static void IdentifyCelebrityFaces(string filename)
{
// Using USWest2, not the default region
AmazonRekognitionClient rekoClient = new AmazonRekognitionClient(Amazon.RegionEndpoint.USWest2);
// Request needs image bytes, so read and add to request
byte[] data = File.ReadAllBytes(filename);
RecognizeCelebritiesRequest rcr = new RecognizeCelebritiesRequest
{
Image = new Amazon.Rekognition.Model.Image
{
Bytes = new MemoryStream(data)
}
};
RecognizeCelebritiesResponse outcome = rekoClient.RecognizeCelebrities(rcr);
if (outcome.CelebrityFaces.Count > 0)
{
// Load a bitmap to modify with face bounding box rectangles
Bitmap facesHighlighted = new Bitmap(filename);
Pen pen = new Pen(Color.Black, 3);
Font drawFont = new Font("Arial", 12);
// Create a graphics context
using (var graphics = Graphics.FromImage(facesHighlighted))
{
foreach (var fd in outcome.CelebrityFaces)
{
// Get the bounding box
BoundingBox bb = fd.Face.BoundingBox;
Console.WriteLine($"Bounding box = ({bb.Left}, {bb.Top}, {bb.Height}, {bb.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);
graphics.DrawString(fd.Name,
font: drawFont,
brush: Brushes.White,
x: facesHighlighted.Width * bb.Left,
y: facesHighlighted.Height * bb.Top + facesHighlighted.Height * bb.Height);
}
}
// Save the image with highlights as PNG
string fileout = filename.Replace(Path.GetExtension(filename), "_celebrityfaces.png");
facesHighlighted.Save(fileout, System.Drawing.Imaging.ImageFormat.Png);
Console.WriteLine(">>> " + outcome.CelebrityFaces.Count + " celebrity face(s) highlighted in file " + fileout);
}
else
{
Console.WriteLine(">>> No celebrity faces found");
}
}
/// <summary>
/// Unmarshaller the response from the service to the response class.
/// </summary>
/// <param name="context"></param>
/// <returns></returns>
public override AmazonWebServiceResponse Unmarshall(JsonUnmarshallerContext context)
{
RecognizeCelebritiesResponse response = new RecognizeCelebritiesResponse();
context.Read();
int targetDepth = context.CurrentDepth;
while (context.ReadAtDepth(targetDepth))
{
if (context.TestExpression("CelebrityFaces", targetDepth))
{
var unmarshaller = new ListUnmarshaller <Celebrity, CelebrityUnmarshaller>(CelebrityUnmarshaller.Instance);
response.CelebrityFaces = unmarshaller.Unmarshall(context);
continue;
}
if (context.TestExpression("OrientationCorrection", targetDepth))
{
var unmarshaller = StringUnmarshaller.Instance;
response.OrientationCorrection = unmarshaller.Unmarshall(context);
continue;
}
if (context.TestExpression("UnrecognizedFaces", targetDepth))
{
var unmarshaller = new ListUnmarshaller <ComparedFace, ComparedFaceUnmarshaller>(ComparedFaceUnmarshaller.Instance);
response.UnrecognizedFaces = unmarshaller.Unmarshall(context);
continue;
}
}
return(response);
}
private static List <Face> MapResponse(ProcessedImage image, RecognizeCelebritiesResponse response)
{
var faces = new List <Face>();
foreach (var celebrityFace in response.CelebrityFaces)
{
var face = new Face
{
MatchConfidence = celebrityFace.MatchConfidence,
Name = celebrityFace.Name,
FaceInfo = new FaceInfo
{
Confidence = celebrityFace.Face.Confidence,
ImageQuality = new Models.ImageQuality
{
Brightness = celebrityFace.Face.Quality.Brightness,
Sharpness = celebrityFace.Face.Quality.Sharpness
},
Pose = new Models.Pose
{
Pitch = celebrityFace.Face.Pose.Pitch,
Roll = celebrityFace.Face.Pose.Roll,
Yaw = celebrityFace.Face.Pose.Yaw
},
BoundingBox = new Models.BoundingBox
{
Width = celebrityFace.Face.BoundingBox.Width * image.Width,
Height = celebrityFace.Face.BoundingBox.Height * image.Height,
Left = celebrityFace.Face.BoundingBox.Left * image.Width,
Top = celebrityFace.Face.BoundingBox.Top * image.Height
}
}
};
var landmarks = new List <Landmark>();
foreach (var faceLandmark in celebrityFace.Face.Landmarks)
{
Enum.TryParse(faceLandmark.Type.Value, true, out LandmarkType type);
var landmark = new Landmark
{
Type = type,
X = faceLandmark.X * image.Width,
Y = faceLandmark.Y * image.Height
};
landmarks.Add(landmark);
}
face.FaceInfo.Landmarks = landmarks;
faces.Add(face);
}
return(faces);
}
public async Task <IActionResult> Login(IFormFile file)
{
CelebrityModel celeb = new CelebrityModel();
Directory.Delete(_appEnvironment.WebRootPath + "/resources/", true);
Directory.CreateDirectory(_appEnvironment.WebRootPath + "/resources/");
if (null != file && file.Length > 0)
{
string speechFileName = "notjeff.mp3";
string speechText = "Nice try. You're not Jeff, I can't let you in.";
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
RecognizeCelebritiesRequest recognizeCelebritiesRequest = new RecognizeCelebritiesRequest();
Amazon.Rekognition.Model.Image img = new Amazon.Rekognition.Model.Image();
MemoryStream memStream = new MemoryStream();
file.CopyTo(memStream);
img.Bytes = memStream;
recognizeCelebritiesRequest.Image = img;
RecognizeCelebritiesResponse recognizeCelebritiesResponse = await rekognitionClient.RecognizeCelebritiesAsync(recognizeCelebritiesRequest);
if (null != recognizeCelebritiesResponse && recognizeCelebritiesResponse.CelebrityFaces.Count > 0)
{
celeb.CelebrityName = recognizeCelebritiesResponse.CelebrityFaces[0].Name;
celeb.Confidence = recognizeCelebritiesResponse.CelebrityFaces[0].MatchConfidence;
if (celeb.CelebrityName == "Jeff Bezos")
{
speechText = "Hello Boss, Welcome to the Deployment Bot. Please continue to start the deployment.";
celeb.IsJeff = true;
speechFileName = "jeff.mp3";
}
}
else
{
celeb.CelebrityName = "Sure, you're popular among your friends. But that doesn't make you a celebrity.";
celeb.Confidence = 0;
}
AmazonPollyClient pollyclient = new AmazonPollyClient();
Amazon.Polly.Model.SynthesizeSpeechResponse speechResponse =
await pollyclient.SynthesizeSpeechAsync(new Amazon.Polly.Model.SynthesizeSpeechRequest()
{
OutputFormat = OutputFormat.Mp3, Text = speechText, VoiceId = VoiceId.Joanna
});
var stream = new FileStream(_appEnvironment.WebRootPath + "/resources/" + speechFileName, FileMode.Create);
await speechResponse.AudioStream.CopyToAsync(stream);
stream.Close();
}
return(View("Login", celeb));
}
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>
/// 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;
}
}
public async Task <IActionResult> UploadAsync(IFormFile[] imgs)
{
IPainter painter = new RectangleMarker();
try
{
var file = Request.Form.Files[0];
var stream = ImageHelper.ConvertFormFileToMemoryStream(file);
if (stream != null)
{
var response = new RecognizeCelebritiesResponse();
response = await _recognizeCelibrities.Recognize(stream);
string markedImg = "";
if (response.CelebrityFaces.Count > 0)
{
System.Drawing.Image output = System.Drawing.Image.FromStream(stream);
foreach (var box in response.CelebrityFaces)
{
var boundingBox = box.Face.BoundingBox;
output = painter.DrawOnImage(output, file.FileName,
boundingBox.Height, boundingBox.Width,
boundingBox.Top, boundingBox.Left, Color.LightGreen);
}
markedImg = ImageHelper.ConvertImageToBase64(output);
}
return(Ok(new { response, markedImg }));
}
else
{
return(BadRequest());
}
}
catch (Exception ex)
{
return(StatusCode(500, "Internal server error"));
}
}
public string GetImageInfo(ImageData imageData, byte[] imgData = null)
{
try
{
var path = Path.Combine(
Directory.GetCurrentDirectory(), "wwwroot",
imageData.fileName);
imgData = Convert.FromBase64String(imageData.base64Data);
_imageData = new MemoryStream(imgData);
RecognizeCelebritiesRequest recognizeCelebrities = new RecognizeCelebritiesRequest()
{
Image = new Image()
{
Bytes = _imageData
}
};
RecognizeCelebritiesResponse celebrity = _rekognitionClient.RecognizeCelebritiesAsync(recognizeCelebrities).Result;
List <Celebrity> lstCelebrities = celebrity.CelebrityFaces;
StringBuilder sbCelebrities = new StringBuilder();
foreach (var item in lstCelebrities)
{
sbCelebrities.Append(item.Name);
sbCelebrities.Append(',');
}
string Celebrities = sbCelebrities.ToString().TrimEnd(',');
return(Celebrities);
}
catch (Exception ex)
{
Console.WriteLine(ex.ToString());
throw;
}
}
/// <summary>
/// Scans the contents of an image file looking for celebrities. If any
/// are found, a bounding box will be drawn around the face and the name
/// of the celebrity drawn under the box.
/// </summary>
/// <param name="client">The Rekognition client used to call
/// RecognizeCelebritiesAsync.</param>
/// <param name="filename">The name of the file that potentially
/// contins faces.</param>
public static async Task IdentifyCelebrityFaces(AmazonRekognitionClient client, string filename)
{
// Request needs image bytes, so read and add to request.
byte[] data = File.ReadAllBytes(filename);
RecognizeCelebritiesRequest request = new RecognizeCelebritiesRequest
{
Image = new Amazon.Rekognition.Model.Image
{
Bytes = new MemoryStream(data),
},
};
RecognizeCelebritiesResponse response = await client.RecognizeCelebritiesAsync(request);
if (response.CelebrityFaces.Count > 0)
{
// Load a bitmap to modify with face bounding box rectangles.
Bitmap facesHighlighted = new Bitmap(filename);
Pen pen = new Pen(Color.Black, 3);
Font drawFont = new Font("Arial", 12);
// Create a graphics context.
using (var graphics = Graphics.FromImage(facesHighlighted))
{
foreach (var fd in response.CelebrityFaces)
{
// Get the bounding box.
BoundingBox bb = fd.Face.BoundingBox;
Console.WriteLine($"Bounding box = ({bb.Left}, {bb.Top}, {bb.Height}, {bb.Width})");
// Draw the rectangle using the bounding box values.
// They are percentages so scale them to the picture.
graphics.DrawRectangle(
pen,
x: facesHighlighted.Width * bb.Left,
y: facesHighlighted.Height * bb.Top,
width: facesHighlighted.Width * bb.Width,
height: facesHighlighted.Height * bb.Height);
graphics.DrawString(
fd.Name,
font: drawFont,
brush: Brushes.White,
x: facesHighlighted.Width * bb.Left,
y: (facesHighlighted.Height * bb.Top) + (facesHighlighted.Height * bb.Height));
}
}
// Save the image with highlights as PNG.
string fileout = filename.Replace(Path.GetExtension(filename), "_celebrityfaces.png");
facesHighlighted.Save(fileout, System.Drawing.Imaging.ImageFormat.Png);
Console.WriteLine($">>> {response.CelebrityFaces.Count} celebrity face(s) highlighted in file {fileout}.");
Console.WriteLine("Found the following celebritie(s):");
foreach (var celeb in response.CelebrityFaces)
{
Console.WriteLine($"{celeb.Name}");
}
}
else
{
Console.WriteLine(">>> No celebrity faces found");
}
}
