public FileContentResult UploadCustomerImage([FromBody] UploadCustomerImageModel model)
{
//Depending on if you want the byte array or a memory stream, you can use the below.
//THIS IS NO LONGER NEEDED AS OUR MODEL NOW HAS A BYTE ARRAY
//var imageDataByteArray = Convert.FromBase64String(model.ImageData);
//When creating a stream, you need to reset the position, without it you will see that you always write files with a 0 byte length.
var imageDataStream = new MemoryStream(model.ImageData);
imageDataStream.Position = 0;
using (FileStream fstream = new FileStream(@"E:/personal/WebApi.Test/WebApi.Test/" +
"salam.png", FileMode.Create))
{
//memStream.WriteTo(fstream);
imageDataStream.WriteTo(fstream);
}
//Go and do something with the actual data.
//_customerImageService.Upload([...])
//For the purpose of the demo, we return a file so we can ensure it was uploaded correctly.
//But otherwise you can just return a 204 etc.
return(File(model.ImageData, "image/png"));
}
public async Task <string> FaceDetection([FromBody] UploadCustomerImageModel model)
{
IEnumerable <FaceRectangle> faces = (await faceDetector.DetectAsync(model.ImageData))
.Select(face => new FaceRectangle {
Height = face["height"],
Left = face["left"],
Top = face["top"],
Width = face["width"],
X1 = face["x1"],
X2 = face["x2"],
Y1 = face["y1"],
Y2 = face["y2"]
});
return(JsonConvert.SerializeObject(faces.Select(face => new FaceModel {
FaceRectangle = face, FaceAttributes = new FaceAttributes()
})));
}
public async Task <string> MaskDetection([FromBody] UploadCustomerImageModel model)
{
IEnumerable <FaceRectangle> faces = (await faceDetector.DetectAsync(model.ImageData))
.Select(face => new FaceRectangle
{
Height = face["height"],
Left = face["left"],
Top = face["top"],
Width = face["width"],
X1 = face["x1"],
X2 = face["x2"],
Y1 = face["y1"],
Y2 = face["y2"]
});
IEnumerable <FaceModel> faceModels = Utils.FaceAnalysis(faceMaskDetector, model.ImageData, faces, true);
return(JsonConvert.SerializeObject(faceModels));
}
