public StreamManager(
String spName,
String kvStreamArn,
String kdStreamArn,
String iamRoleArn,
String collId,
float threshold)
{
streamProcessorName = spName;
kinesisVideoStreamArn = kvStreamArn;
kinesisDataStreamArn = kdStreamArn;
roleArn = iamRoleArn;
collectionId = collId;
matchThreshold = threshold;
rekognitionClient = new AmazonRekognitionClient(MyAWSConfigs.faceCollectionRegion);
}
public static void Example()
{
String photo = "moviestars.jpg";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
RecognizeCelebritiesRequest recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();
Amazon.Rekognition.Model.Image img = new Amazon.Rekognition.Model.Image();
byte[] data = null;
try
{
using (FileStream fs = new FileStream(photo, FileMode.Open, FileAccess.Read))
{
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
}
}
catch (Exception)
{
Console.WriteLine("Failed to load file " + photo);
return;
}
img.Bytes = new MemoryStream(data);
recognizeCelebritiesRequest.Image = img;
Console.WriteLine("Looking for celebrities in image " + photo + "\n");
RecognizeCelebritiesResponse recognizeCelebritiesResponse = rekognitionClient.RecognizeCelebrities(recognizeCelebritiesRequest);
Console.WriteLine(recognizeCelebritiesResponse.CelebrityFaces.Count + " celebrity(s) were recognized.\n");
foreach (Celebrity celebrity in recognizeCelebritiesResponse.CelebrityFaces)
{
Console.WriteLine("Celebrity recognized: " + celebrity.Name);
Console.WriteLine("Celebrity ID: " + celebrity.Id);
BoundingBox boundingBox = celebrity.Face.BoundingBox;
Console.WriteLine("position: " +
boundingBox.Left + " " + boundingBox.Top);
Console.WriteLine("Further information (if available):");
foreach (String url in celebrity.Urls)
{
Console.WriteLine(url);
}
}
Console.WriteLine(recognizeCelebritiesResponse.UnrecognizedFaces.Count + " face(s) were unrecognized.");
}
/// <summary>
/// This method is called for every Lambda invocation. This method takes in an S3 event object and can be used
/// to respond to S3 notifications.
/// </summary>
/// <param name="evnt"></param>
/// <param name="context"></param>
/// <returns></returns>
public async Task <string> FunctionHandler(S3Event evnt, ILambdaContext context)
{
var s3Event = evnt.Records?[0].S3;
if (s3Event == null)
{
return(null);
}
try
{
AmazonRekognitionClient client = new AmazonRekognitionClient(RegionEndpoint.USEast1);
// get the file's name from event
string imageTitle = s3Event.Object.Key;
DetectTextRequest q = new DetectTextRequest();
// get the file from S3
Image img = new Image()
{
S3Object = getObject(imageTitle)
};
q.Image = img;
// detect text from the image
var task = client.DetectTextAsync(q, new System.Threading.CancellationToken());
task.Wait();
DetectTextResponse r = task.Result;
string plate = "";
// filter recognized text
foreach (TextDetection t in r.TextDetections)
{
if (isCapitaLettersNumbers(t.DetectedText))
{
plate = t.DetectedText;
//send message to plate's owner
sendMessage(plate);
}
}
}
catch (Exception e)
{
context.Logger.LogLine($"Error getting object {s3Event.Object.Key} from bucket {s3Event.Bucket.Name}. Make sure they exist and your bucket is in the same region as this function.");
context.Logger.LogLine(e.Message);
context.Logger.LogLine(e.StackTrace);
throw;
}
return("Lamda has returned");
}
public async Task <ModerationResponse> AnalyzeImage(MemoryStream imageStream)
{
using (var client = new AmazonRekognitionClient(Endpoint))
{
var request = new DetectModerationLabelsRequest()
{
Image = new Image()
{
Bytes = imageStream
},
MinConfidence = 0 //do this so that scores are always returned?
};
var awsResponse = await client.DetectModerationLabelsAsync(request);
var response = new ModerationResponse();
if (awsResponse.HttpStatusCode != System.Net.HttpStatusCode.OK)
{
response.Pass = false;
response.ModerationScores = new[] { new ModerationScore()
{
Category = $"ServerError:{awsResponse.HttpStatusCode}", Score = 100
} };
}
else
{
if (awsResponse.ModerationLabels.Any(s => s.Confidence >= 50))
{
response.Pass = false;
}
else
{
response.Pass = true;
}
response.ModerationScores = awsResponse.ModerationLabels
.Select(m => new ModerationScore()
{
Category = $"{m.ParentName}:{m.Name}",
Score = m.Confidence
});
}
return(response);
}
}
public List <FaceRecord> Recognize(string collectionId, Amazon.Rekognition.Model.Image image)
{
//1- Detect faces in the input image and adds them to the specified collection.
AmazonRekognitionClient rekognitionClient = AmazonClient.GetInstance();
IndexFacesRequest indexFacesRequest = new IndexFacesRequest()
{
Image = image,
CollectionId = collectionId,
DetectionAttributes = new List <String>()
{
"DEFAULT"
}
};
IndexFacesResponse indexFacesResponse = rekognitionClient.IndexFaces(indexFacesRequest);
//2- Search all detected faces in the collection
SearchFacesResponse searchFacesResponse = null;
List <FaceRecord> matchedFaces = new List <FaceRecord>();
if (null != indexFacesResponse && null != indexFacesResponse.FaceRecords && 0 != indexFacesResponse.FaceRecords.Count)
{
foreach (FaceRecord face in indexFacesResponse.FaceRecords)
{
searchFacesResponse = rekognitionClient.SearchFaces(new SearchFacesRequest
{
CollectionId = collectionId,
FaceId = face.Face.FaceId,
FaceMatchThreshold = 70F,
MaxFaces = 2
});
if (searchFacesResponse.FaceMatches != null && searchFacesResponse.FaceMatches.Count != 0)
{
matchedFaces.Add(face);
}
}
//Remove newly added faces to the collection
_collectionService.RemoveFacesFromCollection(collectionId, indexFacesResponse.FaceRecords.Select(x => x.Face.FaceId).ToList());
}
return(matchedFaces);
}
private static void searchFace(Amazon.Rekognition.Model.Image image, AmazonRekognitionClient rekognitionClient)
{
String collectionId = "MyCollection";
SearchFacesByImageRequest request = new SearchFacesByImageRequest()
{
CollectionId = collectionId,
Image = image
};
SearchFacesByImageResponse response = rekognitionClient.SearchFacesByImage(request);
foreach (FaceMatch face in response.FaceMatches)
{
Console.WriteLine("FaceId: " + face.Face.FaceId + ", Similarity: " + face.Similarity);
}
}
private void btn_DetectAdultContent_Click(object sender, EventArgs e)
{
txt_adultContent.Text = "";
var source = ToBytesStream($"{sourceAdultContent}");
var client = new AmazonRekognitionClient();
var request = new DetectModerationLabelsRequest
{
Image = source
};
var response = client.DetectModerationLabels(request);
txt_adultContent.Text = ($"Found {response.ModerationLabels.Count} labels: \n");
foreach (var label in response.ModerationLabels)
{
txt_adultContent.Text += $"- {label.Name}\n";
}
}
// snippet-start:[Rekognition.dotnetv3.DeleteCollectionExample]
public static async Task Main()
{
var rekognitionClient = new AmazonRekognitionClient();
string collectionId = "MyCollection";
Console.WriteLine("Deleting collection: " + collectionId);
var deleteCollectionRequest = new DeleteCollectionRequest()
{
CollectionId = collectionId,
};
var deleteCollectionResponse = await rekognitionClient.DeleteCollectionAsync(deleteCollectionRequest);
Console.WriteLine($"{collectionId}: {deleteCollectionResponse.StatusCode}");
}
public static IAsyncOperation <string> GetFaceDetails(string base64, string AccessKey, string SecretKey)
{
return(Task.Run <string>(async() =>
{
byte[] imageBytes;
try
{
base64 = base64.Substring(base64.IndexOf(',') + 1).Trim('\0');
imageBytes = System.Convert.FromBase64String(base64);
}
catch (Exception e) {
return e.Message;
}
string sJSONResponse = "";
AWSCredentials credentials;
try
{
credentials = new BasicAWSCredentials(AccessKey, SecretKey);
}
catch (Exception e)
{
throw new AmazonClientException("Cannot load the credentials from the credential profiles file. "
+ "Please make sure that your credentials file is at the correct "
+ "location (/Users/<userid>/.aws/credentials), and is in a valid format.", e);
}
DetectFacesRequest request = new DetectFacesRequest {
Attributes = new List <string>(new string[] { "ALL" })
};
DetectFacesResponse result = null;
request.Image = new Image {
Bytes = new MemoryStream(imageBytes, 0, imageBytes.Length)
};
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(credentials, RegionEndpoint.USWest2);
try
{
result = await rekognitionClient.DetectFacesAsync(request);
}
catch (AmazonRekognitionException e)
{
throw e;
}
// Return server status as unhealthy with appropriate status code
sJSONResponse = JsonConvert.SerializeObject(result.FaceDetails);
return sJSONResponse;
}).AsAsyncOperation());
}
public static string Create(string _collectionId)
{
if (GetFaceCollectionList().Contains(_collectionId))
{
return("");
}
string collectionId = _collectionId;
string collectionArn = "";
try
{
using (rekognitionClient = new AmazonRekognitionClient(collectionRegion))
{
CreatingCollection();
}
void CreatingCollection()
{
Console.WriteLine("Creating collection: " + collectionId);
CreateCollectionRequest createCollectionRequest = new CreateCollectionRequest()
{
CollectionId = collectionId
};
CreateCollectionResponse createCollectionResponse = rekognitionClient.CreateCollection(createCollectionRequest);
collectionArn = createCollectionResponse.CollectionArn;
Console.WriteLine("Status code : " + createCollectionResponse.StatusCode);
}
}
catch (AmazonRekognitionException e)
{
Console.WriteLine("AmazonRekognitionException: " + e);
collectionArn = "error";
}
catch (Exception e)
{
Console.WriteLine("Error: " + e);
collectionArn = "error";
}
return(collectionArn);
}
/// <summary>
/// Get Face Matches for Celebrities from Amazon service
/// </summary>
/// <param name="photo"></param>
/// <returns></returns>
public async Task <ResponseDTO> GetMatches(IFormFile photo)
{
try
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient(_awsCredentials.Value.Id, _awsCredentials.Value.Key, Amazon.RegionEndpoint.USEast2);
RecognizeCelebritiesRequest recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();
Image img = new Image();
byte[] data = null;
try
{
if (photo.Length > 0)
{
using (var ms = new MemoryStream())
{
photo.CopyTo(ms);
data = ms.ToArray();
}
}
}
catch (Exception ex)
{
throw ex;
}
img.Bytes = new MemoryStream(data);
recognizeCelebritiesRequest.Image = img;
RecognizeCelebritiesResponse recognizeCelebritiesResponse = await rekognitionClient.RecognizeCelebritiesAsync(recognizeCelebritiesRequest);
foreach (Celebrity celebrity in recognizeCelebritiesResponse.CelebrityFaces)
{
CelebrityDetail.Name = celebrity.Name;
foreach (string url in celebrity.Urls)
{
CelebrityDetail.Url = url;
}
CelebrityDetails.Add(CelebrityDetail);
CelebrityDetail = new CelebrityDetail();
}
ResponseDetail.CelebrityDetails = CelebrityDetails;
ResponseDetail.UnMatchCount = recognizeCelebritiesResponse.UnrecognizedFaces.Count;
return(ResponseDetail);
}
catch (Exception ex)
{
throw ex;
}
}
static void IdentifyFaces(string filename)
{
// Using USWest2, not the default region
AmazonRekognitionClient rekoClient = new AmazonRekognitionClient(Amazon.RegionEndpoint.USWest2);
DetectFacesRequest dfr = new DetectFacesRequest();
// Request needs image butes, so read and add to request
Amazon.Rekognition.Model.Image img = new Amazon.Rekognition.Model.Image();
byte[] data = null;
using (FileStream fs = new FileStream(filename, FileMode.Open, FileAccess.Read))
{
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
}
img.Bytes = new MemoryStream(data);
dfr.Image = img;
var outcome = rekoClient.DetectFaces(dfr);
// Load a bitmap to modify with face bounding box rectangles
System.Drawing.Bitmap facesHighlighted = new System.Drawing.Bitmap(filename);
Pen pen = new Pen(Color.Black, 3);
// Create a graphics context
using (var graphics = Graphics.FromImage(facesHighlighted))
{
foreach (var fd in outcome.FaceDetails)
{
// Get the bounding box
BoundingBox bb = fd.BoundingBox;
Console.WriteLine("Bounding box = (" + fd.BoundingBox.Left + ", " + fd.BoundingBox.Top + ", " +
fd.BoundingBox.Height + ", " + fd.BoundingBox.Width + ")");
// Draw the rectangle using the bounding box values
// They are percentages so scale them to picture
graphics.DrawRectangle(pen, x: facesHighlighted.Width * bb.Left,
y: facesHighlighted.Height * bb.Top,
width: facesHighlighted.Width * bb.Width,
height: facesHighlighted.Height * bb.Height);
}
}
// Save the image with highlights as PNG
string fileout = filename.Replace(Path.GetExtension(filename), "_faces.png");
facesHighlighted.Save(fileout, System.Drawing.Imaging.ImageFormat.Png);
Console.WriteLine(">>> Faces highlighted in file " + fileout);
}
// snippet-start:[Rekognition.dotnetv3.CelebritiesInImageExample]
public static async Task Main(string[] args)
{
string photo = "moviestars.jpg";
var rekognitionClient = new AmazonRekognitionClient();
var recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();
var img = new Amazon.Rekognition.Model.Image();
byte[] data = null;
try
{
using var fs = new FileStream(photo, FileMode.Open, FileAccess.Read);
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
}
catch (Exception)
{
Console.WriteLine($"Failed to load file {photo}");
return;
}
img.Bytes = new MemoryStream(data);
recognizeCelebritiesRequest.Image = img;
Console.WriteLine($"Looking for celebrities in image {photo}\n");
var recognizeCelebritiesResponse = await rekognitionClient.RecognizeCelebritiesAsync(recognizeCelebritiesRequest);
Console.WriteLine($"{recognizeCelebritiesResponse.CelebrityFaces.Count} celebrity(s) were recognized.\n");
recognizeCelebritiesResponse.CelebrityFaces.ForEach(celeb =>
{
Console.WriteLine($"Celebrity recognized: {celeb.Name}");
Console.WriteLine($"Celebrity ID: {celeb.Id}");
BoundingBox boundingBox = celeb.Face.BoundingBox;
Console.WriteLine($"position: {boundingBox.Left} {boundingBox.Top}");
Console.WriteLine("Further information (if available):");
celeb.Urls.ForEach(url =>
{
Console.WriteLine(url);
});
});
Console.WriteLine($"{recognizeCelebritiesResponse.UnrecognizedFaces.Count} face(s) were unrecognized.");
}
public void RekognitionDeleteFaces()
{
#region to-delete-a-face-1482182799377
var client = new AmazonRekognitionClient();
var response = client.DeleteFaces(new DeleteFacesRequest
{
CollectionId = "myphotos",
FaceIds = new List <string> {
"ff43d742-0c13-5d16-a3e8-03d3f58e980b"
}
});
List <string> deletedFaces = response.DeletedFaces;
#endregion
}
public static void Example()
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
String collectionId = "MyCollection";
Console.WriteLine("Deleting collection: " + collectionId);
DeleteCollectionRequest deleteCollectionRequest = new DeleteCollectionRequest()
{
CollectionId = collectionId
};
DeleteCollectionResponse deleteCollectionResponse = rekognitionClient.DeleteCollection(deleteCollectionRequest);
Console.WriteLine(collectionId + ": " + deleteCollectionResponse.StatusCode);
}
private string CompareFaces(string strPersonName, MemoryStream msCapture, MemoryStream msFacePic)
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient("", "", Amazon.RegionEndpoint.USEast1);
CompareFacesRequest req = new CompareFacesRequest();
Amazon.Rekognition.Model.Image src = new Amazon.Rekognition.Model.Image();
src.Bytes = msCapture;
req.SourceImage = src;
Amazon.Rekognition.Model.Image trg = new Amazon.Rekognition.Model.Image();
trg.Bytes = msFacePic;
req.TargetImage = trg;
try
{
CompareFacesResponse compareFacesResult = rekognitionClient.CompareFaces(req);
List <CompareFacesMatch> faceDetails = compareFacesResult.FaceMatches;
ComparedFace face = null;
foreach (CompareFacesMatch match in faceDetails)
{
face = match.Face;
BoundingBox position = face.BoundingBox;
System.Diagnostics.Debug.Write("Face at " + position.Left
+ " " + position.Top
+ " matches with " + face.Confidence
+ "% confidence.");
if (face.Confidence > 75)
{
return(strPersonName);
}
}
}
catch (Exception ex)
{
return("Fail");
}
return("Unknown");
}
public static void Example()
{
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
String collectionId = "MyCollection";
Console.WriteLine("Creating collection: " + collectionId);
CreateCollectionRequest createCollectionRequest = new CreateCollectionRequest()
{
CollectionId = collectionId
};
CreateCollectionResponse createCollectionResponse = rekognitionClient.CreateCollection(createCollectionRequest);
Console.WriteLine("CollectionArn : " + createCollectionResponse.CollectionArn);
Console.WriteLine("Status code : " + createCollectionResponse.StatusCode);
}
public void SearchFaces(string fileName, string bucketName)
{
IAmazonRekognition rekoClient = new AmazonRekognitionClient(Amazon.RegionEndpoint.USEast1);
var response = rekoClient.SearchFacesByImage(new SearchFacesByImageRequest
{
CollectionId = "myphotos",
FaceMatchThreshold = 95,
Image = new Amazon.Rekognition.Model.Image
{
S3Object = new Amazon.Rekognition.Model.S3Object
{
Bucket = bucketName,
Name = fileName,
}
},
MaxFaces = 5
});
}
// snippet-start:[Rekognition.dotnetv3.CreateCollectionExample]
public static async Task Main()
{
var rekognitionClient = new AmazonRekognitionClient();
string collectionId = "MyCollection";
Console.WriteLine("Creating collection: " + collectionId);
var createCollectionRequest = new CreateCollectionRequest
{
CollectionId = collectionId,
};
CreateCollectionResponse createCollectionResponse = await rekognitionClient.CreateCollectionAsync(createCollectionRequest);
Console.WriteLine($"CollectionArn : {createCollectionResponse.CollectionArn}");
Console.WriteLine($"Status code : {createCollectionResponse.StatusCode}");
}
private async Task <object> GetImageLabels(string fileName, AmazonRekognitionClient rekognitionClient)
{
var detectResponses = await rekognitionClient.DetectLabelsAsync(new DetectLabelsRequest
{
MinConfidence = 50,
Image = new Image
{
S3Object = new Amazon.Rekognition.Model.S3Object
{
Bucket = bucketName,
Name = fileName
}
}
});
return(detectResponses.Labels);
}
public void RekognitionSearchFaces()
{
#region to-delete-a-face-1482182799377
var client = new AmazonRekognitionClient();
var response = client.SearchFaces(new SearchFacesRequest
{
CollectionId = "myphotos",
FaceId = "70008e50-75e4-55d0-8e80-363fb73b3a14",
FaceMatchThreshold = 90,
MaxFaces = 10
});
List <FaceMatch> faceMatches = response.FaceMatches;
string searchedFaceId = response.SearchedFaceId;
#endregion
}
// snippet-start:[Rekognition.dotnetv3.DetectLabelsLocalFile]
public static async Task Main()
{
string photo = "input.jpg";
var image = new Amazon.Rekognition.Model.Image();
try
{
using var fs = new FileStream(photo, FileMode.Open, FileAccess.Read);
byte[] data = null;
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
image.Bytes = new MemoryStream(data);
}
catch (Exception)
{
Console.WriteLine("Failed to load file " + photo);
return;
}
var rekognitionClient = new AmazonRekognitionClient();
var detectlabelsRequest = new DetectLabelsRequest
{
Image = image,
MaxLabels = 10,
MinConfidence = 77F,
};
try
{
DetectLabelsResponse detectLabelsResponse = await rekognitionClient.DetectLabelsAsync(detectlabelsRequest);
Console.WriteLine($"Detected labels for {photo}");
foreach (Label label in detectLabelsResponse.Labels)
{
Console.WriteLine($"{label.Name}: {label.Confidence}");
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
public static void Example()
{
String photo = "input.jpg";
Amazon.Rekognition.Model.Image image = new Amazon.Rekognition.Model.Image();
try
{
using (FileStream fs = new FileStream(photo, FileMode.Open, FileAccess.Read))
{
byte[] data = null;
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
image.Bytes = new MemoryStream(data);
}
}
catch (Exception)
{
Console.WriteLine("Failed to load file " + photo);
return;
}
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
DetectLabelsRequest detectlabelsRequest = new DetectLabelsRequest()
{
Image = image,
MaxLabels = 10,
MinConfidence = 77F
};
try
{
DetectLabelsResponse detectLabelsResponse = rekognitionClient.DetectLabels(detectlabelsRequest);
Console.WriteLine("Detected labels for " + photo);
foreach (Label label in detectLabelsResponse.Labels)
{
Console.WriteLine("{0}: {1}", label.Name, label.Confidence);
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
static void Main(string[] args)
{
//string filePath = "banner.png";
string filePath = "banner1.jpg";
Image image = new Image();
try
{
using (FileStream fs = new FileStream(filePath, FileMode.Open, FileAccess.Read))
{
byte[] data = null;
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
image.Bytes = new MemoryStream(data);
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
Console.WriteLine("Failed to load file " + filePath);
}
AmazonRekognitionClient client = new AmazonRekognitionClient(Amazon.RegionEndpoint.USEast1);
DetectTextRequest request = new DetectTextRequest
{
Image = image
};
try
{
DetectTextResponse response = client.DetectText(request);
foreach (var text in response.TextDetections)
{
Console.WriteLine(text.DetectedText);
}
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
Console.ReadLine();
}
public bool AddCollection(string collectionId)
{
try
{
AmazonRekognitionClient rekognitionClient = AmazonClient.GetInstance();
CreateCollectionRequest createCollectionRequest = new CreateCollectionRequest()
{
CollectionId = collectionId
};
CreateCollectionResponse createCollectionResponse = rekognitionClient.CreateCollection(createCollectionRequest);
return(true);
}
catch (Exception ex)
{
return(false);
}
}
public static void Example()
{
var rekognitionClient = new AmazonRekognitionClient(RegionEndpoint.APSouth1);
var collectionId = "BhavCollection";
Console.WriteLine("Creating collection: " + collectionId);
var createCollectionRequest = new CreateCollectionRequest()
{
CollectionId = collectionId
};
var createCollectionResponse =
rekognitionClient.CreateCollectionAsync(createCollectionRequest);
Console.WriteLine("CollectionArn : " + createCollectionResponse.Result.CollectionArn);
Console.WriteLine("Status code : " + createCollectionResponse.Result.StatusCode);
}
// 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);
}
static void Main(string[] args)
{
String bucket = ExtFunc.Read("\nAmazon S3 Bucket-Name with a picture:");
String photo = ExtFunc.Read("\nPicture Filename in Bucket:");
AmazonRekognitionClient rekognitionClient =
new AmazonRekognitionClient(Amazon.RegionEndpoint.USEast1);
var analyzed_image = new Image()
{
S3Object = new Amazon.Rekognition.Model.S3Object()
{
Name = photo,
Bucket = bucket
},
};
DetectLabelsRequest detectlabelsRequest = new DetectLabelsRequest()
{
Image = analyzed_image,
MaxLabels = 10,
MinConfidence = 75F
};
try
{
DetectLabelsResponse detectLabelsResponse = rekognitionClient.DetectLabels(detectlabelsRequest);
Console.WriteLine("Detected labels for " + photo);
foreach (Label label in detectLabelsResponse.Labels)
{
Console.WriteLine("{0}: {1}", label.Name, label.Confidence);
}
var tempUrl = GetS3Url(RegionEndpoint.USEast1, photo, bucket, 1);
System.Diagnostics.Process.Start(tempUrl);
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
}
private static async Task <object> GetVideoLabelsResult(string fileName, AmazonRekognitionClient rekognitionClient)
{
var startRequest = new StartLabelDetectionRequest
{
MinConfidence = 50,
Video = new Video
{
S3Object = new Amazon.Rekognition.Model.S3Object
{
Bucket = bucketName,
Name = fileName
}
},
JobTag = "DetectingLabels"
};
var startLabelDetectionResult = await rekognitionClient.StartLabelDetectionAsync(startRequest);
return(startLabelDetectionResult.JobId);
}
public void RekognitionDetectFaces()
{
#region to-detect-faces-in-an-image-1481841782793
var client = new AmazonRekognitionClient();
var response = client.DetectFaces(new DetectFacesRequest
{
Image = new Image {
S3Object = new S3Object {
Bucket = "mybucket",
Name = "myphoto"
}
}
});
List <FaceDetail> faceDetails = response.FaceDetails;
string orientationCorrection = response.OrientationCorrection;
#endregion
}
