You can create a dynamic web application that analyzes nature images located in an Amazon Simple Storage service (Amazon S3) bucket by using the Amazon Rekognition service and the AWS SDK for .NET. After analyzing the images in the S3 bucket, the application generates a report that breaks down each image into a series of labels. For example, the following image shows a lake at sunrise.
After the application analyzes the images, it uses the Amazon Simple Email service (Amazon SES) to send an email message that contains the label data, as shown in the following illustration. For example, some labels for the preceding photo are Outdoors, Sky, and Sun.
In this tutorial, you use the following AWS services:
- Amazon Rekognition
- Amazon S3
- Amazon SES
- Prerequisites
- Understand the application
- Create a .NET Web App project
- Add the AWS packages
- Create the classes
- Modify the CSHTML file
- Run the application
- Next steps
To complete the tutorial, you need the following:
- An AWS account. For more information, see the AWS SDKS and Tools Reference Guide.
- A .NET IDE. This tutorial uses Microsoft Visual Studio.
- .NET Core 5.0 or greater.
- AWS SDK for .NET 3.5 or later.
- The AWS services used by this application are included in the AWS Free Tier.
- This code has not been tested in all AWS Regions. Some AWS services are available only in specific Regions. For more information, see AWS Regional Services.
- Running this code might result in charges to your AWS account.
- Be sure to delete all of the resources that you create while going through this tutorial to ensure that you’re not charged.
Create an S3 bucket named photos[somevalue] and upload five or six nature images. Be sure to use this bucket name in your Amazon S3 .NET code. For more information about creating a bucket, see Creating a bucket.
In addition, make sure that you set up your .NET developer environment before following along with this tutorial. For more information, see Setting up your AWS SDK for .NET environment.
The AWS Photo Analyzer application supports viewing the images that are analyzed. To view the images, choose Get Images.
To generate a report, enter an email address and choose Analyze Photos.
Create a MVC .Net Web App project using Visual Studio. Name it PhotoAnalyzerApp.
-
In Visual Studio, choose File, New, Project.
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In the New Project dialog box, choose ASP .NET Core Web App.
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Choose Next.
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In the Project Name field, enter PhotoAnalyzerApp.
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Choose Next.
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Make sure that the Target Framework is set to .NET Core 5.0 (or make sure that the current version of .NET Core is selected).
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Choose Create.
At this point, you have a new project named PhotoAnalyzerApp. You must add the required AWS packages to your project. They are AWSSDK.Core, AWSSDK.Rekognition, AWSSDK.S3, and AWSSDK.SimpleEmail, as shown in the following illustration.
After you add the packages, you can use the AWS SDK for .NET in your project.
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In the Solution Explorer, choose or right-click the project name, PhotoAnalyzerApp.
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Select Manage NuGet Packages....
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When the NuGet packages dialog opens, choose Browse.
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In the Search field, enter AWSSDK.Core.
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Select the AWSSDK.Core package from the list. Then, in the right pane, choose Install. After installation, you can see the package.
Note: Repeat this process to add the AWSSDK.Rekognition, AWSSDK.S3, and AWSSDK.SimpleEmail packages.
Tip: If you don't see the AWS packages after you add them, confirm that your NuGet is properly configured to use nuget.org. The following illustration shows nuget.org with source https://api.nuget.org/v3/index.json selected under the Package Sources for NuGet Package Manager.
The following illustration shows the structure of this .NET project.
Note: To keep this tutorial simple, the .NET classes are placed in the same namespace as the Controller. However, you can place them in other namespaces if you prefer.
You work with the following .NET classes:
- HomeController - Used as the .NET controller that handles HTTP requests.
- AWSService - Used to invoke service operations by using the Amazon S3, Amazon Rekognition, and Amazon SES .NET API operations. You can create this class in the same location as the HomeController.
- BucketItem - Used as a model that stores S3 bucket information.
- WorkItem - Used as a model that stores Amazon Rekognition data.
Note: You need to add the AWSService, BucketItem, and WorkItem classes to your project.
The following C# code represents the HomeController class. Because the Async version of the AWS SDK for .NET is used, notice that the controller methods have to use async keywords and the return values are defined using Task.
using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Threading.Tasks;
using Microsoft.AspNetCore.Mvc;
using Microsoft.Extensions.Logging;
using PhotoAnalyzerApp.Models;
namespace PhotoAnalyzerApp.Controllers
{
public class HomeController : Controller
{
private readonly ILogger<HomeController> _logger;
private string bucketName = "<Enter your bucket name>";
[HttpGet]
public async Task<ActionResult> GetObjects()
{
var awsService = new AWSService();
var xml = await awsService.ListBucketObjects(bucketName);
return Content(xml);
}
[HttpPost]
public async Task<ActionResult> GetReport(string email)
{
var myemail = email;
var awsService = new AWSService();
List<List<WorkItem>> myList = new List<List<WorkItem>>();
var myNameList = await awsService.ListBucketNames(bucketName);
foreach (var obName in myNameList)
{
List<WorkItem> labelList = await awsService.DetectLabels(bucketName, obName);
myList.Add(labelList);
}
// Now we have a list of WorkItems describing the photos in the S3 bucket.
var xmlReport = awsService.GenerateXMLFromList(myList);
awsService.SendMessage(xmlReport, myemail);
return Content("Report was sent with " + myList.Count() + " items.");
}
public HomeController(ILogger<HomeController> logger)
{
_logger = logger;
}
public IActionResult Index()
{
return View();
}
public IActionResult Process()
{
return View();
}
public IActionResult Privacy()
{
return View();
}
[ResponseCache(Duration = 0, Location = ResponseCacheLocation.None, NoStore = true)]
public IActionResult Error()
{
return View(new ErrorViewModel { RequestId = Activity.Current?.Id ?? HttpContext.TraceIdentifier });
}
}
}Note: Be sure to specify the bucket name for the bucketName variable.
The following C# code represents the AWSService class. This class uses the AWS .NET Rekognition API to analyze photos retrieved from an S3 bucket. The DetectLabels method returns a List object where each element is a WorkItem object that stores the label data. Likewise, the ListBucketNames method uses the Amazon S3 API to return a List object where each element is a string that specifies the object name. The SendMessage method uses the Amazon SES API to send an email message that contains the label data.
Here is the code for AWSService.
using System;
using System.Collections.Generic;
using System.Threading.Tasks;
using System.Xml;
using Amazon;
using Amazon.Rekognition;
using Amazon.Rekognition.Model;
using Amazon.S3;
using Amazon.S3.Model;
using Amazon.SimpleEmail;
using Amazon.SimpleEmail.Model;
namespace PhotoAnalyzerApp.Controllers
{
public class AWSService
{
public async void SendMessage(string text, string toAddress)
{
var sesClient = new AmazonSimpleEmailServiceClient(RegionEndpoint.USWest2);
var sender = "<Enter a valid email address>";
var emailList = new List<string>();
emailList.Add(toAddress);
var destination = new Destination
{
ToAddresses = emailList
};
var content = new Content
{
Data = text
};
var sub = new Content
{
Data = "Amazon Rekognition Report"
};
var body = new Body
{
Text = content
};
var message = new Message
{
Subject = sub,
Body = body
};
var request = new SendEmailRequest
{
Message = message,
Destination = destination,
Source = sender
};
try
{
await sesClient.SendEmailAsync(request);
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
// Uses the Amazon Rekognition service to detect labels within an image.
public async Task<List<WorkItem>> DetectLabels(string bucketName, string photo)
{
var rekognitionClient = new AmazonRekognitionClient(RegionEndpoint.USWest2);
var labelList = new List<WorkItem>();
var detectlabelsRequest = new DetectLabelsRequest
{
Image = new Image()
{
S3Object = new Amazon.Rekognition.Model.S3Object()
{
Name = photo,
Bucket = bucketName,
},
},
MaxLabels = 10,
MinConfidence = 75F,
};
try
{
DetectLabelsResponse detectLabelsResponse = await rekognitionClient.DetectLabelsAsync(detectlabelsRequest);
Console.WriteLine("Detected labels for " + photo);
WorkItem workItem;
foreach (Label label in detectLabelsResponse.Labels)
{
workItem = new WorkItem();
workItem.Key = photo;
workItem.Confidence = label.Confidence.ToString();
workItem.Name = label.Name;
labelList.Add(workItem);
}
return labelList;
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
return null;
}
// Returns object names in the S3 bucket.
public async Task<List<string>> ListBucketNames(string bucketName)
{
var s3Client = new AmazonS3Client(RegionEndpoint.USWest2);
var obList = new List<Amazon.S3.Model.S3Object>();
var obName = new List<string>();
var listRequest = new ListObjectsRequest
{
BucketName = bucketName,
};
ListObjectsResponse response = await s3Client.ListObjectsAsync(listRequest);
obList = response.S3Objects;
foreach (var myobj in obList)
obName.Add(myobj.Key);
return obName;
}
// Returns information about all images in the given S3 bucket.
public async Task<string> ListBucketObjects(string bucketName)
{
var s3Client = new AmazonS3Client(RegionEndpoint.USWest2);
var obList = new List<Amazon.S3.Model.S3Object>();
var obName = new List<BucketItem>();
var listRequest = new ListObjectsRequest
{
BucketName = bucketName,
};
ListObjectsResponse response = await s3Client.ListObjectsAsync(listRequest);
obList = response.S3Objects;
BucketItem myItem;
foreach (var myobj in obList)
{
myItem = new BucketItem();
myItem.Key = myobj.Key;
myItem.Owner = myobj.Owner.DisplayName;
long sizeLg = myobj.Size / 1024;
myItem.Size = sizeLg.ToString();
obName.Add(myItem);
}
var xml = GenerateXML(obName);
return xml;
}
// Convert the list to XML to pass back to the view.
private string GenerateXML(List<BucketItem> obList)
{
XmlDocument doc = new XmlDocument();
XmlNode docNode = doc.CreateXmlDeclaration("1.0", "UTF-8", null);
doc.AppendChild(docNode);
XmlNode subsNode = doc.CreateElement("Items");
doc.AppendChild(subsNode);
// Iterate through the collection.
foreach (BucketItem item in obList)
{
XmlNode subNode = doc.CreateElement("Item");
subsNode.AppendChild(subNode);
XmlNode name = doc.CreateElement("Key");
name.AppendChild(doc.CreateTextNode(item.Key));
subNode.AppendChild(name);
XmlNode owner = doc.CreateElement("Owner");
owner.AppendChild(doc.CreateTextNode(item.Owner));
subNode.AppendChild(owner);
XmlNode size = doc.CreateElement("Size");
size.AppendChild(doc.CreateTextNode(item.Size));
subNode.AppendChild(size);
}
return doc.OuterXml;
}
// Convert the list to XML to pass back to the view.
public string GenerateXMLFromList(List<List<WorkItem>> obList)
{
XmlDocument doc = new XmlDocument();
XmlNode docNode = doc.CreateXmlDeclaration("1.0", "UTF-8", null);
doc.AppendChild(docNode);
XmlNode subsNode = doc.CreateElement("Items");
doc.AppendChild(subsNode);
// Iterate through the outer list.
foreach (var listItem in obList)
{
// Iterate through the collection of WorkItem objects.
foreach (WorkItem item in listItem)
{
XmlNode subNode = doc.CreateElement("Item");
subsNode.AppendChild(subNode);
XmlNode name = doc.CreateElement("Photo");
name.AppendChild(doc.CreateTextNode(item.Key));
subNode.AppendChild(name);
XmlNode owner = doc.CreateElement("Confidence");
owner.AppendChild(doc.CreateTextNode(item.Confidence));
subNode.AppendChild(owner);
XmlNode size = doc.CreateElement("Label");
size.AppendChild(doc.CreateTextNode(item.Name));
subNode.AppendChild(size);
}
}
return doc.OuterXml;
}
}
}Note: Update the email sender address with a verified email address. For more information, see Verifying an identity for Amazon SES sending authorization.
Here is the code for WorkItem.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;
namespace PhotoAnalyzerApp.Controllers
{
public class WorkItem
{
public string Key { get; set; }
public string Name { get; set; }
public string Confidence { get; set; }
}
}Here is the code for BucketItem.
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;
namespace PhotoAnalyzerApp.Controllers
{
public class BucketItem
{
public string Key { get; set; }
public string Owner { get; set; }
public string Size { get; set; }
}
}At this point, you have created all of the .NET classes required for this example application. Now, modify the index.cshtml file required for the application's view. This file exists in the Views/Home folder, as shown in this illustration.
The index.cshtml file is the application's home view.
@{
ViewData["Title"] = "Home Page";
}
<head>
<script src="https://code.jquery.com/jquery-1.11.1.min.js"></script>
<script src="https://code.jquery.com/ui/1.11.1/jquery-ui.min.js"></script>
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" />
</head>
<h1 class="display-4">AWS Photo Analyzer application</h1>
<p>
The AWS Photo Analyzer application is a sample application that uses Amazon Rekognition, other AWS services, and the AWS SDK for .NET.
Analyzing nature photographs has never been easier! Perform the following steps:
<p>
<ol>
<li>You can choose <i>Get Images</i> to view the images located in the S3 bucket. All images in the S3 bucket are displayed in the table. </li>
<li>You can analyze the photographs and produce a report by choosing the <i>Analyze Photos</i> menu item. </li>
<li>Enter an email address in the email field and choose <i>Analyze Photos</i>. </li>
<li>Amazon SES is used to send an email that contains label data to the specified email recipient.</li>
</ol>Create a second CSHTML file named Process.cshtml that is located in the same folder as Index.cshtml. Add the following code to this file.
@{
ViewData["Title"] = "Process Page";
}
<head>
<script src="https://code.jquery.com/jquery-1.11.1.min.js"></script>
<script src="https://code.jquery.com/ui/1.11.1/jquery-ui.min.js"></script>
<script src="https://cdn.datatables.net/v/dt/dt-1.10.20/datatables.min.js"></script>
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" />
<link rel="stylesheet" href="https://cdn.datatables.net/v/dt/dt-1.10.20/datatables.min.css" />
</head>
<script>
$(function () {
$.noConflict();
$("#bar").hide()
$('#myTable').DataTable({
scrollY: "500px",
scrollX: true,
scrollCollapse: true,
paging: true,
columnDefs: [
{ width: 200, targets: 0 }
],
fixedColumns: true
});
});
function GetReport() {
// Post the values to the controller.
$("#bar").show()
var email = $('#email').val();
if (email == "") {
alert("Please enter an email address");
return;
}
$.ajax('GetReport', {
type: 'POST', // http method
data: 'email=' + email, // data to submit
success: function (data, status, xhr) {
$("#bar").hide()
alert(data);
},
});
}
function ProcessImages() {
// Post the values to the controller.
$("#bar").show()
var email = $('#email').val();
$.ajax('GetObjects', {
type: 'GET', // http method
success: function (data, status, xhr) {
$("#bar").hide()
var xml = data
var oTable = $('#myTable').dataTable();
oTable.fnClearTable(true);
$(xml).find('Item').each(function () {
var $field = $(this);
var key = $field.find('Key').text();
var name = $field.find('Owner').text();
var size = $field.find('Size').text();
//Set the new data.
oTable.fnAddData([
key,
name,
size]
);
});
},
});
}
</script>
<h1 class="display-4">AWS Photo Analyzer Application</h1>
<p>You can generate a report that analyzes the images in the S3 bucket. You can send the report to the following email address. </p>
<label for="email">Email address:</label>
<br>
<input type="text" id="email" name="email" value="">
<br>
<div id="bar" class="progress">
<div class="progress-bar progress-bar-striped active" role="progressbar"
aria-valuenow="40" aria-valuemin="0" aria-valuemax="100" style="width:90%">
Generating report
</div>
</div>
<p>Choose the following button to get a report</p>
<button onclick="GetReport()">Analyze Photos</button>
<div>
<br>
<p>Choose the following button to determine the number of images in the bucket</p>
<button onclick="ProcessImages()">Get Images</button>
<table id="myTable" class="display" style="width:100%">
<thead>
<tr>
<th>Name</th>
<th>Owner</th>
<th>Size</th>
</tr>
</thead>
<tbody>
<tr>
<td>No data</td>
<td>No data</td>
<td>No data</td>
</tr>
</tbody>
<tfoot>
<tr>
<th>Name</th>
<th>Owner</th>
<th>Size</th>
</tr>
</tfoot>
<div id="success3"></div>
</table>
</div>Note: Update the menu by adding this code to the Layout.cshtml file.
<li class="nav-item">
<a class="nav-link text-dark" asp-area="" asp-controller="Home" asp-action="Process">Analyze Photos</a>
</li>You can run your application from your IDE. The home page looks like the following image.
Congratulations! You have created a .NET MVC application that analyzes photos located in an S3 bucket. When you're done working with the example, remember to delete all of the resources that you created while following this tutorial to ensure that you won't be charged.
Copyright (c) Amazon.com, Inc. or its affiliates. All Rights Reserved. SPDX-License-Identifier: Apache-2.0