult()
End Sub

6. Barcode and QR code to Text

A unique feature of IronOCR is it can read barcodes and QR codes from documents while it is scanning for text. Instances of the OcrResult.OcrBarcode class give the developer detailed information about each scanned barcode. AWS Textract does not provide this functionality.

The code for IronOCR is given below:

var Ocr = new IronTesseract();
Ocr.Configuration.ReadBarCodes = true;
using (var input = new OcrInput())
{
    input.AddImage("test-files/Barcode.png");
    var Result = Ocr.Read(input);
    foreach (var Barcode in Result.Barcodes)
    {
        Console.WriteLine(Barcode.Value);
        // type and location properties also exposed
    }
}

var Ocr = new IronTesseract();
Ocr.Configuration.ReadBarCodes = true;
using (var input = new OcrInput())
{
    input.AddImage("test-files/Barcode.png");
    var Result = Ocr.Read(input);
    foreach (var Barcode in Result.Barcodes)
    {
        Console.WriteLine(Barcode.Value);
        // type and location properties also exposed
    }
}

Dim Ocr = New IronTesseract()
Ocr.Configuration.ReadBarCodes = True
Using input = New OcrInput()
	input.AddImage("test-files/Barcode.png")
	Dim Result = Ocr.Read(input)
	For Each Barcode In Result.Barcodes
		Console.WriteLine(Barcode.Value)
		' type and location properties also exposed
	Next Barcode
End Using

The code is self-explanatory and easy to understand.

7. Licensing

IronOCR is a library that provides a developer's license for free. It also has a distinct pricing structure; the Lite bundle starts at $799 with no hidden fees. The redistribution of SaaS and OEM products is also possible. All licenses come with a 30-day money-back guarantee, a year of software support and upgrades, dev/staging/production validity, and a perpetual license (one-time purchase). To see IronOCR's entire price structure and licensing details, go here.

IronOCR Pricing Plan

You can get the redistribution of SaaS and OEM products royalty-free service for just a $1,599 single-time purchase.

SAAS Service

AWS Textract API provides developers with AWS Free Tier service. You can get started with Amazon Textract for free. The Free Tier lasts for three months and the pricing is shown below.

Pricing List

You can have a look at the pricing details from this link. Further, you can also adjust the prices as per your needs using the pricing calculator.

8. Conclusion

IronOCR provides C# developers the most advanced Tesseract API we know of, on any platform. IronOCR can be deployed on Windows, Linux, Mac, Azure, AWS, Lambda and supports .NET Framework projects as well as .NET Standard and .NET Core. We can also read barcodes in OCR scans, and even export our OCR as HTML and searchable PDFs.

Amazon Textract makes it easy to add document text detection and analysis to your applications. Amazon Textract is based on the proven, highly scałable, deep-learning technology that was developed by Amazon's computer vision scientists to analyze billions of images and videos daily. You don't need any machine learning expertise to use it. Amazon Textract includes simple, easy-to-use APIs that can analyze image files and PDF files. Amazon Textract is always learning from new data, and Amazon is continually adding new features to the service.

IronOCR licenses are developer-based, which means you should always purchase a license based on the number of developers who will use the product. AWS Textract licenses are based on the number of pages of the document to extract information and analyze the data. The licenses are on a monthly basis and the prices become very high for a large number of pages compared to the IronOCR license. Moreover, IronOCR license is a one-time purchase and it can be used for a lifetime and it supports OME and SaaS distribution.

In overall comparison, IronOCR and AWS OCR both have machine learning capabilities to detect text from a document or image. IronOCR has a slight advantage over AWS OCR as it's fast and time-saving. The code is simple and it's straightforward when detecting text from documents. The task is accomplished in a few methods. On the other hand, AWS Textract uses many methods to achieve the same task. This increases the server response and sometimes it's time-consuming. We can see that if we input even an imperfect document to IronOCR, it can accurately read its content to a statistical accuracy of about 99%, even though the document was badly formatted, skewed, and had digital noise. IronOCR works out of the box with no need to performance tune or heavily modify input images. Speed is blazing: IronOCR.2020+ is up to 10 times faster and makes over 250% fewer errors than previous builds.

Further, Iron Software is currently offering a five-tool package for the price of just two. The tools included in the Iron Suite are:

• IronBarcode
• IronXL
• IronOCR
• IronPDF
• IronWebScraper

Please visit this link to explore the IRONSUITE.