91d8912e
 David Mayerich
moved bsds500 fil...
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#include <stim/image/image.h>
#include <cmath>
#include <stim/visualization/colormap.h>
#include <stim/image/image_contour_detection.h>
#include <sstream>
void array_multiply(float* lhs, float rhs, unsigned int N);
void array_add(float* ptr1, float* ptr2, float* sum, unsigned int N);
/// This function evaluates the cPb given an multi-channel image
/// @param img is the multi-channel image
/// @param r is an array of radii for different scaled discs(filters)
/// @param alpha is is an array of weights for different scaled discs(filters)
/// @param s is the number of scales
stim::image<float> cPb(stim::image<float> img, int* r, float* alpha, int s){
unsigned int w = img.width(); // get the width of picture
unsigned int h = img.height(); // get the height of picture
unsigned int c = img.channels(); // get the channels of picture
stim::image<float> cPb(w, h, 1); // allocate space for cPb
unsigned size = cPb.size(); // get the size of cPb
memset ( cPb.data(), 0, size * sizeof(float)); // initialize all the pixels of cPb to 0
unsigned int N = w * h; // get the number of pixels
int sigma_n = 3; // set the number of standard deviations used to define the sigma
std::ostringstream ss; // (optional) set the stream to designate the test result file
stim::image<float> temp; // set the temporary image to store the addtion result
for (int i = 0; i < c; i++){
for (int j = 0; j < s; j++){
ss << "data_output/cPb_slice"<< i*s + j << ".bmp"; // set the name for test result file (optional)
std::string sss = ss.str();
// get the gaussian gradient by convolving each image slice with the mask
temp = Pb(img.channel(i), r[i*s + j], sigma_n);
// output the test result of each slice (optional)
//stim::cpu2image(temp.data(), sss, w, h, stim::cmBrewer);
// multiply each gaussian gradient with its weight
array_multiply(temp.data(), alpha[i*s + j], N);
// add up all the weighted gaussian gradients
array_add(cPb.data(), temp.data(), cPb.data(), N);
ss.str(""); //(optional) clear the space for stream
}
}
float max = cPb.maxv(); // get the maximum of cPb used for normalization
array_multiply(cPb.data(), 1/max, N); // normalize the cPb
// output the test result of cPb (optional)
//stim::cpu2image(cPb.data(), "data_output/cPb_0916.bmp", w, h, stim::cmBrewer);
return cPb;
}
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