public List <ClassifiedMatch> GetClassifiedMatchesFromImage(ClassifiedImage image, List <User> users)
{
var imageMatches = new List <ClassifiedMatch>();
foreach (var location in image.Locations)
{
var croppedMat = new Mat(image.Mat, location).Resize(new Size(100, 100), interpolation: InterpolationFlags.Cubic).CvtColor(ColorConversionCodes.BGR2GRAY);
Recognizer.Predict(croppedMat, out var userIndex, out var resultConfidence);
if (resultConfidence > ClassifierConfiguration.ConfidenceThreshold)
{
continue;
}
imageMatches.Add(new ClassifiedMatch
{
User = users[userIndex],
Distance = resultConfidence,
Location = GetLocationFromOpenCVRect(location)
});
}
SetIsCenteredOnClassifiedMatches(image, imageMatches);
return(imageMatches);
}
public async Task PutImage(string path)
{
string imageBase64 = ImageToBase64(new Bitmap(path));
SelectedImage = new ClassifiedImage()
{
Id = -1, Name = Path.GetFileName(path),
Class = -1, Confidence = -1, RetrieveCount = -1,
ImageBase64 = imageBase64
};
await Task.Run(() =>
{
HttpClient httpClient = new HttpClient();
NewImage newImage = new NewImage()
{
Name = Path.GetFileName(path),
ImageBase64 = imageBase64
};
string json = JsonConvert.SerializeObject(newImage);
var content = new StringContent(json);
content.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/json");
var putResult = httpClient.PutAsync(Urls.ClassifiedImages, content).Result;
json = putResult.Content.ReadAsStringAsync().Result;
Dispatcher.UIThread.InvokeAsync(() =>
{
SelectedImage = JsonConvert.DeserializeObject <ClassifiedImage>(json);
});
});
}
public async Task <IActionResult> PutClassifiedImage([FromRoute] int id, [FromBody] ClassifiedImage classifiedImage)
{
if (!ModelState.IsValid)
{
return(BadRequest(ModelState));
}
if (id != classifiedImage.Id)
{
return(BadRequest());
}
_context.Entry(classifiedImage).State = EntityState.Modified;
try
{
await _context.SaveChangesAsync();
}
catch (DbUpdateConcurrencyException)
{
if (!ClassifiedImageExists(id))
{
return(NotFound());
}
else
{
throw;
}
}
return(NoContent());
}
private void SetIsCenteredOnClassifiedMatches(ClassifiedImage image, List<ClassifiedMatch> classifiedMatches)
{
var centerPoint = new Point(image.Bitmap.Size.Width / 2, image.Bitmap.Height / 2);
foreach (var classifiedMatch in classifiedMatches)
{
if (!classifiedMatches.Any(c => c.IsCenter))
{
classifiedMatch.IsCenter = true;
continue;
}
var currentIsCenterClassifiedMatch = classifiedMatches.Single(c => c.IsCenter);
var currentIsCenterCenterDifference = currentIsCenterClassifiedMatch.Location.CenterDifference(centerPoint);
var classifiedMatchCenterDifference = classifiedMatch.Location.CenterDifference(centerPoint);
if (currentIsCenterCenterDifference >= classifiedMatchCenterDifference)
{
continue;
}
currentIsCenterClassifiedMatch.IsCenter = false;
classifiedMatch.IsCenter = true;
}
}
public async Task <IActionResult> Edit(int id, [Bind("Id,Date,Latitude,Longitude,GeoPolygon,Photo,PhotoName,FileType,Geolocalization,GeoJSON,FireTypeClassification,SmokeTypeClassification,FireScoreClassification,SmokeScoreClassification")] ClassifiedImage classifiedImage)
{
if (id != classifiedImage.Id)
{
return(NotFound());
}
if (ModelState.IsValid)
{
try
{
_context.Update(classifiedImage);
await _context.SaveChangesAsync();
}
catch (DbUpdateConcurrencyException)
{
if (!ClassifiedImageExists(classifiedImage.Id))
{
return(NotFound());
}
else
{
throw;
}
}
return(RedirectToAction(nameof(Index)));
}
return(View(classifiedImage));
}
public ClassifiedImage GetClassifiedImage(Bitmap bitmap)
{
var image = new ClassifiedImage(Classifier, ClassifierConfiguration);
image.Load(bitmap);
return image;
}
public List<ClassifiedMatch> GetClassifiedMatchesFromImage(ClassifiedImage image, List<User> users)
{
var classifiedMatches = new List<ClassifiedMatch>();
foreach (var location in image.Locations)
{
var croppedImage = image.Image.Copy(location).Convert<Gray, byte>().Resize(100, 100, Inter.Cubic);
var result = Recognizer.Predict(croppedImage);
Console.WriteLine($"{result.Distance} - {users[result.Label].Name}");
if (result.Distance > ClassifierConfiguration.DistanceThreshold)
{
continue;
}
classifiedMatches.Add(new ClassifiedMatch
{
User = users[result.Label],
Distance = result.Distance,
Location = location
});
}
SetIsCenteredOnClassifiedMatches(image, classifiedMatches);
return classifiedMatches;
}
public ClassifiedImage GetClassifiedImage(Bitmap bitmap)
{
var capturedImage = new ClassifiedImage(FaceRecognition);
capturedImage.Load(bitmap);
return(capturedImage);
}
public async Task <IActionResult> Create([Bind("Id,Date,Latitude,Longitude,GeoPolygon,Photo,PhotoName,FileType,Geolocalization,GeoJSON,FireTypeClassification,SmokeTypeClassification,FireScoreClassification,SmokeScoreClassification")] ClassifiedImage classifiedImage)
{
if (ModelState.IsValid)
{
_context.Add(classifiedImage);
await _context.SaveChangesAsync();
return(RedirectToAction(nameof(Index)));
}
return(View(classifiedImage));
}
public async Task <IActionResult> PostClassifiedImage([FromBody] ClassifiedImage classifiedImage)
{
if (!ModelState.IsValid)
{
return(BadRequest(ModelState));
}
_context.ClassifiedImages.Add(classifiedImage);
await _context.SaveChangesAsync();
return(CreatedAtAction("GetClassifiedImage", new { id = classifiedImage.Id }, classifiedImage));
}
public ClassifiedImage PutImage(NewImage newImage)
{
ClassifiedImage classifiedImage = db.FindImage(newImage);
if (classifiedImage != null)
{
return(classifiedImage);
}
classifiedImage = classifier.Classify(newImage);
db.PutImage(classifiedImage);
return(classifiedImage);
}
public async Task <IActionResult> Create(ClassifiedListing listing)
{
if (ModelState.IsValid)
{
var identityUser = await _userManager.GetUserAsync(HttpContext.User);
var loggedInUser = await _context.Owner.FindAsync(identityUser.OwnerId);
listing.LastModifiedBy = loggedInUser.FullName;
listing.LastModifiedDate = DateTime.Now;
listing.ListingDate = DateTime.Now;
listing.Owner = loggedInUser;
listing.OwnerId = loggedInUser.OwnerId;
_context.ClassifiedListing.Add(listing);
await _context.SaveChangesAsync();
//image uploading
string webRootPath = _hostingEnvironment.WebRootPath;
var files = HttpContext.Request.Form.Files;
var uploads = Path.Combine(webRootPath, @"img\ClassifiedsImages");
int i = 0;
foreach (var file in files)
{
i++;
var extension = Path.GetExtension(file.FileName);
using (var filestream = new FileStream(Path.Combine(uploads, listing.ClassifiedListingId + @"_" + i + extension), FileMode.Create))
{
file.CopyTo(filestream); // moves to server and renames
}
var image = new ClassifiedImage()
{
ClassifiedListingId = listing.ClassifiedListingId,
IsMainImage = (file == files.First()),
ImageExtension = extension,
ImageURL = @"\" + @"img\ClassifiedsImages" + @"\" + listing.ClassifiedListingId + @"_" + i + extension
};
_context.ClassifiedImage.Add(image);
}
await _context.SaveChangesAsync();
return(RedirectToAction(nameof(Index)));
}
ViewData["Category"] = new SelectList(_context.ClassifiedCategory.Where(u => u.Description != "Other"), "ClassifiedCategoryId", "Description", listing.ClassifiedCategoryId);
return(View(listing));
}
public ClassifiedImageModel AddClassifiedImage(InputClassifiedImageModel inputModel)
{
using (var scope = new TransactionScope())
{
var classifiedImage = new ClassifiedImage()
{
ClassifiedId = inputModel.ClassifiedId,
ImageExtension = inputModel.ImageExtension,
ImageGuid = inputModel.ImageGuid,
IsMainImage = inputModel.IsMainImage
};
_unitOfWork.ClassifiedImageRepository.Add(classifiedImage);
_unitOfWork.Save();
scope.Complete();
return(Mapper.Map <ClassifiedImage, ClassifiedImageModel>(classifiedImage));
}
}
public List <ClassifiedMatch> GetClassifiedMatchesFromImage(ClassifiedImage image, List <User> users)
{
var classifiedMatches = new List <ClassifiedMatch>();
foreach (var user in users)
{
foreach (var userImage in user.UserImages)
{
// you can leverage a saved encoding instead of loading the image then comparing.
var userClassifiedImage = new ClassifiedImage(FaceRecognition);
userClassifiedImage.Load(userImage.ImageFilePath);
for (var encodingIndex = 0; encodingIndex < image.Encodings.Count; encodingIndex++)
{
foreach (var userEncoding in userClassifiedImage.Encodings)
{
var faceDistance = FaceRecognition.FaceDistance(image.Encodings[encodingIndex], userEncoding);
if (!(faceDistance < FaceDistanceThreshold))
{
continue;
}
classifiedMatches.Add(new ClassifiedMatch
{
User = user,
FaceEncoding = image.Encodings[encodingIndex],
Distance = faceDistance,
Location = GetLocationFromFaceRecognitionLocation(image.Locations[encodingIndex])
});
}
}
}
}
SetIsCenteredOnClassifiedMatches(image, classifiedMatches);
return(classifiedMatches);
}
public async Task <IActionResult> PutClassifiedImage(int Id, DateTime Date, string Latitude, string Longitude, string GeoPolygon, string Photo, string PhotoName, string FileType, string Geolocalization, string GeoJSON, string FireTypeClassification, string SmokeTypeClassification, double FireScoreClassification, double SmokeScoreClassification)
{
ClassifiedImage classifiedImageobj = new ClassifiedImage(Id, Date, Latitude, Longitude, GeoPolygon, Photo, PhotoName, FileType, Geolocalization, GeoJSON, FireTypeClassification, SmokeTypeClassification, FireScoreClassification, SmokeScoreClassification);
_context.Entry(classifiedImageobj).State = Microsoft.EntityFrameworkCore.EntityState.Modified;
try
{
await _context.SaveChangesAsync();
}
catch (DbUpdateConcurrencyException)
{
if (!ClassifiedImageExists(classifiedImageobj.Id))
{
Console.WriteLine("L'immagine selezionata non esiste");
}
else
{
throw;
}
}
return(NoContent());
}
public ClassifiedImage PutImage(ClassifiedImage classifiedImage)
{
ClassifiedDbImage dbImage = new ClassifiedDbImage()
{
Name = classifiedImage.Name,
Class = classifiedImage.Class,
Confidence = classifiedImage.Confidence,
RetrieveCount = classifiedImage.RetrieveCount,
};
using (ImageDbContext dbContext = new ImageDbContext())
{
Blob blob = new Blob()
{
Bytes = Convert.FromBase64String(classifiedImage.ImageBase64)
};
dbContext.Add(blob);
dbImage.Image = blob;
dbContext.Add(dbImage);
dbContext.SaveChanges();
}
classifiedImage.Id = dbImage.Id;
return(classifiedImage);
}
public async Task <ActionResult> Edit(int?id, ClassifiedListing listing)
{
if (id != listing.ClassifiedListingId)
{
return(NotFound());
}
var identityUser = await _userManager.GetUserAsync(HttpContext.User);
var loggedInUser = await _context.Owner.FindAsync(identityUser.OwnerId);
if (ModelState.IsValid)
{
listing.LastModifiedBy = loggedInUser.FullName;
listing.LastModifiedDate = DateTime.Now;
listing.OwnerId = loggedInUser.OwnerId;
_context.Update(listing);
await _context.SaveChangesAsync();
var files = HttpContext.Request.Form.Files;
if (files.Count != 0)
{
string webRootPath = _hostingEnvironment.WebRootPath;
var uploads = Path.Combine(webRootPath, @"img\ClassifiedsImages");
var oldImages = await _context.ClassifiedImage.Where(x => x.ClassifiedListingId == listing.ClassifiedListingId).ToListAsync();
foreach (var oldImage in oldImages)
{
if (System.IO.File.Exists(Path.Combine(webRootPath, oldImage.ImageURL.Substring(1))))
{
System.IO.File.Delete(Path.Combine(webRootPath, oldImage.ImageURL.Substring(1)));
}
_context.ClassifiedImage.Remove(oldImage);
}
int i = 0;
foreach (var file in files)
{
i++;
var extension = Path.GetExtension(file.FileName);
using (var filestream = new FileStream(Path.Combine(uploads, listing.ClassifiedListingId + @"_" + i + extension), FileMode.Create))
{
file.CopyTo(filestream); // moves to server and renames
}
var image = new ClassifiedImage()
{
ClassifiedListingId = listing.ClassifiedListingId,
IsMainImage = (file == files.First()),
ImageExtension = extension,
ImageURL = @"\" + @"img\ClassifiedsImages" + @"\" + listing.ClassifiedListingId + @"_" + i + extension
};
_context.ClassifiedImage.Add(image);
}
await _context.SaveChangesAsync();
}
return(RedirectToAction(nameof(Index)));
}
ViewData["Category"] = new SelectList(_context.ClassifiedCategory, "ClassifiedCategoryId", "Description", listing.ClassifiedCategoryId);
return(View(listing));
}
public IActionResult ShowClassification(string localization, List <IFormFile> files)
{
ViewData["localization"] = localization; //localization contiene il posizione in termini di latitudine e longitudine
var photo_note = new List <String>(); //photo_note è una nota di testo contentente i nomi di tutte le immagini passate in input (serve per la classificazione)
string path1 = @"assets\inputs-predict\data\image_list.tsv"; //path1 percorso della nota di testo
string path2 = @"assets\inputs-predict\data"; //path2 percorso della cartella contenente le foto
//se la cartella relativa al 'path2' non esiste viene creata
if (System.IO.Directory.Exists(path2) == false)
{
Directory.CreateDirectory(path2); //viene creata la cartella che conterrà le immagini
}
//se la cartella relativa al 'path2' esiste ed è piena viene svuotata per far spazio alle nuove foto in input
System.IO.DirectoryInfo di = new DirectoryInfo(path2);
foreach (FileInfo file in di.GetFiles())
{
file.Delete();
}
foreach (DirectoryInfo dir in di.GetDirectories())
{
dir.Delete(true);
}
//files_from_video è la lista che conterrà i nome dei frame video (nel caso in cui in input ci fosse un video)
List <String> files_from_video = new List <String>();
//cotruisco una lista di oggetti da salvare nel database successivamente
List <ClassifiedImage> classifiedImages = new List <ClassifiedImage>();
int i = 0; //mi serve per la gestione della lista 'score'
int n = 0; //mi serve per la gestione della lista 'classifiedImages'
foreach (var image in files) //iterazione di tutte le immagini in input
{
if (image != null)
{
/*
* GESTIONE CARICAMENTO IMMAGINI
*/
//il seguente if serve per controllare se il file caricato è un immagine o no
if (Path.GetExtension(image.FileName).ToLower() == ".jpg" ||
Path.GetExtension(image.FileName).ToLower() == ".png" ||
Path.GetExtension(image.FileName).ToLower() == ".gif" ||
Path.GetExtension(image.FileName).ToLower() == ".jpeg")
{
var fileName = Path.Combine(he.WebRootPath, Path.GetFileName(image.FileName));
image.CopyTo(new FileStream(fileName, FileMode.Create));
photo_note.Add(image.FileName); //il nome dell'immagine viene aggiunto alla nota di testo
string FileToCopy = null;
string NewCopy = null;
FileToCopy = fileName;
NewCopy = Path.Combine(path2, image.FileName); //viene caricata l'immagine nel 'path2'
//se l'immagine gia esiste viene sovrascritta
if (System.IO.File.Exists(FileToCopy) == true)
{
if (System.IO.File.Exists(NewCopy))
{
System.IO.File.Delete(NewCopy);
}
System.IO.File.Copy(FileToCopy, NewCopy);
}
//visto che in ingresso ci sono immagini viene settata a null la lista files_from_video
files_from_video = null;
Image p = Image.FromFile("assets/inputs-predict/data/" + image.FileName);
//converto l'immagine in una stringa base64
MemoryStream m = new MemoryStream();
p.Save(m, p.RawFormat);
byte[] imageBytes = m.ToArray();
string base64String = Convert.ToBase64String(imageBytes);
string img_db = base64String;
string gpsLatitudeRef = " ";
double latitude = 0;
string gpsLongitudeRef = " ";
double longitude = 0;
//la seguente porzione di codice serve per estrapolare i metadati dalle immagine
try{
gpsLatitudeRef = BitConverter.ToChar(p.GetPropertyItem(1).Value, 0).ToString();
latitude = DecodeRational64u(p.GetPropertyItem(2));
gpsLongitudeRef = BitConverter.ToChar(p.GetPropertyItem(3).Value, 0).ToString();
longitude = DecodeRational64u(p.GetPropertyItem(4));
}
catch (System.ArgumentException e)
{
Console.WriteLine("{0} Exception caught.", e);
}
string geolocalization = (latitude.ToString().Replace(",", ".") + "," + longitude.ToString().Replace(",", "."));
string filetype = Path.GetExtension(image.FileName);
string photoname = image.FileName;
//creo un nuovo oggetto da aggiungere al database
ClassifiedImage classifiedImage = new ClassifiedImage
{
PhotoName = photoname,
Date = DateTime.Now,
Photo = img_db,
Latitude = latitude,
Longitude = longitude,
FileType = filetype,
Geolocalization = geolocalization,
FireScoreClassification = 200,
SmokeScoreClassification = 233
};
classifiedImages.Add(classifiedImage);
}
/*
* GESTIONE CARICAMENTO IMMAGINI DA VIDEO
*/
/*
* il servizio chiamato estrae i frame dal video caricato e successivamente
* carica all'interno della cartella (che poi si trasformerà in un db) sia questi ultimi che
* il file di testo.
*
*/
if (Path.GetExtension(image.FileName).ToLower() == ".avi")
{
var fileName = Path.Combine(he.WebRootPath, Path.GetFileName(image.FileName));
FileStream filestream = new FileStream(fileName, FileMode.Create);
image.CopyTo(filestream);
filestream.Close();
string FileToCopy = fileName;
string NewCopy = null;
NewCopy = Path.Combine(path2, image.FileName); //viene caricato il video
//se il video gia esiste viene sovrascritta
if (System.IO.File.Exists(FileToCopy) == true)
{
if (System.IO.File.Exists(NewCopy))
{
System.IO.File.Delete(NewCopy);
}
System.IO.File.Copy(FileToCopy, NewCopy);
}
String uriString = "http://localhost:5020";
// Create a new WebClient instance.
WebClient myWebClient = new WebClient();
string fileNameHttpUpload = NewCopy;
// Caricamento del file sull'URI.
// Il metodo 'UploadFile(uriString,fileName)' usa implicitamente il metodo POST HTTP.
byte[] responseArray = myWebClient.UploadFile(uriString, fileNameHttpUpload);
// Decodificazione e visualizzazione della risposta.
Console.WriteLine("\nResponse Received.The contents of the file uploaded are:\n{0}",
System.Text.Encoding.ASCII.GetString(responseArray));
// estrapolazione dei nomi dei frame contenuti all'interno del file di testo per salvarli nell'arraylist photo_note
// lettura file usando StreamReader.
using (StreamReader file = new StreamReader(path1))
{
int counter = 0;
string ln;
while ((ln = file.ReadLine()) != null)
{
photo_note.Add(ln);
files_from_video.Add("/" + ln);
counter++;
}
file.Close();
}
foreach (var frame in files_from_video)
{
Image frame_video = Image.FromFile("assets/inputs-predict/data" + frame);
// conversione dell'immagine in una stringa base64
MemoryStream m = new MemoryStream();
frame_video.Save(m, frame_video.RawFormat);
byte[] imageBytes = m.ToArray();
string base64Stringvideo = Convert.ToBase64String(imageBytes);
string frame_db = base64Stringvideo;
string gpsLatitudeRef = " ";
double latitude = 0;
string gpsLongitudeRef = " ";
double longitude = 0;
try
{
gpsLatitudeRef = BitConverter.ToChar(frame_video.GetPropertyItem(1).Value, 0).ToString();
latitude = DecodeRational64u(frame_video.GetPropertyItem(2));
gpsLongitudeRef = BitConverter.ToChar(frame_video.GetPropertyItem(3).Value, 0).ToString();
longitude = DecodeRational64u(frame_video.GetPropertyItem(4));
}
catch (System.ArgumentException e)
{
Console.WriteLine("{0} Exception caught.", e);
}
string geolocalization = (latitude.ToString().Replace(",", ".") + "," + longitude.ToString().Replace(",", "."));
string filetype = Path.GetExtension(frame);
string photoname = frame;
//creazione di un nuovo oggetto da aggiungere al database
ClassifiedImage classifiedImage = new ClassifiedImage
{
PhotoName = photoname,
Date = DateTime.Now,
Photo = frame_db,
Latitude = latitude,
Longitude = longitude,
FileType = filetype,
Geolocalization = geolocalization,
FireScoreClassification = 200,
SmokeScoreClassification = 233
};
classifiedImages.Add(classifiedImage);
}
}
}
}
// se il file di testo gia esiste viene cancellato e poi creato
if (System.IO.File.Exists(path1) == true)
{
System.IO.File.Delete(path1);
}
using (StreamWriter sw = System.IO.File.CreateText(path1))
{
foreach (var photo in photo_note) //iterazione della nota per scrivere i nomi all'interno di essa
{
sw.WriteLine(photo);
}
}
// creazione di una lista di stringhe che contiene i nomi di ogni immagine classicata
var listfilenames = new List <String>();
foreach (var o in files)
{
listfilenames.Add("/" + Path.GetFileName(o.FileName));
}
var score_fire = new List <String>(); // creazione di una lista di stringhe che conterrà i valori di classificazione con il modello del fuoco
var score_smoke = new List <String>(); // creazione di una lista di stringhe che conterrà i valori di classificazione con il modello del fumo
var score = new List <String>(); // creazione di una lista di stringhe che conterrà i valori di classificazione di entrambi i modelli
// le liste vengono riempite chiamando un metodo proveniente dal progetto di tipo ML.NET
score_fire = TransferLearningTF.Program.ClassyAPIfire();
score_smoke = TransferLearningTF.Program.ClassyAPIsmoke();
// riempimento della lista score iterando sulle liste dei due modelli
i = 0;
foreach (var sco in score_fire)
{
score.Add(sco);
score.Add(score_smoke[i]);
i++;
}
n = 0;
foreach (var cimg in classifiedImages)
{
cimg.FireTypeClassification = score[n];
cimg.SmokeTypeClassification = score[n + 1];
cimg.FireScoreClassification = Convert.ToDouble(score[n + 2].ToString());
cimg.SmokeScoreClassification = Convert.ToDouble(score[n + 3].ToString());
n = n + 4;
}
if (files_from_video != null)
{
ViewData["filenames"] = files_from_video;
}
else
{
ViewData["filenames"] = listfilenames;
}
int countrow = CountRowInDB(); //qui conto il numero degli elementi all'interno del DB per calcolare l'Id
Console.WriteLine("AAAAAAAAA: " + countrow);
// questo serve per settare l'Id all'interno della lista classifiedImages da passare a ShowClassification
int countrow_noid = 0;
if (!countrow.Equals(1))
{
// se non è la prima immagine da inserire nel database allora bisogna prendere l'ultimo numero messo come id
countrow_noid = GetLastIndexUpdate(countrow - 2);
}
PostClassifiedImages(classifiedImages, countrow);
ViewData["classifiedImages"] = classifiedImages;
ViewData["score"] = score; // lista classificazione di ogni immagine
return(View());
}
public async Task <IActionResult> AddServicePOST(string description)
{
if (String.IsNullOrEmpty(description))
{
ModelState.AddModelError("Description", "Please enter a description");
}
var files = HttpContext.Request.Form.Files;
if (files == null || files.Count == 0)
{
ModelState.AddModelError("Files", "Please upload one file");
}
if (ModelState.IsValid)
{
var identityUser = await _userManager.GetUserAsync(HttpContext.User);
var loggedInUser = await _context.Owner.FindAsync(identityUser.OwnerId);
var service = new ClassifiedListing
{
ClassifiedCategoryId = 3, // Manually set to "Other"
ItemName = "Service",
Description = description,
Price = 0,
LastModifiedBy = loggedInUser.FullName,
LastModifiedDate = DateTime.Now,
ListingDate = DateTime.Now,
Owner = loggedInUser,
OwnerId = loggedInUser.OwnerId
};
_context.ClassifiedListing.Add(service);
await _context.SaveChangesAsync();
//image uploading
string webRootPath = _hostingEnvironment.WebRootPath;
var uploads = Path.Combine(webRootPath, @"img\ClassifiedsImages");
var file = files[0];
var extension = Path.GetExtension(file.FileName);
using (var filestream = new FileStream(Path.Combine(uploads, service.ClassifiedListingId + extension), FileMode.Create))
{
file.CopyTo(filestream); // moves to server and renames
}
var image = new ClassifiedImage()
{
ClassifiedListingId = service.ClassifiedListingId,
IsMainImage = (file == files.First()),
ImageExtension = extension,
ImageURL = @"\" + @"img\ClassifiedsImages" + @"\" + service.ClassifiedListingId + extension
};
_context.Add(image);
await _context.SaveChangesAsync();
return(RedirectToAction(nameof(Index)));
}
return(View());
}
public Bitmap GetFaceBitmapFromClassifiedImage(ClassifiedImage image)
{
return(new Mat(image.Mat, image.Locations.First()).Resize(new Size(100, 100), interpolation: InterpolationFlags.Cubic).ToBitmap());
}
public Bitmap GetFaceBitmapFromClassifiedImage(ClassifiedImage image)
{
return image.Image.Copy(image.Locations.First()).Resize(100, 100, Inter.Cubic).ToBitmap();
}