コード例 #1
0
ファイル: ProcessWorkflow.java プロジェクト: cmongis/imagejfx
  /**
   * Extract the plane at the different positions and concatenate the Dataset
   *
   * @param newValue
   * @return
   */
  private CallbackTask<Void, Void> createSampleImage(File newValue) {
    return new CallbackTask<Void, Void>()
        .run(
            () -> {
              try {
                File fileTarget = workflowModel.getMapImages().get(newValue);
                Dataset datasetTarget = (Dataset) iOService.open(fileTarget.getAbsolutePath());
                ImageDisplay imageDisplayTarget = new SilentImageDisplay();
                context.inject(imageDisplayTarget);
                imageDisplayTarget.display(datasetTarget);
                selectPosition(
                    imageDisplayTarget,
                    workflowModel.getPositionLeft(),
                    workflowModel.getPositionRight(),
                    imageDisplayPaneRight);

                Dataset datasetSource = (Dataset) iOService.open(newValue.getAbsolutePath());
                ImageDisplay imageDisplaySource = new SilentImageDisplay();
                context.inject(imageDisplaySource);
                imageDisplaySource.display(datasetSource);
                selectPosition(
                    imageDisplaySource,
                    workflowModel.getPositionLeft(),
                    workflowModel.getPositionRight(),
                    imageDisplayPaneLeft);

              } catch (IOException ex) {
                Logger.getLogger(ProcessWorkflow.class.getName()).log(Level.SEVERE, null, ex);
              }
            })
        .submit(loadingScreenService);
  }
コード例 #2
0
  public void dummySegmentation() {

    List<Dataset> predictDataset = new ArrayList<>(imgDatasets.size());

    INDArray predict = dummyClassification();
    int currIdx = 0;

    for (int ds = 0; ds < imgDatasets.size(); ds++) {
      List<List<int[]>> profilesSet = testData.get(ds).getProfiles();

      predictDataset.add(imagePlaneService.createEmptyPlaneDataset(imgDatasets.get(ds)));

      Dataset currDataset = predictDataset.get(ds);

      RandomAccess<RealType<?>> randomAccess = currDataset.randomAccess();

      for (List<int[]> p : profilesSet) {
        for (int i = 0; i < p.size(); i++) {
          randomAccess.setPosition(p.get(i)[0], 0);
          randomAccess.setPosition(p.get(i)[1], 1);

          double value = predict.getRow(currIdx).getDouble(i);
          if (value != 0) randomAccess.get().setReal(value);
        }
      }
      Overlay[] overlays = BinaryToOverlay.transform(context, currDataset, true);
      //            List<Overlay> overlayList = Arrays.asList(BinaryToOverlay.transform(context,
      // currDataset, true));
      overlayStatService.setRandomColor(Arrays.asList(overlays));
      ImageDisplay display = new DefaultImageDisplay();
      context.inject(display);
      display.display(currDataset);
      for (Overlay o : overlays) {
        display.display(o);
      }
      uis.show(display);
    }
  }