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BilateralSolver.cpp
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BilateralSolver.cpp
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#include <Eigen/Dense>
#include <Eigen/SparseCore>
#include <Eigen/SparseCholesky>
#include <Eigen/IterativeLinearSolvers>
#include <Eigen/Sparse>
#include<opencv2/core/core.hpp>
#include<opencv2/core/eigen.hpp>
#include<opencv2/highgui.hpp>
#include<opencv2/opencv.hpp>
#include <set>
#include <cmath>
#include <math.h>
#include <time.h>
#include <chrono>
#include <vector>
#include <memory>
#include <stdio.h>
#include <stdlib.h>
#include <string>
#include <sstream>
#include <iostream>
#include <iterator>
#include <algorithm>
#include <unordered_set>
#include <unordered_map>
#include <opencv2/ximgproc.hpp>
#include "BilateralSolver.hpp"
void process(cv::Mat reference,cv::Mat target,float spatialSigma = 8,float lumaSigma = 8,float chromaSigma = 8,float fgs_spatialSigma = 2000,float fgs_colorSigma = 1.5);
void int2str(const int &int_temp,std::string &string_temp);
int main(int argc, char const *argv[]) {
std::cout << "hello solver" << '\n';
cv::Mat reference = cv::imread(argv[1],1);
cv::Mat target = cv::imread(argv[2],0);
// cv::Mat confidence = cv::imread(argv[3],0);
float spatialSigma = float(atof(argv[4])); //8.0
float lumaSigma = float(atof(argv[5])); //8.0
float chromaSigma = float(atof(argv[6])); //8.0
float fgs_spatialSigma = float(atof(argv[7])); //2000
float fgs_colorSigma = float(atof(argv[8])); //1.5
std::string rgbd_file = argv[3];
// process(reference,target,spatialSigma,lumaSigma,chromaSigma,fgs_spatialSigma,fgs_colorSigma);
for (int i = 0; i < 10; i++) {
std::string idx;
int2str(i,idx);
std::string reference_file = rgbd_file + "/rgb00000" + idx +".png";
std::string target_file = rgbd_file + "/depth00000" + idx +".png";
std::cout << "depth :"<< target_file << '\n';
std::cout << "rgb :"<< reference_file << '\n';
cv::Mat reference = cv::imread(reference_file,1);
cv::Mat target = cv::imread(target_file,0);
process(reference,target,spatialSigma,lumaSigma,chromaSigma,fgs_spatialSigma,fgs_colorSigma);
}
for (int i = 10; i < 100; i++) {
std::string idx;
int2str(i,idx);
std::string reference_file = rgbd_file + "/rgb0000" + idx +".png";
std::string target_file = rgbd_file + "/depth0000" + idx +".png";
std::cout << "depth :"<< target_file << '\n';
std::cout << "rgb :"<< reference_file << '\n';
cv::Mat reference = cv::imread(reference_file,1);
cv::Mat target = cv::imread(target_file,0);
process(reference,target,spatialSigma,lumaSigma,chromaSigma,fgs_spatialSigma,fgs_colorSigma);
}
for (int i = 100; i < 950; i++) {
std::string idx;
int2str(i,idx);
std::string reference_file = rgbd_file + "/rgb000" + idx +".png";
std::string target_file = rgbd_file + "/depth000" + idx +".png";
std::cout << "depth :"<< target_file << '\n';
std::cout << "rgb :"<< reference_file << '\n';
cv::Mat reference = cv::imread(reference_file,1);
cv::Mat target = cv::imread(target_file,0);
process(reference,target,spatialSigma,lumaSigma,chromaSigma,fgs_spatialSigma,fgs_colorSigma);
}
return 0;
}
void process(cv::Mat reference,cv::Mat target,float spatialSigma,float lumaSigma,float chromaSigma,float fgs_spatialSigma,float fgs_colorSigma)
{
float filtering_time;
clock_t now;
now = clock();
printf( "start : now is %f seconds\n\n", (float)(now) / CLOCKS_PER_SEC);
cv::Mat confidence = 0*cv::Mat::ones(target.size(), CV_8UC1);
for(int i = 0; i < target.rows;i++)
{
for(int j = 0; j < target.cols;j++)
{
if(target.at<uchar>(i,j) != 0 && reference.at<cv::Vec3b>(i,j)[0] != 0) confidence.at<uchar>(i,j) = 255;
}
}
for(int i = 0; i < target.rows;i++)
{
for(int j = 0; j < target.cols;j++)
{
if(target.at<uchar>(i,j) != 0 && reference.at<cv::Vec3b>(i,j)[0] != 0) target.at<uchar>(i,j) = 255-target.at<uchar>(i,j);
}
}
filtering_time = (float)cv::getTickCount();
cv::equalizeHist(target, target);
#define ENABLE_FGS_FILTER
#ifdef ENABLE_FGS_FILTER
std::chrono::steady_clock::time_point start_fgs = std::chrono::steady_clock::now();
cv::Mat x;
cv::Mat w;
cv::Mat xw;
cv::Mat filtered_xw;
cv::Mat filtered_w;
cv::Mat filtered_disp;
target.convertTo(x, CV_32FC1, 1.0f/255.0f);
confidence.convertTo(w, CV_32FC1);
xw = x.mul(w);
cv::ximgproc::fastGlobalSmootherFilter(reference, xw, filtered_xw, fgs_spatialSigma, fgs_colorSigma);
cv::ximgproc::fastGlobalSmootherFilter(reference, w, filtered_w, fgs_spatialSigma, fgs_colorSigma);
cv::divide(filtered_xw, filtered_w, filtered_disp, 255.0f, CV_8UC1);
// cv::ximgproc::fastGlobalSmootherFilter(reference, target, filtered_disp, spatialSigma*spatialSigma, lumaSigma);
std::chrono::steady_clock::time_point end_fgs = std::chrono::steady_clock::now();
std::cout << "fastGlobalSmootherFilter time: " << std::chrono::duration_cast<std::chrono::milliseconds>(end_fgs - start_fgs).count() << "ms" << std::endl;
// cv::equalizeHist(filtered_disp, filtered_disp);
cv::imshow("fgs_filtered_disp",filtered_disp);
#endif //ENABLE_FGS_FILTER
// cvtColor(reference, reference, cv::COLOR_BGR2YUV);
std::cout << "reference:" << reference.cols<<"x"<< reference.rows<< std::endl;
std::chrono::steady_clock::time_point start_solver = std::chrono::steady_clock::now();
cv::Mat result;
// cv::ximgproc::fastBilateralSolverFilter(reference,filtered_disp,confidence,result,spatialSigma,lumaSigma,chromaSigma);
cv::ximgproc::fastBilateralSolverFilter(reference,target,confidence,result,spatialSigma,lumaSigma,chromaSigma,100);
std::chrono::steady_clock::time_point end_solver = std::chrono::steady_clock::now();
std::cout << "solver time: " << std::chrono::duration_cast<std::chrono::milliseconds>(end_solver - start_solver).count() << "ms" << std::endl;
cv::equalizeHist(result, result);
// cv::normalize(result,result,255,0,cv::NORM_MINMAX);
cv::imshow("input",reference);
cv::imshow("target",target);
cv::imshow("output",result);
// #define ENABLE_DOMAIN_TRANSFORM_FILTER
#ifdef ENABLE_DOMAIN_TRANSFORM_FILTER
const float property_dt_sigmaSpatial = 40.0f;
const float property_dt_sigmaColor = 220.0f;
const int property_dt_numIters = 3;
cv::Mat final_disparty_dtfiltered_image;
cv::ximgproc::dtFilter(reference,
// filtered_disp, final_disparty_dtfiltered_image,
result, final_disparty_dtfiltered_image,
property_dt_sigmaSpatial, property_dt_sigmaColor,
cv::ximgproc::DTF_RF,
property_dt_numIters);
// display disparity image
cv::Mat adjmap_dt;
final_disparty_dtfiltered_image.convertTo(adjmap_dt, CV_8UC1);
// 255.0f / 255.0f, 0.0f);
// cv::imwrite("output+df.png",adjmap_dt);
cv::imshow("disparity image + domain transform", adjmap_dt);
#endif
filtering_time = ((float)cv::getTickCount() - filtering_time)/cv::getTickFrequency();
std::cout<<"Filtering time: "<<filtering_time<<"s"<<std::endl;
cv::waitKey(1);
}
void int2str(const int &int_temp,std::string &string_temp)
{
std::stringstream stream;
stream<<int_temp;
string_temp=stream.str();
}