public void UploadUserPhoto(Stream stream, Rect rect)
{
if (this.IsSaving)
{
return;
}
this.IsSaving = true;
this.SetInProgress(true, "");
ImagePreprocessor.PreprocessImage(stream, VKConstants.ResizedImageSize, true, (Action <ImagePreprocessResult>)(pres =>
{
Stream stream1 = pres.Stream;
byte[] numArray = (byte[])new byte[stream1.Length];
stream1.Read(numArray, 0, (int)stream1.Length);
stream1.Close();
UsersService.Instance.SaveProfilePhoto(ImagePreprocessor.GetThumbnailRect((double)pres.Width, (double)pres.Height, rect), numArray, (Action <BackendResult <ProfilePhoto, ResultCode> >)(res =>
{
this.IsSaving = false;
this.SetInProgress(false, "");
if (res.ResultCode == ResultCode.Succeeded)
{
BaseDataManager.Instance.NeedRefreshBaseData = true;
BaseDataManager.Instance.RefreshBaseDataIfNeeded();
}
else
{
ExtendedMessageBox.ShowSafe(CommonResources.Error);
}
}));
}));
}
public void UpdatePhoto(Stream photoStream, Rect crop)
{
this.IsPhotoChanging = true;
this.SetInProgress(true, "");
ImagePreprocessor.PreprocessImage(photoStream, VKConstants.ResizedImageSize, true, (Action<ImagePreprocessResult>)(resized =>
{
Stream stream = resized.Stream;
byte[] photoData = ImagePreprocessor.ReadFully(stream);
stream.Close();
BackendServices.MessagesService.UpdateChatPhoto(this.ChatId, photoData, ImagePreprocessor.GetThumbnailRect((double)resized.Width, (double)resized.Height, crop), (Action<BackendResult<ChatInfoWithMessageId, ResultCode>>)(result => Execute.ExecuteOnUIThread((Action)(() =>
{
if (result.ResultCode == ResultCode.Succeeded)
{
this._chatInformation.chat.photo_200 = result.ResultData.chat.photo_200;
this.NotifyPropertyChanged<string>((Expression<Func<string>>)(() => this.Photo));
this.NotifyPropertyChanged<Visibility>((Expression<Func<Visibility>>)(() => this.PhotoPlaceholderVisibility));
this.NotifyPropertyChanged<bool>((Expression<Func<bool>>)(() => this.IsPhotoMenuEnabled));
}
else
GenericInfoUC.ShowBasedOnResult(result.ResultCode, "", (VKRequestsDispatcher.Error)null);
this.SetInProgress(false, "");
this.IsPhotoChanging = false;
}))));
}));
}
public void Dispose()
{
PixelDeltaAlgorithm.Dispose();
ImagePreprocessor.Dispose();
GC.SuppressFinalize(this);
}
private void mnistDesktopButton_Click(object sender, EventArgs e)
{
MNistEnvironment env = new MNistEnvironment(this);
env.Path = Application.StartupPath + "\\..\\..\\..\\..\\..\\Mnist\\";
env.ItemsToLoad = 5;
_agents.Add(env);
ImagePreprocessor preprocessor = new ImagePreprocessor(this);
_agents.Add(preprocessor);
HTMBuilder htmBuilder = new HTMBuilder(this);
_agents.Add(htmBuilder);
preprocessor.InputAgent = env; // link the preprocessor to the environment
htmBuilder.InputAgent = preprocessor; // link the htm builder to the preprocessor
// Set the layout
preprocessor.MdiParent = this;
preprocessor.Location = new Point(0, 0);
preprocessor.Show();
htmBuilder.MdiParent = this;
htmBuilder.Location = new Point(0, preprocessor.Height);
htmBuilder.Show();
env.MdiParent = this;
env.Location = new Point(preprocessor.Width, 0);
env.Show();
//
this.Log("Image desktop created.");
initializeButton.Enabled = true;
imageDesktopButton.Enabled = false;
mnistDesktopButton.Enabled = false;
dataDesktopButton.Enabled = false;
}
private void OnClassifyImage(object sender, EventArgs e)
{
try
{
_loggingService.Log("Classify drawing has started");
var imagePreprocessor = new ImagePreprocessor();
double[] pixels = imagePreprocessor.Preprocess(_uploadImageView.Image);
IPredictionModel predictionModel = Global.PredictionModel;
double[] prediction = predictionModel.Predict(pixels);
_uploadImageView.ProcessPrediction(prediction);
_loggingService.Log("Classify drawing has completed");
}
catch (NullReferenceException exception)
{
_loggingService.Log(exception);
_messageService.ShowMessage("No image was uploaded. Please upload an image and try again.", "Upload error", icon: MessageBoxIcon.Information);
}
catch (Exception exception)
{
_loggingService.Log(exception);
_messageService.ShowMessage("An error ocurred while classyfing the drawing. Please try again.", "Classification error", icon: MessageBoxIcon.Information);
}
}
public async Task <Prediction> PredictAsync(Image <Rgba32> image)
{
var preprocessor = new ImagePreprocessor(Rgba32.White, Rgba32.Black);
image = preprocessor.Preprocess(image);
var inputs = PrepareMLStudioInput(image);
using (var client = new HttpClient())
{
var requestContent = new StringContent(inputs);
requestContent.Headers.ContentType = new MediaTypeHeaderValue("application/json");
client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", _apiKey);
var response = await client.PostAsync(_apiUrl, requestContent);
var responseContent = response.Content is HttpContent c ? await c.ReadAsStringAsync() : null;
var prediction = JsonConvert.DeserializeObject <MLStudioResponseObject>(responseContent);
var tag = prediction.results.WebServiceOutput0.FirstOrDefault()?["Scored Labels"];
return(new Prediction
{
Tag = Convert.ToInt32(tag),
Probability = 1
});
}
}
public void UploadPhoto(Stream photoDataStream, Action <BackendResult <Photo, ResultCode> > callback)
{
ImagePreprocessor.PreprocessImage(photoDataStream, VKConstants.ResizedImageSize, true, (Action <ImagePreprocessResult>)(pres =>
{
Stream stream = pres.Stream;
byte[] numArray = new byte[stream.Length];
stream.Read(numArray, 0, (int)stream.Length);
stream.Close();
this.SetInProgress(true, "");
PhotosService.Current.UploadPhotoToAlbum(this._albumId, this._isGroup ? this._userOrGroupId : 0, numArray, (Action <BackendResult <Photo, ResultCode> >)(res =>
{
this.SetInProgress(false, "");
if (res.ResultCode == ResultCode.Succeeded)
{
Execute.ExecuteOnUIThread((Action)(() =>
{
Photo resultData1 = res.ResultData;
EventAggregator current = EventAggregator.Current;
PhotoUploadedToAlbum photoUploadedToAlbum = new PhotoUploadedToAlbum();
photoUploadedToAlbum.photo = resultData1;
long pid = resultData1.pid;
photoUploadedToAlbum.pid = pid;
string str = resultData1.aid.ToString();
photoUploadedToAlbum.aid = str;
current.Publish((object)photoUploadedToAlbum);
if (string.IsNullOrEmpty(this.ThumbSrc))
{
EventAggregator.Current.Publish((object)new PhotoSetAsAlbumCover()
{
aid = this._albumId,
pid = resultData1.pid,
Photo = resultData1
});
}
else
{
if (this._albumPhotos.Count <= 1)
{
return;
}
Photo photo = this._albumPhotos[1].Photo;
if (!(this.ThumbSrc == photo.photo_75) && !(this.ThumbSrc == photo.photo_130) && (!(this.ThumbSrc == photo.photo_604) && !(this.ThumbSrc == photo.photo_807)) && (!(this.ThumbSrc == photo.photo_1280) && !(this.ThumbSrc == photo.photo_2560) && (!(this.ThumbSrc == photo.src) && !(this.ThumbSrc == photo.src_small))) && (!(this.ThumbSrc == photo.src_big) && !(this.ThumbSrc == photo.src_xbig) && !(this.ThumbSrc == photo.src_xxbig)))
{
return;
}
Photo resultData2 = res.ResultData;
EventAggregator.Current.Publish((object)new PhotoSetAsAlbumCover()
{
aid = this._albumId,
Photo = resultData2,
pid = resultData2.pid
});
}
}));
}
callback(res);
}));
}));
}
public Stream GetImageStream(string albumId, int seqNo, bool preview = false)
{
ImageEffectsInfo imageEffectsInfo1 = this._sessionEffectsInfo.GetImageEffectsInfo(albumId, seqNo);
if (!preview && imageEffectsInfo1.AppliedAny)
{
string pathForEffects = this.GetPathForEffects(albumId, seqNo);
using (IsolatedStorageFile storeForApplication = IsolatedStorageFile.GetUserStoreForApplication())
{
using (IsolatedStorageFileStream storageFileStream = storeForApplication.OpenFile(pathForEffects, (FileMode)3, (FileAccess)1))
{
MemoryStream exifStream = new MemoryStream();
if (imageEffectsInfo1.Exif != null)
{
exifStream = new MemoryStream(this.ResetOrientation(imageEffectsInfo1.ParsedExif.OrientationOffset, imageEffectsInfo1.Exif, imageEffectsInfo1.ParsedExif.LittleEndian));
}
MemoryStream memoryStream = ImagePreprocessor.MergeExif((Stream)storageFileStream, exifStream);
exifStream.Close();
return((Stream)memoryStream);
}
}
}
else
{
Stopwatch stopwatch = Stopwatch.StartNew();
Picture galleryImage = this.GetGalleryImage(albumId, seqNo);
if (preview)
{
Stream thumbnail = galleryImage.GetThumbnail();
galleryImage.Dispose();
stopwatch.Stop();
return(thumbnail);
}
ImageEffectsInfo imageEffectsInfo2 = this.GetImageEffectsInfo(albumId, seqNo);
Stream image = galleryImage.GetImage();
if (imageEffectsInfo2.Exif == null && !this.SuppressParseEXIF)
{
Stopwatch.StartNew();
MemoryStream exifStream;
ImagePreprocessor.PatchAwayExif(image, out exifStream);
image.Position = 0L;
imageEffectsInfo2.Exif = new byte[exifStream.Length];
exifStream.Read(imageEffectsInfo2.Exif, 0, (int)exifStream.Length);
JpegInfo info = new ExifReader(image).info;
imageEffectsInfo2.ParsedExif = info;
image.Position = 0L;
}
stopwatch.Stop();
galleryImage.Dispose();
return(image);
}
}
/// <summary>
/// When an image changes, this method updates all images
/// </summary>
private void RefreshDisplayedImages()
{
currImageI = new Image <Bgr, byte>(curr.Title);
nextImageI = new Image <Bgr, byte>(next.Title);
_preprocessor = new ImagePreprocessor(curr, next);
int currFacesCount = _preprocessor.FacesListCurr.Count;
int nextFacesCount = _preprocessor.FacesListNext.Count;
if (currFacesCount > 0 && nextFacesCount > 0)
{
facesDetected = true;
}
if (!_preprocessor.MorphEnabled)
{
InitializeComponent();
//morphBtn.IsEnabled = false;
mySlider.IsEnabled = false;
displayMorphOk = false;
}
else
{
InitializeComponent();
//morphBtn.IsEnabled = true;
mySlider.IsEnabled = true;
displayMorphOk = true;
}
// Display errors and number of found faces:
facesCountCurr.Content = $"{_preprocessor.FacesListCurr.Count}";
facesCountNext.Content = $"{_preprocessor.FacesListNext.Count}";
errorMessageCurr.Content = "";
errorMessageNext.Content = "";
if (_preprocessor.FacesListCurr.Count == 0)
{
errorMessageCurr.Content = "No faces were found";
}
errorMessageCurr.Foreground = System.Windows.Media.Brushes.Red;
if (_preprocessor.FacesListNext.Count == 0)
{
errorMessageNext.Content = "No faces were found";
}
errorMessageNext.Foreground = System.Windows.Media.Brushes.Red;
// ---------------------------------------------
this.currImageI = _preprocessor.CurrImageI;
this.nextImageI = _preprocessor.NextImageI;
}
private void OnClassifyDrawing(object sender, EventArgs e)
{
try
{
_loggingService.Log("Classify drawing has started");
var imagePreprocessor = new ImagePreprocessor();
IPredictionModel predictionModel = Global.PredictionModel;
Image img = _slidingWindowView.Drawing;
foreach (Size windowSize in WindowSizes)
{
foreach (BoundingBox boundingBox in ImageUtilities.SlidingWindow(img, windowSize, 112))
{
try
{
double[] pixels = imagePreprocessor.Preprocess(boundingBox.Image);
double[] prediction = predictionModel.Predict(pixels);
// If classification is over 99% draw a bounding box at this location
int predicted = prediction.ArgMax();
double predictedAccuracy = prediction[prediction.ArgMax()];
if (predictedAccuracy >= 0.95)
{
_slidingWindowView.DrawBoundingBox(boundingBox, predicted, predictedAccuracy);
}
}
catch (Exception exception)
{
_loggingService.Log(exception);
}
}
}
_loggingService.Log("Classify drawing has completed");
}
catch (Exception exception)
{
_loggingService.Log(exception);
_messageService.ShowMessage("An error ocurred while classyfing the drawing. Please try again.", "Classification error", icon: MessageBoxIcon.Information);
}
}
private void InitCamera()
{
// ADD CAMERA SUPPORT
_imagePreprocessor = new ImagePreprocessor();
_cameraHandler = CameraHandler.Instance;
Handler threadLooper = new Handler(MainLooper);
_cameraHandler.InitializeCamera(this, threadLooper, new ImageAvailableListener()
{
OnImageAvailableAction = (imageReader) =>
{
Bitmap bitmap = _imagePreprocessor.PreprocessImage(imageReader.AcquireNextImage());
OnPhotoReady(bitmap);
}
});
}
internal static async Task Main(string[] args)
{
if (args.Length == 0)
{
Console.WriteLine("Source directory needed.");
return;
}
string res = args[0];
string sourceDirectory = $"Resources/{res}";
string destTempDirectory = $"temp/{res}_preprocessed";
bool skipPreprocessing = false;
if (args.Length > 1 && bool.Parse(args[1]))
skipPreprocessing = true;
if (!skipPreprocessing)
{
IImageProvider rawImageProvider = new DirectoryImageProvider();
IImagePreprocessor preprocessor = new ImagePreprocessor();
preprocessor.ProcessImages(rawImageProvider.LoadImages(sourceDirectory), destTempDirectory);
}
int NUM_LAYERS = 8;
Network network = new Network(NUM_LAYERS);
var pictureDirectories = Directory.EnumerateDirectories(destTempDirectory);
Directory.CreateDirectory("results");
Directory.CreateDirectory(destTempDirectory);
System.Diagnostics.Stopwatch stopwatch = new System.Diagnostics.Stopwatch();
int NUM_THREADS = 4;
for (int i = 0; i < NUM_LAYERS; i += NUM_THREADS)
{
Task[] splitTask = new Task[NUM_THREADS];
for(int t = 0; t < NUM_THREADS; t++)
{
int layerIndex = t + i;
splitTask[t] = Task.Run(() => DoAnalysis(layerIndex, pictureDirectories, ref network));
}
await Task.WhenAll(splitTask);
}
}
internal void SetUserPhoto(Stream stream, Rect rect)
{
this._photoCropRect = rect;
ImagePreprocessor.PreprocessImage(stream, 1500000, false, (Action <ImagePreprocessResult>)(imPR => Execute.ExecuteOnUIThread((Action)(() =>
{
BitmapImage bitmapImage = new BitmapImage();
Stream stream1 = imPR.Stream;
bitmapImage.SetSource(stream1);
WriteableBitmap bmp = new WriteableBitmap((BitmapSource)bitmapImage);
WriteableBitmap bitmap = bmp.Crop(new Rect()
{
Width = (double)bmp.PixelWidth * rect.Width,
Height = (double)bmp.PixelHeight * rect.Height,
Y = rect.Top * (double)bmp.PixelHeight,
X = rect.Left * (double)bmp.PixelWidth
});
try
{
if (!string.IsNullOrWhiteSpace(this._fullAvatarUri))
{
File.Delete(this._fullAvatarUri);
}
using (IsolatedStorageFile storeForApplication = IsolatedStorageFile.GetUserStoreForApplication())
{
MemoryStream memoryStream = new MemoryStream();
bitmap.SaveJpeg((Stream)memoryStream, bitmap.PixelWidth, bitmap.PixelHeight, 0, 90);
memoryStream.Position = 0L;
this._fullAvatarUri = Guid.NewGuid().ToString();
ImageCache.Current.TrySetImageForUri("cropped" + this._fullAvatarUri, (Stream)memoryStream);
stream.Position = 0L;
using (IsolatedStorageFileStream storageFileStream = storeForApplication.OpenFile(this._fullAvatarUri, FileMode.Create, FileAccess.Write))
StreamUtils.CopyStream(stream, (Stream)storageFileStream, (Action <double>)null, (Cancellation)null, 0L);
this.HavePhoto = true;
}
}
catch
{
}
}))));
}
public override void Upload(Action completionCallback, Action <double> progressCallback = null)
{
Action action;
Execute.ExecuteOnUIThread((Action)(() =>
{
if (this.UploadState == OutboundAttachmentUploadState.Uploading)
{
return;
}
if (this.UploadState == OutboundAttachmentUploadState.Completed)
{
completionCallback();
}
else
{
this.UploadState = OutboundAttachmentUploadState.Uploading;
Stream stream = ImageCache.Current.GetCachedImageStream(this.LocalUrlBig);
ImagePreprocessor.PreprocessImage(stream, VKConstants.ResizedImageSize, true, (Action <ImagePreprocessResult>)(pres =>
{
Stream stream2 = pres.Stream;
stream.Close();
byte[] bytes = ImagePreprocessor.ReadFully(stream2);
stream2.Close();
this.UploadImpl(bytes, (action = (Action)(() =>
{
if (this._uploadState == OutboundAttachmentUploadState.Completed && this._photo != null)
{
this.CleanupCache();
this._localUri = this._photo.src_big;
}
completionCallback();
})), progressCallback);
}));
}
}));
}
/// <summary>
/// Generates full video
/// </summary>
/// <param name="images"></param>
public VideoGenerator(ObservableCollection <ImageDetails> images, int fpsUser, float alphaUser, string path)
{
this.images = images;
this.destinationPath = path;
ImagePreprocessor ip1;
System.Drawing.Size tmpSize = new System.Drawing.Size(0, 0);
for (int i = 0; i < images.Count - 1; i++)
{
ip1 = new ImagePreprocessor(images.ElementAt(i), images.ElementAt(i + 1));
if (ip1.FacesListCurr.Count == 0)
{
images.RemoveAt(i);
}
if (ip1.FacesListNext.Count == 0)
{
images.RemoveAt(i + 1);
}
else
{
if (ip1.curr.ResizedImage.Width > tmpSize.Width)
{
tmpSize.Width = ip1.curr.ResizedImage.Width;
}
if (ip1.curr.ResizedImage.Height > tmpSize.Height)
{
tmpSize.Height = ip1.curr.ResizedImage.Width;
}
}
}
if (tmpSize.Width > 1280)
{
tmpSize.Width = 1280;
tmpSize.Height = 720;
}
MorphImage m;
ImagePreprocessor ip;
try
{
//videoWriter = new VideoWriter(fileName: destinationPath, fps: 30, size: tmpSize, isColor: true);
videoWriter = new VideoWriter(fileName: destinationPath, compressionCode: VideoWriter.Fourcc('M', 'P', '4', 'V'), fps: fpsUser, size: tmpSize, isColor: true);
List <Mat> frames = new List <Mat>();
for (int i = 0; i < images.Count - 1; i++)
{
ip = new ImagePreprocessor(images.ElementAt(i), images.ElementAt(i + 1), tmpSize);
float alpha = 0.0f;
while (alpha < 1.0f)
{
m = new MorphImage(ip.curr, ip.next, ip.ffpCurr, ip.ffpNext, alpha);
Image <Bgr, byte> morphedImage = m.GetMorphedImageI();
frames.Add(morphedImage.Mat);
//videoWriter.Write(morphedImage.Mat);
alpha += alphaUser;
//morphedImage.Dispose();
}
}
int img1 = 0;
foreach (Mat mat in frames)
{
img1 += 1;
videoWriter.Write(mat);
}
if (videoWriter.IsOpened)
{
videoWriter.Dispose();
}
MessageBox.Show($"Completed");
}
catch (Exception)
{
MessageBox.Show("The program has run out of memory. Try to use fewer images, a larger alpha value (0.05 - 0.1) or a lower FPS count (25)");
}
}
public BlobHandler()
{
imgProcessor = new ImagePreprocessor();
}
private byte[] ResetOrientation(long p, byte[] exifData, bool littleEndian)
{
return(ImagePreprocessor.ResetOrientation(p, exifData, littleEndian));
}
