public MyPipeline(HSBuffer <byte> inBuf)
{
Input = inBuf;
// For this lesson, we'll use a two-stage pipeline that sharpens
// and then applies a look-up-table (LUT).
// First we'll define the LUT. It will be a gamma curve.
Lut[I] = HS.Cast <byte>(HS.Clamp(HSMath.Pow(I / 255.0f, 1.2f) * 255.0f, 0, 255));
// Augment the input with a boundary condition.
Padded[X, Y, C] = Input[HS.Clamp(X, 0, Input.Width - 1),
HS.Clamp(Y, 0, Input.Height - 1), C];
// Cast it to 16-bit to do the math.
Padded16[X, Y, C] = HS.Cast <ushort>(Padded[X, Y, C]);
// Next we sharpen it with a five-tap filter.
Sharpen[X, Y, C] = (Padded16[X, Y, C] * 2 -
(Padded16[X - 1, Y, C] +
Padded16[X, Y - 1, C] +
Padded16[X + 1, Y, C] +
Padded16[X, Y + 1, C]) / 4);
// Then apply the LUT.
Curved[X, Y, C] = Lut[Sharpen[X, Y, C]];
}
public static int Main(string[] args)
{
// First we'll declare some Vars to use below.
var x = new HSVar("x");
var y = new HSVar("y");
var c = new HSVar("c");
// Now we'll express a multi-stage pipeline that blurs an image
// first horizontally, and then vertically.
{
// Take a color 8-bit input
var input = HSBuffer <byte> .LoadImage("rgb.png");
// Upgrade it to 16-bit, so we can do math without it overflowing.
var input_16 = new HSFunc("input_16");
input_16[x, y, c] = HS.Cast <ushort>(input[x, y, c]);
// Blur it horizontally:
var blur_x = new HSFunc("blur_x");
blur_x[x, y, c] = (input_16[x - 1, y, c] +
2 * input_16[x, y, c] +
input_16[x + 1, y, c]) / 4;
// Blur it vertically:
var blur_y = new HSFunc("blur_y");
blur_y[x, y, c] = (blur_x[x, y - 1, c] +
2 * blur_x[x, y, c] +
blur_x[x, y + 1, c]) / 4;
// Convert back to 8-bit.
var output = new HSFunc("output");
output[x, y, c] = HS.Cast <byte>(blur_y[x, y, c]);
// Each Func in this pipeline calls a previous one using
// familiar function call syntax (we've overloaded operator()
// on Func objects). A Func may call any other Func that has
// been given a definition. This restriction prevents
// pipelines with loops in them. Halide pipelines are always
// feed-forward graphs of Funcs.
// Now let's realize it...
// Buffer<byte> result = output.realize(input.width(), input.height(), 3);
// Except that the line above is not going to work. Uncomment
// it to see what happens.
// Realizing this pipeline over the same domain as the input
// image requires reading pixels out of bounds in the input,
// because the blur_x stage reaches outwards horizontally, and
// the blur_y stage reaches outwards vertically. Halide
// detects this by injecting a piece of code at the top of the
// pipeline that computes the region over which the input will
// be read. When it starts to run the pipeline it first runs
// this code, determines that the input will be read out of
// bounds, and refuses to continue. No actual bounds checks
// occur in the inner loop; that would be slow.
//
// So what do we do? There are a few options. If we realize
// over a domain shifted inwards by one pixel, we won't be
// asking the Halide routine to read out of bounds. We saw how
// to do this in the previous lesson:
var result = new HSBuffer <byte>(input.Width - 2, input.Height - 2, 3);
result.SetMin(1, 1);
output.Realize(result);
// Save the result. It should look like a slightly blurry
// parrot, and it should be two pixels narrower and two pixels
// shorter than the input image.
result.SaveImage("blurry_parrot_1.png");
// This is usually the fastest way to deal with boundaries:
// don't write code that reads out of bounds :) The more
// general solution is our next example.
}
// The same pipeline, with a boundary condition on the input.
{
// Take a color 8-bit input
var input = HSBuffer <byte> .LoadImage("rgb.png");
// This time, we'll wrap the input in a Func that prevents
// reading out of bounds:
var clamped = new HSFunc("clamped");
// Define an expression that clamps x to lie within the
// range [0, input.width()-1].
var clamped_x = HS.Clamp(x, 0, input.Width - 1);
// clamp(x, a, b) is equivalent to max(min(x, b), a).
// Similarly clamp y.
var clamped_y = HS.Clamp(y, 0, input.Height - 1);
// Load from input at the clamped coordinates. This means that
// no matter how we evaluated the Func 'clamped', we'll never
// read out of bounds on the input. This is a clamp-to-edge
// style boundary condition, and is the simplest boundary
// condition to express in Halide.
clamped[x, y, c] = input[clamped_x, clamped_y, c];
// Defining 'clamped' in that way can be done more concisely
// using a helper function from the BoundaryConditions
// namespace like so:
//
// clamped = BoundaryConditions::repeat_edge(input);
//
// These are important to use for other boundary conditions,
// because they are expressed in the way that Halide can best
// understand and optimize. When used correctly they are as
// cheap as having no boundary condition at all.
// Upgrade it to 16-bit, so we can do math without it
// overflowing. This time we'll refer to our new Func
// 'clamped', instead of referring to the input image
// directly.
var input_16 = new HSFunc("input_16");
input_16[x, y, c] = HS.Cast <ushort>(clamped[x, y, c]);
// The rest of the pipeline will be the same...
// Blur it horizontally:
var blur_x = new HSFunc("blur_x");
blur_x[x, y, c] = (input_16[x - 1, y, c] +
2 * input_16[x, y, c] +
input_16[x + 1, y, c]) / 4;
// Blur it vertically:
var blur_y = new HSFunc("blur_y");
blur_y[x, y, c] = (blur_x[x, y - 1, c] +
2 * blur_x[x, y, c] +
blur_x[x, y + 1, c]) / 4;
// Convert back to 8-bit.
var output = new HSFunc("output");
output[x, y, c] = HS.Cast <byte>(blur_y[x, y, c]);
// This time it's safe to evaluate the output over the some
// domain as the input, because we have a boundary condition.
var result = output.Realize <byte>(input.Width, input.Height, 3);
// Save the result. It should look like a slightly blurry
// parrot, but this time it will be the same size as the
// input.
result.SaveImage("blurry_parrot_2.png");
}
Console.WriteLine("Success!");
return(0);
}