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)); }