public ActionResult AddOrEdit(imageModel img)
{
if (img.ImageUpload != null)
{
string fileName = Path.GetFileNameWithoutExtension(img.ImageUpload.FileName);
string extension = Path.GetExtension(img.ImageUpload.FileName);
fileName = img.Name + extension;
img.ImagePath = "/File/image/" + fileName;
img.ImageUpload.SaveAs(Path.Combine(Server.MapPath("/File/image/"), fileName));
}
using (UploadImageContext db = new UploadImageContext())
{
if (img.Id == 0)
{
image obj = new image();
obj.ImagePath = img.ImagePath;
obj.Name = img.Name;
db.images.Add(obj);
db.SaveChanges();
return(Json(new { success = true, message = "Saved successfully!!!" }, JsonRequestBehavior.AllowGet));
}
else
{
db.Entry(img).State = EntityState.Modified;
db.SaveChanges();
return(Json(new { success = true, message = "Updated successfully!!!" }, JsonRequestBehavior.AllowGet));
}
}
}
// GET: Image/Details/5
public ActionResult Details(int id)
{
if (id == 0)
{
return(new HttpStatusCodeResult(HttpStatusCode.BadRequest));
}
var image = gs.GetByIdImage(id);
imageModel um = new imageModel
{
id = image.id,
image1 = image.image1,
name = image.name,
aime = image.aime,
danger = image.danger,
user = image.user,
visib = image.visib,
dateinvisibl = image.dateinvisibl
};
if (image == null)
{
return(HttpNotFound());
}
return(View(um));
}
/// <summary>
/// Predict emotion on the basis of wrinkles and distances
/// </summary>
/// <param name="ImageMats">Input image on which emotion need to detect</param>
/// <returns>Business model containing images of different steps and output result</returns>
public EmotionBusinessModel DetectEmotionsDistanceAndWrinkledBased(Mat[] ImageMats, List <Rectangle> facess)
{
EmotionBusinessModel output = new EmotionBusinessModel();
EmotionBusinessModel.outputmsgs = new List <string>();
try
{
using (Logger logger = new Logger())
{
KeyValuePair <string, Color> keyPair = new KeyValuePair <string, Color>("smile", Color.Yellow);
keyPairs.Add(keyPair);
keyPair = new KeyValuePair <string, Color>("sad", Color.Blue);
keyPairs.Add(keyPair);
keyPair = new KeyValuePair <string, Color>("surprise", Color.SlateGray);
keyPairs.Add(keyPair);
keyPair = new KeyValuePair <string, Color>("anger", Color.Red);
keyPairs.Add(keyPair);
keyPair = new KeyValuePair <string, Color>("disgust", Color.Purple);
keyPairs.Add(keyPair);
keyPair = new KeyValuePair <string, Color>("fear", Color.Black);
keyPairs.Add(keyPair);
keyPair = new KeyValuePair <string, Color>("neutral", Color.Green);
keyPairs.Add(keyPair);
Mat ImageMat = ImageMats[0];
logger.LogIntoFile(Log.logType.INFO, (string)ConstantsLoader.getInstance().getValue(EnumConstant.emotionDetectionMessage));
List <Rectangle> faces = new List <Rectangle>();
faces = facess;
//faces = FDIPMAin.DetectFace(ImageMat);
output.faceRect = new List <Rectangle>();
foreach (Rectangle face in faces)
{
List <Rectangle> fcs = new List <Rectangle>();
fcs.Add(face);
output.outputResult = EDRIPDistanceAndWrinklesBasedFeatures.getInstance().FindEmotionDistanceAndWrinkleBased(ImageMat, fcs, 0);
EmotionBusinessModel.outputmsgs.Add(output.outputResult);
output.faceRect.Add(face);
}
imageModel img = new imageModel();
if (faces.Count > 0)
{
img.image = CvmlUtility.getInstance().annotate(ImageMat, faces[0], output.outputResult, Color.Blue);
}
//img.image=drawRect(ImageMat.ToImage<Bgr, byte>(), faces[0], output.outputResult);
img.label = "Final emotion detected image with rectangle on face";
output.images.Add(img);
output.outputMessage = "Emotion detected successfully in given image using wrinkled and distance based approach";
output.success = true;
}
}
catch (Exception e)
{
string text = ExceptionHandle.GetExceptionMessage(e);
output.success = false;
output.outputResult = "neutral";
output.e = e;
}
return(output);
}
// GET: Image/Delete/5
public ActionResult Delete(int id)
{
var image = gs.GetByIdImage(id);
imageModel um = new imageModel
{
id = image.id,
name = image.name,
};
return(View(um));
}
