// Copy tile to output
private void CopyToOutput(TileRenderState state, Tensor <float> tensor, Rectangle tile)
{
if (tile.Y > 0)
{
BlendTopMargin(state, tensor, tile);
}
var sx = tile.X > 0 ? Margin : 0;
var sy = tile.Y > 0 ? Margin : 0;
var(x, y) = (tile.X, tile.Y);
var cols = Math.Min(tensor.Width() - sx, Output.Width - tile.X);
var rows = Math.Min(tensor.Height() - sy, Output.Height - tile.Y);
var tensorRow = new ArraySegment <byte>(state.TensorRow, 0, cols * 4);
var marginLeft = new ArraySegment <byte>(state.OutputRow, 0, sx * 4);
for (int row = sy; row < rows; ++row)
{
_ = tensor.GetRowArgb(tensorRow, sx, row + sy);
Output.GetRowArgb(marginLeft, tile.X, row + y);
marginLeft.LinearBlend(tensorRow, tensorRow);
Output.SetRowArgb(tensorRow, x, row + y);
}
}
/// <summary>
/// Copy a row of ARGB pixel values to an NHWC-formatted BGR tensor
/// </summary>
/// <param name="tensor">NHWC-formatted BGR-valued tensor</param>
/// <param name="data">Data row containing ARGB pixel values</param>
/// <param name="x">X-offset to copy to</param>
/// <param name="y">Y-offset to copy to</param>
/// <returns>Number of copied elements</returns>
public static int SetRowArgb(this Tensor <float> tensor, byte[] data, int x, int y)
{
Contract.Requires(tensor != null && data != null);
var memory = ((DenseTensor <float>)tensor).Buffer.Span;
var width = tensor.Width();
var offset = y * width * 3 + x * 3;
var cols = Math.Min(data.Length / 4, width);
for (int i = 0, j = offset; i < cols; ++i)
{
memory[j++] = data[i * 4 + 2] / 255f;
memory[j++] = data[i * 4 + 1] / 255f;
memory[j++] = data[i * 4 + 0] / 255f;
}
return(cols * 3);
}
/// <summary>
/// Copy a row of ARGB pixel values to an NHWC-formatted BGR tensor
/// </summary>
/// <param name="tensor">NHWC-formatted BGR-valued tensor</param>
/// <param name="data">Data row containing ARGB pixel values</param>
/// <param name="x">X-offset to copy to</param>
/// <param name="y">Y-offset to copy to</param>
/// <returns>Number of copied elements</returns>
public static int SetRowArgb(this Tensor <float> tensor, ArraySegment <byte> data, int x, int y)
{
Contract.Requires(tensor != null);
var memory = ((DenseTensor <float>)tensor).Buffer.Span;
var source = data.Array;
var width = tensor.Width();
var offset = y * width * 3 + x * 3;
var cols = Math.Min(data.Count / 4, width);
for (int i = 0, j = offset, k = data.Offset; i < cols; ++i, k += 4)
{
memory[j++] = source[k + 2] / 255f;
memory[j++] = source[k + 1] / 255f;
memory[j++] = source[k + 0] / 255f;
}
return(cols * 3);
}
// Blend a tile's top rows with previous output
private void BlendTopMargin(TileRenderState state, Tensor <float> tensor, Rectangle tile)
{
var(ix, iy) = (tile.X > 0 ? Margin : 0, Margin);
var(ox, oy) = (tile.X, tile.Y);
var delta = 1.0f / Margin;
var c = delta;
var elements = (tensor.Width() - ix) * 4;
var tensorRow = new ArraySegment <byte>(state.TensorRow, 0, elements);
var outputRow = new ArraySegment <byte>(state.OutputRow, 0, elements);
var resultRow = new ArraySegment <byte>(state.BufferRow, 0, elements);
for (int i = 0; i < Margin; ++i, ++iy, ++oy, c += delta)
{
_ = tensor.GetRowArgb(tensorRow, ix, iy);
_ = Output.GetRowArgb(outputRow, ox, oy);
outputRow.MixArgb(tensorRow, resultRow, c);
Output.SetRowArgb(resultRow, ox, oy);
}
}