public ConvolutionRowOperation(
Rectangle bounds,
Buffer2D <TPixel> targetPixels,
Buffer2D <TPixel> sourcePixels,
KernelSamplingMap map,
DenseMatrix <float> kernelMatrix,
Configuration configuration,
bool preserveAlpha)
{
this.bounds = bounds;
this.targetPixels = targetPixels;
this.sourcePixels = sourcePixels;
this.map = map;
this.kernelMatrix = kernelMatrix;
this.configuration = configuration;
this.preserveAlpha = preserveAlpha;
}
/// <inheritdoc/>
protected override void OnFrameApply(ImageFrame <TPixel> source)
{
using Buffer2D <TPixel> firstPassPixels = this.Configuration.MemoryAllocator.Allocate2D <TPixel>(source.Size());
var interest = Rectangle.Intersect(this.SourceRectangle, source.Bounds());
// We use a rectangle 2x the interest width to allocate a buffer big enough
// for source and target bulk pixel conversion.
var operationBounds = new Rectangle(interest.X, interest.Y, interest.Width * 2, interest.Height);
// We can create a single sampling map with the size as if we were using the non separated 2D kernel
// the two 1D kernels represent, and reuse it across both convolution steps, like in the bokeh blur.
using var mapXY = new KernelSamplingMap(this.Configuration.MemoryAllocator);
mapXY.BuildSamplingOffsetMap(this.Kernel.Length, this.Kernel.Length, interest);
// Horizontal convolution
var horizontalOperation = new HorizontalConvolutionRowOperation(
interest,
firstPassPixels,
source.PixelBuffer,
mapXY,
this.Kernel,
this.Configuration,
this.PreserveAlpha);
ParallelRowIterator.IterateRows <HorizontalConvolutionRowOperation, Vector4>(
this.Configuration,
operationBounds,
in horizontalOperation);
// Vertical convolution
var verticalOperation = new VerticalConvolutionRowOperation(
interest,
source.PixelBuffer,
firstPassPixels,
mapXY,
this.Kernel,
this.Configuration,
this.PreserveAlpha);
ParallelRowIterator.IterateRows <VerticalConvolutionRowOperation, Vector4>(
this.Configuration,
operationBounds,
in verticalOperation);
}
public SecondPassConvolutionRowOperation(
Rectangle bounds,
Buffer2D <Vector4> targetValues,
Buffer2D <ComplexVector4> sourceValues,
KernelSamplingMap map,
Complex64[] kernel,
float z,
float w)
{
this.bounds = bounds;
this.targetValues = targetValues;
this.sourceValues = sourceValues;
this.map = map;
this.kernel = kernel;
this.z = z;
this.w = w;
}
public HorizontalConvolutionRowOperation(
Rectangle bounds,
Buffer2D <TPixel> targetPixels,
Buffer2D <TPixel> sourcePixels,
KernelSamplingMap map,
float[] kernel,
Configuration configuration,
bool preserveAlpha)
{
this.bounds = bounds;
this.targetPixels = targetPixels;
this.sourcePixels = sourcePixels;
this.map = map;
this.kernel = kernel;
this.configuration = configuration;
this.preserveAlpha = preserveAlpha;
}
/// <summary>
/// Computes and aggregates the convolution for each complex kernel component in the processor.
/// </summary>
/// <param name="source">The source image. Cannot be null.</param>
/// <param name="sourceRectangle">The <see cref="Rectangle" /> structure that specifies the portion of the image object to draw.</param>
/// <param name="configuration">The configuration.</param>
/// <param name="processingBuffer">The buffer with the raw pixel data to use to aggregate the results of each convolution.</param>
private void OnFrameApplyCore(
ImageFrame <TPixel> source,
Rectangle sourceRectangle,
Configuration configuration,
Buffer2D <Vector4> processingBuffer)
{
// Allocate the buffer with the intermediate convolution results
using Buffer2D <ComplexVector4> firstPassBuffer = configuration.MemoryAllocator.Allocate2D <ComplexVector4>(source.Size());
// Unlike in the standard 2 pass convolution processor, we use a rectangle of 1x the interest width
// to speedup the actual convolution, by applying bulk pixel conversion and clamping calculation.
// The second half of the buffer will just target the temporary buffer of complex pixel values.
// This is needed because the bokeh blur operates as TPixel -> complex -> TPixel, so we cannot
// convert back to standard pixels after each separate 1D convolution pass. Like in the gaussian
// blur though, we preallocate and compute the kernel sampling maps before processing each complex
// component, to avoid recomputing the same sampling map once per convolution pass. Since we are
// doing two 1D convolutions with the same kernel, we can use a single kernel sampling map as if
// we were using a 2D kernel with each dimension being the same as the length of our kernel, and
// use the two sampling offset spans resulting from this same map. This saves some extra work.
using var mapXY = new KernelSamplingMap(configuration.MemoryAllocator);
mapXY.BuildSamplingOffsetMap(this.kernelSize, this.kernelSize, sourceRectangle);
ref Complex64[] baseRef = ref MemoryMarshal.GetReference(this.kernels.AsSpan());