public void AddToDataBase(ResultClassification obj)
{
lock (db)
{
Avalonia.Media.Imaging.Bitmap BImage = new Avalonia.Media.Imaging.Bitmap(obj._PathImage);
Blob ImageBlob = new Blob {
Bytes = ImageToByteArray(BImage)
};
db.Blobs.Add(ImageBlob);
db.SaveChanges();
RecognitionImage elem = new RecognitionImage
{
Class = obj._ClassImage,
Prob = obj.Probability,
ImageBytes = ImageBlob,
Call = 0,
Hash = GetHashFromBytes(ImageToByteArray(BImage))
};
db.Images.Add(elem);
db.SaveChanges();
}
}
public void ClassificationImages(string currentDirectory)
{
Classes.Clear();
PathImages = new List <string>(Directory.GetFiles(currentDirectory, "*.jpg"));
Thread t = new Thread(() =>
{
foreach (string path in PathImages)
{
ResultClassification imageDataBase = FindInDataBase(path);
if (imageDataBase != null)
{
ExistsCompletedHandler(imageDataBase);
}
else
{
NewPathImages.Enqueue(path);
}
}
task = new ThreadClassification(NewPathImages, onnxModel, RecognitionCompletedHandler);
task.Run();
});
t.Start();
}
public void CreateResults(ResultClassification elem)
{
Dispatcher.UIThread.InvokeAsync(() => {
Result.Add(elem);
int index = CheckUniqueClass(elem._ClassImage);
if (index == -1)
{
Classes.Add(new Tuple <string, int>(elem._ClassImage, 1));
}
else
{
Classes[index] = new Tuple <string, int>(Classes[index].Item1, Classes[index].Item2 + 1);
}
});
}
static void RecognitionCompletedHandler(ResultClassification result)
{
Console.WriteLine(result);
}
public void ExistsCompletedHandler(ResultClassification elem)
{
CreateResults(elem);
}
public void RecognitionCompletedHandler(ResultClassification elem)
{
CreateResults(elem);
AddToDataBase(elem);
}
