A high-performance general-purpose compute library

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image_processing/brain_segmentation.cpp
/*******************************************************
* Copyright (c) 2014, ArrayFire
* All rights reserved.
*
* This file is distributed under 3-clause BSD license.
* The complete license agreement can be obtained at:
* http://arrayfire.com/licenses/BSD-3-Clause
********************************************************/
#include <arrayfire.h>
#include <math.h>
#include <stdio.h>
#include <string.h>
#include "../common/progress.h"
using namespace af;
const float h_sx_kernel[] = {1, 2, 1, 0, 0, 0, -1, -2, -1};
const float h_sy_kernel[] = {-1, 0, 1, -2, 0, 2, -1, 0, 1};
// Unused
// const float h_lp_kernel[] = { -0.5f, -1.0f, -0.5f,
// -1.0f, 6.0f, -1.0f,
// -0.5f, -1.0f, -0.5f
//};
array edges_slice(array x) {
array ret;
static array kernelx = array(dim4(3, 3), h_sx_kernel);
static array kernely = array(dim4(3, 3), h_sy_kernel);
ret = convolve(x, kernelx) + convolve(x, kernely);
return abs(ret);
}
array gauss(array x, float u, float s) {
double f = 1 / sqrt(2 * af::Pi * s * s);
array e = exp(-pow((x - u), 2) / (2 * s * s));
return f * e;
}
array segment_volume(array A, int k) {
array I1 = A(span, span, k);
float mx = max<float>(I1);
float mn = min<float>(I1);
float u0 = 0.9 * mx;
float s0 = (mx - mn) / 2;
float u1 = 1.1 * mn;
float s1 = (mx - mn) / 2;
array L0 = gauss(I1, u0, s0);
array L11 = gauss(I1, u1, s1);
array L10;
array L12;
static array kernel = constant(1, 3, 3) / 9;
static array L11_old;
static array L12_old;
if (k == 0) {
L11 = convolve(L11, kernel);
L10 = L11;
} else {
L10 = L11_old;
L11 = L12_old;
}
if (k < A.dims(2) - 1) {
L12 = gauss(A(span, span, k + 1), u1, s1);
L12 = convolve(L12, kernel);
} else {
L12 = L11;
}
L11_old = L11;
L12_old = L12;
array L1 = (L10 + L11 + L12) / 3;
array S = (L0 > L1);
return S.as(A.type());
}
void brain_seg(bool console) {
af::Window wnd("Brain Segmentation Demo");
wnd.setColorMap(AF_COLORMAP_HEAT);
double time_total = 30; // run for N seconds
array B = loadImage(ASSETS_DIR "/examples/images/brain.png");
int slices = 256;
B = moddims(B, dim4(B.dims(0), B.dims(1) / slices, slices));
af::sync();
int N = 2 * slices - 1;
timer t = timer::start();
int iter = 0;
/* loop forward and backward for 100 frames
* exit if the user presses escape or the animation
* ends
*/
for (int i = 0; !wnd.close(); i++) {
iter++;
int j = i % N;
int k = std::min(j, N - j);
array Bi = B(span, span, k);
/* process */
array Si = segment_volume(B, k);
array Ei = edges_slice(Si);
array Mi = meanShift(Bi, 10, 10, 5);
/* visualization */
if (!console) {
wnd.grid(2, 2);
wnd(0, 0).image(Bi / 255.f, "Input");
wnd(1, 0).image(Ei, "Edges");
wnd(0, 1).image(Mi / 255.f, "Meanshift");
wnd(1, 1).image(Si, "Segmented");
wnd.show();
} else {
/* sync the operations so that current
* iteration comptation finishes
* */
af::sync();
}
/* we have had ran throuh simlation results
* exit the rendering loop */
if (!progress(iter, t, time_total)) break;
if (!(i < 100 * N)) break;
}
}
int main(int argc, char* argv[]) {
int device = argc > 1 ? atoi(argv[1]) : 0;
bool console = argc > 2 ? argv[2][0] == '-' : false;
try {
af::setDevice(device);
af::info();
printf("Brain segmentation example\n");
brain_seg(console);
} catch (af::exception& e) { fprintf(stderr, "%s\n", e.what()); }
return 0;
}
arrayfire.h
af::Window
Window object to render af::arrays.
Definition graphics.h:37
af::array
A multi dimensional data container.
Definition array.h:37
af::array::dims
dim4 dims() const
Get dimensions of the array.
af::array::type
dtype type() const
Get array data type.
af::array::as
const array as(dtype type) const
Casts the array into another data type.
af::dim4
Generic object that represents size and shape.
Definition dim4.hpp:26
af::exception
An ArrayFire exception class.
Definition exception.h:22
af::exception::what
virtual const char * what() const
Returns an error message for the exception in a string format.
Definition exception.h:46
AF_COLORMAP_HEAT
@ AF_COLORMAP_HEAT
Heat map.
Definition defines.h:460
af::abs
array abs(const array &in)
C++ Interface to calculate the absolute value.
af::exp
array exp(const array &in)
C++ Interface to evaluate the exponential.
af::pow
array pow(const array &base, const array &exponent)
C++ Interface to raise a base to a power (or exponent).
af::sqrt
array sqrt(const array &in)
C++ Interface to evaluate the square root.
af::constant
array constant(T val, const dim4 &dims, const dtype ty=(af_dtype) dtype_traits< T >::ctype)
C++ Interface to generate an array with elements set to a specified value.
af::info
AFAPI void info()
af::setDevice
AFAPI void setDevice(const int device)
Sets the current device.
af::sync
AFAPI void sync(const int device=-1)
Blocks until the device is finished processing.
af::meanShift
AFAPI array meanShift(const array &in, const float spatial_sigma, const float chromatic_sigma, const unsigned iter, const bool is_color=false)
C++ Interface for mean shift.
af::loadImage
AFAPI array loadImage(const char *filename, const bool is_color=false)
C++ Interface for loading an image.
af::moddims
AFAPI array moddims(const array &in, const dim4 &dims)
C++ Interface to modify the dimensions of an input array to a specified shape.
af::convolve
AFAPI array convolve(const array &signal, const array &filter, const convMode mode=AF_CONV_DEFAULT, const convDomain domain=AF_CONV_AUTO)
C++ Interface for convolution any(one through three) dimensional signals.
af
Definition algorithm.h:15
af::Pi
AFAPI const double Pi
af::timer
Internal timer object.
Definition timing.h:29