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mainSift.cpp
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mainSift.cpp
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/***********************************************************************/
// CUDA SIFT extractor by Marten Björkman aka Celebrandil //
// celle @ csc.kth.se //
// Added features : //
// 1-Cropping //
// 2-Limiting the memory allocation //
// for only 4GB per image //
// for the purposes of MPS //
// 2 GPUs (P100 of 16 GB per GPU) //
// By Aymen Alsaadi //
// [email protected] //
//***********************************************************//
#include <iostream>
#include <cmath>
#include <iomanip>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <fstream>
#include "cudaImage.h"
#include "cudaSift.h"
#include <vector>
#include <stdlib.h> // for strtol
#include <string>
using std::string;
int ImproveHomography(SiftData &data, float *homography, int numLoops, float minScore, float maxAmbiguity, float thresh);
void PrintMatchData(SiftData &siftData1, SiftData &siftData2, CudaImage &img, const string& s, const string& s2);
void MatchAll(SiftData &siftData1, SiftData &siftData2, float *homography);
double ScaleUp(CudaImage &res, CudaImage &src);
int main(int argc, char **argv)
{
int devNum = 2, imgSet = 0;
if( argc != 11)
{
std::cout <<"Usage :";
std::cout <<"./cudaSift img1 x1 y1 x2 y2 img2 x1 y1 x2 y2 " << std::endl;
std::cout <<" img1 : The source image to be matched! " << std::endl;
std::cout <<" img2 : The target image to be matched! " << std::endl;
std::cout <<" x1,y1,x2,y2 are the coordinates of the tile! " << std::endl;
return -1;
}
cv::Mat src_limg, trg_rimg;
cv::imread(argv[1], 0).convertTo(src_limg, CV_32FC1);
cv::imread(argv[6], 0).convertTo(trg_rimg, CV_32FC1);
//check for valid GEOTIFF input
if(! src_limg.data || ! trg_rimg.data)
{
std::cout << "Could not open or find the image" << std::endl ;
return -1;
}
else
{
std::cout << "GEOTIFF image1 detected " <<argv[1]<<std::endl;
std::cout << "GEOTIFF image2 detected " <<argv[6]<<std::endl;
}
//Tiling Method @aymenalsaadi :)
int src_x1= strtol(argv[2],NULL, 10);
int src_y1= strtol(argv[3],NULL, 10);
int src_x2= strtol(argv[4],NULL, 10);
int src_y2= strtol(argv[5],NULL, 10);
int trg_x1= strtol(argv[7],NULL, 10);
int trg_y1= strtol(argv[8],NULL, 10);
int trg_x2= strtol(argv[9],NULL, 10);
int trg_y2= strtol(argv[10],NULL,10);
/*
if (((src_x1 > src_limg.cols) || (src_y1 > src_limg.rows)) && ((src_x2 > src_limg.cols) ||(src_y2 > src_limg.rows)))
{
std::cout << "Requested tile size is bigger than the original source image size" << std::endl ;
return -1;
}
else if (((trg_x1 > trg_rimg.cols) || (trg_y1 > trg_rimg.rows)) && ((trg_y2 > trg_rimg.cols) ||(trg_y2 > trg_rimg.rows)))
{
std::cout << "Requested tile size is bigger than the original target image size" << std::endl ;
return -1;
}
*/
cv::Mat limg = cv::Mat(src_limg, cv::Rect(src_x1,src_y1,src_x2,src_y2));
cv::Mat rimg = cv::Mat(trg_rimg, cv::Rect(trg_x1,trg_y1,trg_x2,trg_y2));
//cv::gpu::GpuMat gm; //I have used opencv GPU and it is only working on my local system
//gm.upload(src_limg); // So i stopped it for now
//gm.upload(trg_rimg);
//cv::gpu::GpuMat rimg= trg_rimg;
//cv::gpu::GpuMat.upload(limg);
//cv::gpu::GpuMat.upload(rimg);
unsigned int w = limg.cols;
unsigned int h = limg.rows;
unsigned int w2 = rimg.cols;
unsigned int h2 = rimg.rows;
std::string command1 ,command2;
std::string cmd,cmd2="gdalinifo ";
std::cout << "gdal source image 1 inforamtion " <<system(cmd.c_str())<<std::endl;
std::cout << "Source image size = (" << w << "," << h << ")" << std::endl;
std::cout << "Target image size = (" << w2 << "," << h2 << ")" << std::endl;
//This funcion will use adaptive threshold instead for giving a static value // Some libraries are failing to load
//
//
// //cv::Mat dst2,dst1,limg2,rimg2;
// //limg2=cv::imread(argv[1],CV_LOAD_IMAGE_GRAYSCALE);
// //cv::adaptiveThreshold(limg2, dst1, 200,cv::ADAPTIVE_THRESH_GAUSSIAN_C , cv::THRESH_BINARY, 65, 0);
// //cv::imwrite("/home/aymen/SummerRadical/GPU-SIFT/dst1.jpg", dst1);
// //rimg2=cv::imread(argv[2],CV_LOAD_IMAGE_GRAYSCALE);
// //cv::adaptiveThreshold(rimg2, dst2, 200, cv::ADAPTIVE_THRESH_GAUSSIAN_C, cv::THRESH_BINARY, 65, 0);
// //cv::imwrite("~/GPU-SIFT/dst2.jpg", dst2);
// //*************************************************************************************************************//
// Initial Cuda images and download images to device
std::cout << "Initializing data..." << std::endl;
InitCuda(devNum);
CudaImage img1, img2;
img1.Allocate(w, h, iAlignUp(w, 128), false, NULL, (float*)limg.data);
img2.Allocate(w, h, iAlignUp(w, 128), false, NULL, (float*)rimg.data);
img1.Download();
img2.Download();
// Extract Sift features from images
SiftData siftData1, siftData2;
float initBlur = 0.3f;
float thresh = (imgSet ? 4.5f : 3.0f);
std::cout<<"Threshold value :"<<thresh<<std::endl;
InitSiftData(siftData1, 132768, true, true); //before it was 100,000
InitSiftData(siftData2, 132768, true, true); //before it was 100,000
system("nvidia-smi");
// A bit of benchmarking
//for (int thresh1=1.00f;thresh1<=4.01f;thresh1+=0.50f) {
float *memoryTmp = AllocSiftTempMemory(w, h, 5, false);
for (int i=0;i<1000;i++) {
ExtractSift(siftData1, img1, 3, initBlur, thresh, 0.0f, false, memoryTmp);
ExtractSift(siftData2, img2, 3, initBlur, thresh, 0.0f, false, memoryTmp);
}
FreeSiftTempMemory(memoryTmp);
// Match Sift features and find a homography
for (int i=0;i<1;i++)
MatchSiftData(siftData1, siftData2);
float homography[9];
int numMatches;
FindHomography(siftData1, homography, &numMatches, 10000, 0.0f, 0.80f, 5.0);
int numFit = ImproveHomography(siftData1, homography, 5, 0.0f, 0.80f, 3.0);
std::cout << "Number features detected by SIFT descriptors : " <<"Source Image "<< siftData1.numPts << ", Target Image " << siftData2.numPts << std::endl;
std::cout << "Number of Matched features: " << numMatches <<std::endl;
std::cout << "Number of fitted features after applying ImproveHomography : " << numFit <<std::endl;
std::cout << 100.0f*numFit/std::min(siftData1.numPts, siftData2.numPts) << "% " <<std::endl;
//}
// Print out and store summary data
string ss1 = (argv[1]);
string ss2 = (argv[6]);
std::cout<<ss1;
char sep = '/';
size_t i = ss1.rfind(sep, ss1.length());
size_t i2 = ss2.rfind(sep, ss2.length());
if (i != string::npos && i2 != string::npos)
{
string filename = ss1.substr(i+1, ss1.length() - i);
string filename2 = ss2.substr(i2+1, ss2.length() - i2);
size_t lastindex = filename.find_last_of(".");
size_t lastindex2 = filename2.find_last_of(".");
string rawname = filename.substr(0, lastindex);
string rawname2 = filename2.substr(0, lastindex2);
PrintMatchData(siftData1, siftData2, img1, rawname, rawname2);
}
//PrintMatchData(siftData1, siftData2, img1, ss1);
//PrintMatchData(siftData1, siftData2, img2);
cv::imwrite("/home/aymen/SummerRadical/SIFT-GPU/source_output.pgm", limg);
std::cout<< "img1 saved"<<std::endl;
cv::imwrite("/home/aymen/SummerRadical/SIFT-GPU/target_output.pgm", rimg);
std::cout<< "img2 saved"<<std::endl;
std::cout << "Output Images are saved in the same directory !) "<<std::endl;
//MatchAll(siftData1, siftData2, homography);
// Free Sift data from device
FreeSiftData(siftData1);
FreeSiftData(siftData2);
}
void MatchAll(SiftData &siftData1, SiftData &siftData2, float *homography)
{
#ifdef MANAGEDMEM
SiftPoint *sift1 = siftData1.m_data;
SiftPoint *sift2 = siftData2.m_data;
#else
SiftPoint *sift1 = siftData1.h_data;
SiftPoint *sift2 = siftData2.h_data;
#endif
int numPts1 = siftData1.numPts;
int numPts2 = siftData2.numPts;
int numFound = 0;
#if 1
homography[0] = homography[4] = -1.0f;
homography[1] = homography[3] = homography[6] = homography[7] = 0.0f;
homography[2] = 1279.0f;
homography[5] = 959.0f;
#endif
for (int i=0;i<numPts1;i++) {
float *data1 = sift1[i].data;
std::cout << i << ":" << sift1[i].scale << ":" << (int)sift1[i].orientation << " " << sift1[i].xpos << " " << sift1[i].ypos << std::endl;
bool found = false;
for (int j=0;j<numPts2;j++) {
float *data2 = sift2[j].data;
float sum = 0.0f;
for (int k=0;k<128;k++)
sum += data1[k]*data2[k];
float den = homography[6]*sift1[i].xpos + homography[7]*sift1[i].ypos + homography[8];
float dx = (homography[0]*sift1[i].xpos + homography[1]*sift1[i].ypos + homography[2]) / den - sift2[j].xpos;
float dy = (homography[3]*sift1[i].xpos + homography[4]*sift1[i].ypos + homography[5]) / den - sift2[j].ypos;
float err = dx*dx + dy*dy;
if (err<100.0f) // 100.0
found = true;
if (err<100.0f || j==sift1[i].match) { // 100.0
if (j==sift1[i].match && err<100.0f)
std::cout << " *";
else if (j==sift1[i].match)
std::cout << " -";
else if (err<100.0f)
std::cout << " +";
else
std::cout << " ";
std::cout << j << ":" << sum << ":" << (int)sqrt(err) << ":" << sift2[j].scale << ":" << (int)sift2[j].orientation << " " << sift2[j].xpos << " " << sift2[j].ypos << " " << (int)dx << " " << (int)dy << std::endl;
}
}
std::cout << std::endl;
if (found)
numFound++;
}
std::cout << "Number of finds: " << numFound << " / " << numPts1 << std::endl;
std::cout << homography[0] << " " << homography[1] << " " << homography[2] << std::endl;//%%%
std::cout << homography[3] << " " << homography[4] << " " << homography[5] << std::endl;//%%%
std::cout << homography[6] << " " << homography[7] << " " << homography[8] << std::endl;//%%%
}
void PrintMatchData(SiftData &siftData1, SiftData &siftData2, CudaImage &img, const string& s, const string& s2)
{
//@aymenalsaadi creating a csv file to save the matched keypoints
std::ofstream myfile;
string ss1 = s;
string ss2 = s2;
string ff = string("/pylon5/mc3bggp/aymen/cuda_out/sift_matches_")+ss1+string("_")+ss2+string(".csv");
const char * c = ff.c_str();
myfile.open(c, std::ofstream::out | std::ofstream::trunc);
myfile<<"x1, y1, sigma1, angle1, t1_x, t1_y, theta1, x2, y2, sigma2, angle2, t2_x, t2_y, theta2"<<std::endl;
int numPts = siftData1.numPts;
#ifdef MANAGEDMEM
SiftPoint *sift1 = siftData1.m_data;
SiftPoint *sift2 = siftData2.m_data;
#else
SiftPoint *sift1 = siftData1.h_data;
SiftPoint *sift2 = siftData2.h_data;
#endif
float *h_img = img.h_data;
int w = img.width;
int h = img.height;
std::cout << std::setprecision(3);
for (int j=0;j<numPts;j++) {
int k = sift1[j].match;
if (sift1[j].match_error<5) {
float dx = sift2[k].xpos - sift1[j].xpos;
float dy = sift2[k].ypos - sift1[j].ypos;
#if 0
if (false && sift1[j].xpos>550 && sift1[j].xpos<600) {
std::cout << "pos1=(" << (int)sift1[j].xpos << "," << (int)sift1[j].ypos << ") ";
std::cout << j << ": " << "score=" << sift1[j].score << " ambiguity=" << sift1[j].ambiguity << " match=" << k << " ";
std::cout << "scale=" << sift1[j].scale << " ";
std::cout << "error=" << (int)sift1[j].match_error << " ";
std::cout << "orient=" << (int)sift1[j].orientation << "," << (int)sift2[k].orientation << " ";
std::cout << " delta=(" << (int)dx << "," << (int)dy << ")" << std::endl;
}
#endif
#if 1
int len = (int)(fabs(dx)>fabs(dy) ? fabs(dx) : fabs(dy));
for (int l=0;l<len;l++) {
int x = (int)(sift1[j].xpos + dx*l/len);
int y = (int)(sift1[j].ypos + dy*l/len);
h_img[y*w+x] = 255.0f;
}
#endif
}
int x = (int)(sift1[j].xpos+0.5);
int y = (int)(sift1[j].ypos+0.5);
int x2 = (int)(sift2[j].xpos+0.5);
int y2 = (int)(sift2[j].ypos+0.5);
int s = std::min(x, std::min(y, std::min(w-x-2, std::min(h-y-2, (int)(1.41*sift1[j].scale)))));
int s2 = std::min(x, std::min(y, std::min(w-x-2, std::min(h-y-2, (int)(1.41*sift2[j].scale)))));
int p = y*w + x;
int p2 = y2*w + x2;
myfile<<(x)<<","<<(y)<<","<<(s)<<","<<(s2)<<","<<(p)<<","<<(p2)<<","<<(x2)<<","<<(y2)<<","<<(s)<<","<<(s2)<<","<<(p)<<","<<(p2)<<","<<(s)<<","<<(p)<<std::endl;
p += (w+1);
for (int k=0;k<s;k++)
h_img[p-k] = h_img[p+k] = h_img[p-k*w] = h_img[p+k*w] = 0.0f;
p -= (w+1);
for (int k=0;k<s;k++)
h_img[p-k] = h_img[p+k] = h_img[p-k*w] =h_img[p+k*w] = 255.0f;
}
std::cout << std::setprecision(6);
}