public async static Task <FaceDetail> GetFaceDetailFromStream(IAmazonRekognition rekognitionClient, MemoryStream stream)
{
FaceDetail result = null;
DetectFacesRequest detectFacesRequest = new DetectFacesRequest()
{
Image = new Image {
Bytes = stream
},
Attributes = new List <String>()
{
"ALL"
}
};
try
{
Task <DetectFacesResponse> detectTask = rekognitionClient.DetectFacesAsync(detectFacesRequest);
DetectFacesResponse detectFacesResponse = await detectTask;
PrintFaceDetails(detectFacesResponse.FaceDetails);
if (detectFacesResponse.FaceDetails.Count > 0)
{
result = detectFacesResponse.FaceDetails[0]; // take the 1st face only
}
}
catch (AmazonRekognitionException rekognitionException)
{
Console.WriteLine(rekognitionException.Message, rekognitionException.InnerException);
}
return(result);
}
public async static Task <FaceDetail> GetObjectDetailFromStream(IAmazonRekognition rekognitionClient, MemoryStream stream)
{
FaceDetail result = null;
DetectLabelsRequest detectLabelsRequest = new DetectLabelsRequest()
{
Image = new Image {
Bytes = stream
},
MaxLabels = 10,
MinConfidence = 75F
};
try
{
Task <DetectLabelsResponse> detectTask = rekognitionClient.DetectLabelsAsync(detectLabelsRequest);
DetectLabelsResponse detectLabelsResponse = await detectTask;
PrintObjectDetails(detectLabelsResponse.Labels);
// if (detectFacesResponse.FaceDetails.Count > 0)
// result = detectFacesResponse.FaceDetails[0]; // take the 1st face only
}
catch (AmazonRekognitionException rekognitionException)
{
Console.WriteLine(rekognitionException.Message, rekognitionException.InnerException);
}
return(result);
}
public async static void GetFaceDetailFromS3(IAmazonRekognition rekognitionClient, string bucketName, string keyName)
{
FaceDetail result = null;
DetectFacesRequest detectFacesRequest = new DetectFacesRequest()
{
Image = new Image {
S3Object = new S3Object {
Bucket = bucketName,
Name = keyName
}
},
Attributes = new List <String>()
{
"ALL"
}
};
try
{
Task <DetectFacesResponse> detectTask = rekognitionClient.DetectFacesAsync(detectFacesRequest);
DetectFacesResponse detectFacesResponse = await detectTask;
PrintFaceDetails(detectFacesResponse.FaceDetails);
if (detectFacesResponse.FaceDetails.Count > 0)
{
result = detectFacesResponse.FaceDetails[0]; // take the 1st face only
}
}
catch (AmazonRekognitionException rekognitionException)
{
Console.WriteLine(rekognitionException.Message, rekognitionException.InnerException);
}
}
private List <RecognitionItem> GetRecognitionItems(FaceDetail face)
{
var result = new List <RecognitionItem>()
{
new RecognitionItem()
{
Name = "Beard",
Value = face.Beard.Value.ToString(),
Confidence = face.Beard.Confidence
},
new RecognitionItem()
{
Name = "Eyeglasses",
Value = face.Eyeglasses.Value.ToString(),
Confidence = face.Eyeglasses.Confidence
},
new RecognitionItem()
{
Name = "EyesOpen",
Value = face.EyesOpen.Value.ToString(),
Confidence = face.EyesOpen.Confidence
},
new RecognitionItem()
{
Name = "MouthOpen",
Value = face.MouthOpen.Value.ToString(),
Confidence = face.MouthOpen.Confidence
},
new RecognitionItem()
{
Name = "Mustache",
Value = face.Mustache.Value.ToString(),
Confidence = face.Mustache.Confidence
},
new RecognitionItem()
{
Name = "Smile",
Value = face.Smile.Value.ToString(),
Confidence = face.Smile.Confidence
},
new RecognitionItem()
{
Name = "Sunglasses",
Value = face.Sunglasses.Value.ToString(),
Confidence = face.Sunglasses.Confidence
}
};
return(result);
}
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);
DetectFacesRequest detectFaces = new DetectFacesRequest()
{
Image = new Image()
{
Bytes = _imageData
}
};
DetectFacesResponse facesResponse = _rekognitionClient.DetectFacesAsync(detectFaces).Result;
List <FaceDetail> lstCelebrities = facesResponse.FaceDetails;
FaceDetail faceDetail = new FaceDetail();
StringBuilder sbCelebrities = new StringBuilder();
//foreach (var item in lstCelebrities)
//{
// switch (switch_on)
// {
// default:
// }
//}
string Celebrities = sbCelebrities.ToString().TrimEnd(',');
return(Celebrities);
}
catch (Exception ex)
{
Console.WriteLine(ex.ToString());
throw;
}
}
public List <Emotion> EmotionDetect(string _image)
{
{
String photo = _image;
String bucket = "ngankhanh98";
List <Emotion> response;
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
DetectFacesRequest detectFacesRequest = new DetectFacesRequest()
{
Image = new Amazon.Rekognition.Model.Image()
{
S3Object = new S3Object()
{
Name = photo,
Bucket = bucket
},
},
Attributes = new List <String>()
{
"ALL"
}
};
try
{
DetectFacesResponse detectFacesResponse = rekognitionClient.DetectFaces(detectFacesRequest);
bool hasAll = detectFacesRequest.Attributes.Contains("ALL");
FaceDetail face = detectFacesResponse.FaceDetails[0];
return(face.Emotions);
}
catch (Exception e)
{
Console.WriteLine(e.Message);
return(null);
}
}
}
private async Task <bool> ProcessLabels(ILambdaContext context, string jobId)
{
GetFaceDetectionResponse response = null;
do
{
GetFaceDetectionRequest request = new GetFaceDetectionRequest()
{
JobId = jobId,
MaxResults = MaxResults,
NextToken = response?.NextToken,
};
response = await this.rekClient.GetFaceDetectionAsync(request).ConfigureAwait(false);
if (response.Faces.Count != 1 || !(response.Faces[0].Face.Confidence > 60))
{
return(false);
}
FaceDetail face = response.Faces[0].Face;
if (face.Emotions.Any(x => this.invalidEmotions.Any(y => y == x.Type)))
{
return(false);
}
if (!face.EyesOpen.Value || face.EyesOpen.Confidence < 60)
{
return(false);
}
if (face.Quality.Brightness < 50.00f || face.Quality.Sharpness < 50.00f)
{
return(false);
}
return(true);
} while (response?.NextToken != null);
}
public async Task <IActionResult> Post([FromBody] GameStagePostImageDTO dto)
{
Console.WriteLine("PostImage entered.");
string bucketName = "reinvent-gottalent";
// Retrieving image data
// ex: game/10/Happiness.jpg
string keyName = string.Format("game/{0}/{1}.jpg", dto.gameId, dto.actionType);
string croppedKeyName = string.Format("game/{0}/{1}_cropped.jpg", dto.gameId, dto.actionType);
byte[] imageByteArray = Convert.FromBase64String(dto.base64Image);
if (imageByteArray.Length == 0)
{
return(BadRequest("Image length is 0."));
}
StageLog newStageLog = null;
using (MemoryStream ms = new MemoryStream(imageByteArray))
{
// call Rekonition API
FaceDetail faceDetail = await RekognitionUtil.GetFaceDetailFromStream(this.RekognitionClient, ms);
// Crop image to get face only
System.Drawing.Image originalImage = System.Drawing.Image.FromStream(ms);
System.Drawing.Image croppedImage = GetCroppedFaceImage(originalImage, faceDetail.BoundingBox);
MemoryStream croppedms = new MemoryStream();
croppedImage.Save(croppedms, ImageFormat.Jpeg);
// Upload image to S3 bucket
//await Task.Run(() => S3Util.UploadToS3(this.S3Client, bucketName, keyName, ms));
await Task.Run(() => S3Util.UploadToS3(this.S3Client, bucketName, keyName, croppedms));
// Get a specific emotion score
double emotionScore = 0.0f;
if (dto.actionType != "Profile")
{
emotionScore = RekognitionUtil.GetEmotionScore(faceDetail.Emotions, dto.actionType);
}
int evaluatedAge = (faceDetail.AgeRange.High + faceDetail.AgeRange.Low) / 2;
string evaluatedGender = faceDetail.Gender.Value;
// Database update
newStageLog = new StageLog {
game_id = dto.gameId,
action_type = dto.actionType,
score = emotionScore,
file_loc = keyName,
age = evaluatedAge,
gender = evaluatedGender,
log_date = DateTime.Now
};
var value = _context.StageLog.Add(newStageLog);
await _context.SaveChangesAsync();
}
// Send response
string signedURL = S3Util.GetPresignedURL(this.S3Client, bucketName, keyName);
newStageLog.file_loc = signedURL;
return(Ok(newStageLog));
}
