public static void RunHorizontal1D(NativeArray <byte> pixelBuffer, NativeArray <float> pixelOut,
Kernel2D <short> kernel, int width, int height)
{
var xPad = (kernel.Width - 1) / 2;
for (var r = 0; r < height; r++)
{
var rowIndex = r * width;
for (var c = xPad; c < width - xPad; c++)
{
var centerPixelIndex = rowIndex + c;
var kernelIndex = 0;
var kernelSum = 0f;
for (var kX = -xPad; kX < xPad; kX++)
{
var pixelIndex = centerPixelIndex + kX;
var inputPixelValue = pixelBuffer[pixelIndex];
float kernelMultiplier = kernel.Weights[kernelIndex];
kernelSum += inputPixelValue * kernelMultiplier;
kernelIndex++;
}
kernelSum /= 255f;
pixelOut[centerPixelIndex] = kernelSum;
}
}
}
public static void ConvolveVertical(this Kernel2D <byte> kernel,
Image <byte> image, NativeArray <float> pixelOut,
int yPad)
{
var pixelBuffer = image.Buffer;
var width = image.Width;
var height = image.Height;
for (var r = yPad; r < height - yPad; r++)
{
var rowIndex = r * width;
for (var c = 0; c < width; c++)
{
var centerPixelIndex = rowIndex + c;
var kernelIndex = 0;
var kernelSum = 0f;
for (var kY = -yPad; kY < yPad; kY++)
{
var kRowOffset = kY * width;
var pixelIndex = centerPixelIndex + kRowOffset;
var inputPixelValue = pixelBuffer[pixelIndex];
float kernelMultiplier = kernel.Weights[kernelIndex];
kernelSum += inputPixelValue * kernelMultiplier;
kernelIndex++;
}
pixelOut[centerPixelIndex] = kernelSum;
}
}
}
public static float3 Accumulate(this Kernel2D <float> kernel,
Image <float3> image, int centerPixelIndex)
{
var kernelIndex = 0;
var sum = new float3();
var pixelBuffer = image.Buffer;
var negativeBound = kernel.Bounds.negative;
var positiveBound = kernel.Bounds.positive;
for (var y = negativeBound.y; y <= positiveBound.y; y++)
{
var rowOffset = y * image.Width;
var rowIndex = centerPixelIndex + rowOffset;
for (var x = negativeBound.x; x <= positiveBound.x; x++)
{
var pixelIndex = rowIndex + x;
var inputPixelValue = pixelBuffer[pixelIndex];
var kernelMultiplier = kernel.Weights[kernelIndex];
sum += inputPixelValue * kernelMultiplier;
kernelIndex++;
}
}
return(sum);
}
public static void RunVertical1D(NativeArray <float> pixelBuffer, NativeArray <float> pixelOut,
Kernel2D <short> kernel, int width, int height)
{
var yPad = (kernel.Height - 1) / 2;
for (var r = yPad; r < height - yPad; r++)
{
var rowIndex = r * width;
for (var c = 0; c < width; c++)
{
var centerPixelIndex = rowIndex + c;
var kernelIndex = 0;
var kernelSum = 0f;
for (var kY = -yPad; kY < yPad; kY++)
{
var kRowOffset = kY * width;
var pixelIndex = centerPixelIndex + kRowOffset;
var inputPixelValue = pixelBuffer[pixelIndex];
float kernelMultiplier = kernel.Weights[kernelIndex];
kernelSum += inputPixelValue * kernelMultiplier;
kernelIndex++;
}
pixelOut[centerPixelIndex] = kernelSum;
}
}
}
public static float Accumulate(this Kernel2D <float> kernel,
Image <byte> image, int centerPixelIndex)
{
var kernelIndex = 0;
var sum = 0f;
var pixelBuffer = image.Buffer;
var negativeBound = kernel.Bounds.negative;
var positiveBound = kernel.Bounds.positive;
for (var y = negativeBound.y; y <= positiveBound.y; y++)
{
var rowOffset = y * image.Width;
var rowIndex = centerPixelIndex + rowOffset;
for (var x = negativeBound.x; x <= positiveBound.x; x++)
{
var pixelIndex = rowIndex + x;
var inputPixelValue = pixelBuffer[pixelIndex];
var kernelMultiplier = kernel.Weights[kernelIndex];
sum += inputPixelValue * kernelMultiplier;
kernelIndex++;
}
}
//convert from 0-255 byte range to 0-1 float range
const float oneOver255 = 0.0039215686f;
return(sum * oneOver255);
}
public static void ConvolveHorizontal(this Kernel2D <byte> kernel,
Image <byte> image, NativeArray <float> pixelOut,
int xPad)
{
var pixelBuffer = image.Buffer;
var height = image.Height;
var width = image.Width;
for (var r = 0; r < height; r++)
{
var rowIndex = r * width;
for (var c = xPad; c < width - xPad; c++)
{
var centerPixelIndex = rowIndex + c;
var kernelIndex = 0;
var kernelSum = 0f;
for (var kX = -xPad; kX < xPad; kX++)
{
var pixelIndex = centerPixelIndex + kX;
var inputPixelValue = pixelBuffer[pixelIndex];
float kernelMultiplier = kernel.Weights[kernelIndex];
kernelSum += inputPixelValue * kernelMultiplier;
kernelIndex++;
}
kernelSum /= 255f;
pixelOut[centerPixelIndex] = kernelSum;
}
}
}
public static float3 AccumulateVector3(this Kernel2D <float> kernel,
Image <float3> image, int centerPixelIndex)
{
var kernelIndex = 0;
var sum = new float3();
var pixels = image.Buffer;
var negativeBound = kernel.Bounds.negative;
var positiveBound = kernel.Bounds.positive;
for (var y = negativeBound.y; y <= positiveBound.y; y++)
{
var rowOffset = y * image.Width;
var rowIndex = centerPixelIndex + rowOffset;
var rowVec = new float3x3(pixels[rowIndex - 1], pixels[rowIndex], pixels[rowIndex + 1]);
var row = (y + 1);
var kernelRowVec = new float3(kernel.Weights[row * 3], kernel.Weights[row * 3 + 1], kernel.Weights[row * 3 + 2]);
sum += math.mul(rowVec, kernelRowVec);
}
return(sum);
}
public Convolution2D(T[,] kernel, int stride = 1, int pad = 1)
{
Kernel2D = new Kernel2D <T>(kernel);
Stride = new Vector2Int(stride, stride);
Padding = new Vector2Int(pad, pad);
}
public Convolution2D(Kernel2D <T> kernel, Vector2Int stride, Vector2Int padding)
{
Kernel2D = kernel;
Stride = stride;
Padding = padding;
}