void ResultEventHandler(object sender, ResultEventArgs args)
{
var result = args.Result;
int index = 0;
lock (ImageResults) {
foreach (var image in ImageResults)
{
if (image.Path == result.Path)
{
index = ImageResults.IndexOf(image);
break;
}
}
Dispatcher.UIThread.InvokeAsync(() => {
lock (ImageResults) {
ImageResults[index] = new MNISTModelResultDb(result);
ImageClasses[result.Class].Add(new MNISTModelResultDb(result));
ClassesInfo[result.Class] = ClassInfoProcess(result.Class,
ImageClasses[result.Class].Count);
processed++;
ProdProgressInfo();
}
});
Task.Run(() =>
{
lock (dbContext)
{
Bitmap resImage = new Bitmap(result.Path);
Blob resBlob = new Blob {
Bytes = ImageToByteArray(resImage)
};
dbContext.ClassifiedImages.Add(new ClassifiedImage {
Path = result.Path,
Class = result.Class, Confidence = result.Confidence,
RetrieveCount = 0, Image = resBlob
});
dbContext.Blobs.Add(resBlob);
dbContext.SaveChanges();
}
});
}
}
void ResultEventHandler(object sender, ResultEventArgs args)
{
var result = args.Result;
int index = 0;
lock (ImageResults) {
foreach (var image in ImageResults)
{
if (image.Path == result.Path)
{
index = ImageResults.IndexOf(image);
break;
}
}
Dispatcher.UIThread.InvokeAsync(() => {
lock (ImageResults) {
ImageResults[index] = new MNISTModelResult(result);
ImageClasses[result.Class].Add(new MNISTModelResult(result));
ClassesInfo[result.Class] = ClassInfoProcess(result.Class,
ImageClasses[result.Class].Count);
}
});
}
}
