public async Task PredImages(string dirPath)
{
var imagePaths = await Task.Run <IEnumerable <string> >(() =>
{ return(Directory.EnumerateFiles(dirPath)); });
ImageResults.Clear();
Source = new CancellationTokenSource();
foreach (var imageClass in ImageClasses)
{
imageClass.Clear();
ClassesInfo[ImageClasses.IndexOf(imageClass)] =
ClassInfoProcess(ImageClasses.IndexOf(imageClass), 0);
}
foreach (var imagePath in imagePaths)
{
ImageResults.Add(new MNISTModelResult(imagePath));
}
await Task.Run(() => model.PredImages(dirPath, Source.Token));
}
public async Task PredImages(string dirPath)
{
var imagePaths = await Task.Run <IEnumerable <string> >(() =>
{ return(Directory.EnumerateFiles(dirPath)); });
ImageResults.Clear();
Source = new CancellationTokenSource();
foreach (var imageClass in ImageClasses)
{
imageClass.Clear();
ClassesInfo[ImageClasses.IndexOf(imageClass)] =
ClassInfoProcess(ImageClasses.IndexOf(imageClass), 0);
}
ParallelOptions options = new ParallelOptions();
options.CancellationToken = Source.Token;
processed = 0;
numOfImages = imagePaths.Count();
ProdProgressInfo();
dbContext = new ImageDbContext();
await Task.Run(() =>
{
Parallel.ForEach(imagePaths, options, (imagePath) =>
{
List <string> imagesToClassify = new List <string>();
if (Source.Token.IsCancellationRequested)
{
return;
}
MNISTModelResultDb dbImage = null;
dbImage = FindImageInDb(imagePath);
if (dbImage != null)
{
Dispatcher.UIThread.InvokeAsync(() =>
{
lock (ImageResults)
{
ImageResults.Add(dbImage);
ImageClasses[dbImage.Class].Add(dbImage);
ClassesInfo[dbImage.Class] = ClassInfoProcess(dbImage.Class,
ImageClasses[dbImage.Class].Count);
processed++;
ProdProgressInfo();
}
});
}
else
{
Dispatcher.UIThread.InvokeAsync(() =>
{
lock (ImageResults)
{
ImageResults.Add(new MNISTModelResultDb(imagePath));
}
});
imagesToClassify.Add(imagePath);
model.PredImages(imagesToClassify, Source.Token).Wait();
}
});
});
}