fun_mPb_theta.cpp
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#include <stim/image/image.h>
#include <cmath>
#include <conio.h>
#include <stim/visualization/colormap.h>
#include <stim/image/image_contour_detection.h>
void array_multiply(float* lhs, float rhs, unsigned int N);
void array_add(float* ptr1, float* ptr2, float* sum, unsigned int N);
stim::image<float> func_mPb_theta(stim::image<float> lab, float theta, unsigned int w, unsigned int h){
stim::image<float> mPb_theta(w, h, 1);
stim::image<float> pic_light, pic_colora, pic_colorb;
pic_light = lab.channel(0);
pic_colora = lab.channel(1);
pic_colorb = lab.channel(2);
unsigned int N = w * h;
float sigma = 2;
unsigned int sigma_n = 3;
unsigned r1 = 3;
unsigned r2 = 5;
unsigned r3 = 10;
unsigned r4 = 20;
float alpha[9] = {1,1,1,1,1,1,1,1,1};
stim::image<float> l1,l2,l3,a1,a2,a3,b1,b2,b3;
l1 = gaussian_derivative_filter_odd(pic_light, sigma, sigma_n, r1 * 2, theta, w, h);
stim::cpu2image(l1.data(), "data_output/l1_tex.bmp", w, h, stim::cmBrewer);
l2 = gaussian_derivative_filter_odd(pic_light, sigma, sigma_n, r2 * 2, theta, w, h);
stim::cpu2image(l2.data(), "data_output/l2_tex.bmp", w, h, stim::cmBrewer);
l3 = gaussian_derivative_filter_odd(pic_light, sigma, sigma_n, r3 * 2, theta, w, h);
stim::cpu2image(l3.data(), "data_output/l3_tex.bmp", w, h, stim::cmBrewer);
a1 = gaussian_derivative_filter_odd(pic_colora, sigma, sigma_n, r2 * 2, theta, w, h);
stim::cpu2image(a1.data(), "data_output/a1_tex.bmp", w, h, stim::cmBrewer);
a2 = gaussian_derivative_filter_odd(pic_colora, sigma, sigma_n, r3 * 2, theta, w, h);
stim::cpu2image(a2.data(), "data_output/a2_tex.bmp", w, h, stim::cmBrewer);
a3 = gaussian_derivative_filter_odd(pic_colora, sigma, sigma_n, r4 * 2, theta, w, h);
stim::cpu2image(a3.data(), "data_output/a3_tex.bmp", w, h, stim::cmBrewer);
b1 = gaussian_derivative_filter_odd(pic_colorb, sigma, sigma_n, r2 * 2, theta, w, h);
stim::cpu2image(b1.data(), "data_output/b1_tex.bmp", w, h, stim::cmBrewer);
b2 = gaussian_derivative_filter_odd(pic_colorb, sigma, sigma_n, r3 * 2, theta, w, h);
stim::cpu2image(b2.data(), "data_output/b2_tex.bmp", w, h, stim::cmBrewer);
b3 = gaussian_derivative_filter_odd(pic_colorb, sigma, sigma_n, r4 * 2, theta, w, h);
stim::cpu2image(b3.data(), "data_output/b3_tex.bmp", w, h, stim::cmBrewer);
/*for (unsigned i = 0; i<N; i++){
mPb_theta.data()[i] = l1.data()[i] * alpha[0] +
l2.data()[i] * alpha[1] +
l3.data()[i] * alpha[2] +
a1.data()[i] * alpha[3] +
a2.data()[i] * alpha[4] +
a3.data()[i] * alpha[5] +
b1.data()[i] * alpha[6] +
b2.data()[i] * alpha[7] +
b3.data()[i] * alpha[8] ;
}*/
array_multiply(l1.data(), alpha[0], N);
//stim::cpu2image(l1.data(), "data_output/array_add_l1.bmp", w, h, stim::cmBrewer);
array_multiply(l2.data(), alpha[1], N);
//stim::cpu2image(l2.data(), "data_output/array_add_l2.bmp", w, h, stim::cmBrewer);
array_multiply(l3.data(), alpha[2], N);
array_multiply(a1.data(), alpha[3], N);
array_multiply(a2.data(), alpha[4], N);
array_multiply(a3.data(), alpha[5], N);
array_multiply(b1.data(), alpha[6], N);
array_multiply(b2.data(), alpha[7], N);
array_multiply(b3.data(), alpha[8], N);
array_add(l1.data(), l2.data(), mPb_theta.data(), N);
//stim::cpu2image(sum, "data_output/array_add_sum.bmp", w, h, stim::cmBrewer);
array_add(mPb_theta.data(), l3.data(), mPb_theta.data(), N);
array_add(mPb_theta.data(), a1.data(), mPb_theta.data(), N);
array_add(mPb_theta.data(), a2.data(), mPb_theta.data(), N);
array_add(mPb_theta.data(), a3.data(), mPb_theta.data(), N);
array_add(mPb_theta.data(), b1.data(), mPb_theta.data(), N);
array_add(mPb_theta.data(), b2.data(), mPb_theta.data(), N);
array_add(mPb_theta.data(), b3.data(), mPb_theta.data(), N);
//stim::cpu2image(mPb_theta.data(), "data_output/mPb_theta0_1.bmp", w, h, stim::cmBrewer);
//getch();
return mPb_theta;
}