How to use

scaleExt

method

in

boofcv.abst.distort.FDistort

  public static void main(String[] args) {
    BufferedImage original = UtilImageIO.loadImage(UtilIO.pathExample("simple_objects.jpg"));

    Planar<GrayF32> input = new Planar<>(GrayF32.class,
        original.getWidth(),original.getHeight(),3);

    ConvertBufferedImage.convertFromPlanar(original,input,true,GrayF32.class);

    Planar<GrayF32> output = new Planar<>(GrayF32.class,
        original.getWidth()/3,original.getHeight()/3,3);
    Planar<GrayF32> output2 = new Planar<>(GrayF32.class,
        original.getWidth()/3,original.getHeight()/3,3);

    AverageDownSampleOps.down(input, output);
    new FDistort(input,output2).scaleExt().apply();

    BufferedImage outputFull = ConvertBufferedImage.convertTo_F32(output, null, true);
    BufferedImage outputFull2 = ConvertBufferedImage.convertTo_F32(output2, null, true);

    ShowImages.showWindow(original,"Original");
    ShowImages.showWindow(outputFull,"3x small average");
    ShowImages.showWindow(outputFull2,"3x small bilinear");
  }
}

new FDistort(unscaled,input0).scaleExt().apply();
ConvertBufferedImage.convertFrom(image1, unscaled, false);
new FDistort(unscaled,input1).scaleExt().apply();

  private void scaleUpLayers() {
    T l = pyramid.getLayer(0);
    if( upscale == null ) {
      interp = (InterpolatePixelS<T>) FactoryInterpolation.nearestNeighborPixelS(l.getClass());
      upscale = (T)l.createNew(l.width,l.height);
    } else {
      upscale.reshape(l.width,l.height);
    }

    int N = pyramid.getNumLayers();

    for( int i = 0; i < N; i++ ) {
      new FDistort(pyramid.getLayer(i),upscale).interpNN().scaleExt().apply();
      BufferedImage b = ConvertBufferedImage.convertTo(upscale,null,true);
      if( showScales )
        addImage(b,String.format("%5.2f",pyramid.getScale(i)));
      else
        addImage(b,String.format("%5.2f",pyramid.getSigma(i)));
    }
  }
}

  private void scaleUpLayers() {
    T l = pyramid.getLayer(0);
    if( upscale == null ) {
      interp = (InterpolatePixelS<T>) FactoryInterpolation.nearestNeighborPixelS(l.getClass());
      upscale = (T)l.createNew(l.width,l.height);
    } else {
      upscale.reshape(l.width,l.height);
    }

    int N = pyramid.getNumLayers();

    for( int i = 0; i < N; i++ ) {
      new FDistort(pyramid.getLayer(i),upscale).interpNN().scaleExt().apply();
      BufferedImage b = ConvertBufferedImage.convertTo(upscale,null,true);
      if( showScales )
        addImage(b,String.format("%5.2f",pyramid.getScale(i)));
      else
        addImage(b,String.format("%5.2f",pyramid.getSigma(i)));
    }
  }
}

@Override
public void setActiveAlgorithm(String name, Object cookie) {
  DerivType type = (DerivType)cookie;
  panel.reset();
  for( int radius = 1; radius <= 40; radius += 2 ) {
    int maxOrder = Math.max(type.orderX,type.orderY);
    double sigma = FactoryKernelGaussian.sigmaForRadius(radius,maxOrder);
    Class typeKer1 = FactoryKernel.getKernelType(imageType,1);
    Kernel1D kerX =  FactoryKernelGaussian.derivativeK(typeKer1,type.orderX,sigma,radius);
    Kernel1D kerY = FactoryKernelGaussian.derivativeK(typeKer1,type.orderY,sigma,radius);
    Kernel2D kernel = GKernelMath.convolve(kerY, kerX);
    T smallImg = GKernelMath.convertToImage(kernel);
    new FDistort(smallImg,largeImg).interpNN().scaleExt().apply();
    double maxValue = GImageStatistics.maxAbs(largeImg);
    BufferedImage out = VisualizeImageData.colorizeSign(largeImg,null,maxValue);
    panel.addImage(out,String.format("%5d",radius));
  }
}

  AverageDownSampleOps.down(inputGray,scaled);
} else {
  new FDistort(inputGray,scaled).scaleExt().apply();

@Override
public void setActiveAlgorithm(String name, Object cookie) {
  DisplayGaussianKernelApp.DerivType dt = (DisplayGaussianKernelApp.DerivType)cookie;
  // add basis
  SteerableKernel<K> steerable = createKernel(dt.orderX,dt.orderY);
  basisPanel.reset();
  for( int i = 0; i < steerable.getBasisSize(); i++ ) {
    T smallImg = GKernelMath.convertToImage(steerable.getBasis(i));
    new FDistort(smallImg,largeImg).scaleExt().interpNN().apply();
    double maxValue = GImageStatistics.maxAbs(largeImg);
    BufferedImage out = VisualizeImageData.colorizeSign(largeImg,null,maxValue);
    basisPanel.addImage(out,"Basis "+i);
  }
  // add steered kernels
  steerPanel.reset();
  for( int i = 0; i <= 20; i++  ) {
    double angle = Math.PI*i/20.0;
    K kernel = steerable.compute(angle);
    T smallImg = GKernelMath.convertToImage(kernel);
    new FDistort(smallImg,largeImg).scaleExt().interpNN().apply();
    double maxValue = GImageStatistics.maxAbs(largeImg);
    BufferedImage out = VisualizeImageData.colorizeSign(largeImg,null,maxValue);
    steerPanel.addImage(out,String.format("%5d",(int)(180.0*angle/Math.PI)));
  }
  repaint();
}

new FDistort(featureImg,scaledIntensity).interpNN().scaleExt().apply();