private void Btn_runML_Click(object sender, RoutedEventArgs e)
{
MainWindow.mMainWindow.listBox.Items.Clear();
switch (MLCore.MLModelSelected)
{
case MLModel.ResNet:
ResNet.EvaluationSingleImage(GV.imgOriginal);
for (int i = 0; i < ResNet.resultList.Count; i++)
{
MainWindow.mMainWindow.listBox.Items.Add(string.Format("{0}: {1}", MLCore.MLSelectedLabels[i], ResNet.resultList[i]));
}
BindMngr.GMessage.value = string.Format("This must be a {0}!", ResNet.OutputString, ResNet.OutputProbablility);
break;
case MLModel.FastRCNN:
FastRCNN.EvaluateObjectDetectionModel();
break;
case MLModel.Yolo:
GV.imgProcessed = new Image <Bgr, byte>(mYolo.Detect(GV.imgOriginal.ToBitmap()));
MainWindow.mMainWindow.ibOriginal.Source = ImgConverter.ToBitmapSource(GV.imgProcessed);
break;
}
}
public static List <PredResult> GroceryDetection()
{
string imagePath = string.Format("{0}images\\grocery.jpg", AppDomain.CurrentDomain.BaseDirectory);
FastRCNN app = new FastRCNN(FastRCNNModel.Grocery100);
app.LoadModel();
return(app.Predict(imagePath));
}
public static List <PredResult> PascalDetection()
{
string imagePath = string.Format("{0}\\images\\objdet.jpg", AppDomain.CurrentDomain.BaseDirectory);
FastRCNN app = new FastRCNN(FastRCNNModel.Pascal);
app.LoadModel();
return(app.Predict(imagePath));
}
