Halide
tutorial/lesson_07_multi_stage_pipelines.cpp
// Halide tutorial lesson 7: Multi-stage pipelines
// On linux, you can compile and run it like so:
// g++ lesson_07*.cpp -g -std=c++11 -I ../include -I ../tools -L ../bin -lHalide `libpng-config --cflags --ldflags` -ljpeg -lpthread -ldl -o lesson_07
// LD_LIBRARY_PATH=../bin ./lesson_07
// On os x:
// g++ lesson_07*.cpp -g -std=c++11 -I ../include -I ../tools -L ../bin -lHalide `libpng-config --cflags --ldflags` -ljpeg -o lesson_07
// DYLD_LIBRARY_PATH=../bin ./lesson_07
// If you have the entire Halide source tree, you can also build it by
// running:
// make tutorial_lesson_07_multi_stage_pipelines
// in a shell with the current directory at the top of the halide
// source tree.
#include "Halide.h"
#include <stdio.h>
using namespace Halide;
// Support code for loading pngs.
#include "halide_image_io.h"
using namespace Halide::Tools;
int main(int argc, char **argv) {
// First we'll declare some Vars to use below.
Var x("x"), y("y"), c("c");
// Now we'll express a multi-stage pipeline that blurs an image
// first horizontally, and then vertically.
{
// Take a color 8-bit input
Buffer<uint8_t> input = load_image("images/rgb.png");
// Upgrade it to 16-bit, so we can do math without it overflowing.
Func input_16("input_16");
input_16(x, y, c) = cast<uint16_t>(input(x, y, c));
// Blur it horizontally:
Func blur_x("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:
Func blur_y("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.
Func output("output");
output(x, y, c) = cast<uint8_t>(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<uint8_t> 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:
Buffer<uint8_t> result(input.width()-2, input.height()-2, 3);
result.set_min(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.
save_image(result, "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
Buffer<uint8_t> input = load_image("images/rgb.png");
// This time, we'll wrap the input in a Func that prevents
// reading out of bounds:
Func clamped("clamped");
// Define an expression that clamps x to lie within the
// range [0, input.width()-1].
Expr clamped_x = clamp(x, 0, input.width()-1);
// clamp(x, a, b) is equivalent to max(min(x, b), a).
// Similarly clamp y.
Expr clamped_y = 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.
Func input_16("input_16");
input_16(x, y, c) = cast<uint16_t>(clamped(x, y, c));
// The rest of the pipeline will be the same...
// Blur it horizontally:
Func blur_x("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:
Func blur_y("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.
Func output("output");
output(x, y, c) = cast<uint8_t>(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.
Buffer<uint8_t> result = output.realize(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.
save_image(result, "blurry_parrot_2.png");
}
printf("Success!\n");
return 0;
}