mirror of https://github.com/opencv/opencv.git
Vadim Pisarevsky
15 years ago
parent
b2244f87ac
commit
e1058f9a13
1 changed files with 684 additions and 0 deletions
@ -0,0 +1,684 @@ |
||||
#include <opencv2/core/core.hpp> |
||||
#include <opencv2/imgproc/imgproc.hpp> |
||||
#include <opencv2/calib3d/calib3d.hpp> |
||||
#include <opencv2/features2d/features2d.hpp> |
||||
#include <opencv2/highgui/highgui.hpp> |
||||
|
||||
#include <map> |
||||
|
||||
#include <ctype.h> |
||||
#include <stdio.h> |
||||
#include <stdlib.h> |
||||
|
||||
using namespace cv; |
||||
using namespace std; |
||||
|
||||
static bool readCameraMatrix(const string& filename, |
||||
Mat& cameraMatrix, Mat& distCoeffs, |
||||
Size& calibratedImageSize ) |
||||
{ |
||||
FileStorage fs(filename, FileStorage::READ); |
||||
fs["image_width"] >> calibratedImageSize.width; |
||||
fs["image_height"] >> calibratedImageSize.height; |
||||
fs["distortion_coefficients"] >> distCoeffs; |
||||
fs["camera_matrix"] >> cameraMatrix; |
||||
|
||||
if( distCoeffs.type() != CV_64F ) |
||||
distCoeffs = Mat_<double>(distCoeffs); |
||||
if( cameraMatrix.type() != CV_64F ) |
||||
cameraMatrix = Mat_<double>(cameraMatrix); |
||||
|
||||
return true; |
||||
} |
||||
|
||||
static bool readModelViews( const string& filename, vector<Point3f>& box, |
||||
vector<string>& imagelist, |
||||
vector<Rect>& roiList, vector<Vec6f>& poseList ) |
||||
{ |
||||
imagelist.resize(0); |
||||
roiList.resize(0); |
||||
poseList.resize(0); |
||||
box.resize(0); |
||||
|
||||
FileStorage fs(filename, FileStorage::READ); |
||||
if( !fs.isOpened() ) |
||||
return false; |
||||
fs["box"] >> box; |
||||
|
||||
FileNode all = fs["views"]; |
||||
if( all.type() != FileNode::SEQ ) |
||||
return false; |
||||
FileNodeIterator it = all.begin(), it_end = all.end(); |
||||
|
||||
for(; it != it_end; ++it) |
||||
{ |
||||
FileNode n = *it; |
||||
imagelist.push_back((string)n["image"]); |
||||
FileNode nr = n["roi"]; |
||||
roiList.push_back(Rect((int)nr[0], (int)nr[1], (int)nr[2], (int)nr[3])); |
||||
FileNode np = n["pose"]; |
||||
poseList.push_back(Vec6f((float)np[0], (float)np[1], (float)np[2], |
||||
(float)np[3], (float)np[4], (float)np[5])); |
||||
} |
||||
|
||||
return true; |
||||
} |
||||
|
||||
|
||||
struct PointModel |
||||
{ |
||||
vector<Point3f> points; |
||||
vector<vector<int> > didx; |
||||
Mat descriptors; |
||||
string name; |
||||
}; |
||||
|
||||
|
||||
static void writeModel(const string& modelFileName, const string& modelname, |
||||
const PointModel& model) |
||||
{ |
||||
FileStorage fs(modelFileName, FileStorage::WRITE); |
||||
|
||||
fs << modelname << "{" << |
||||
"points" << "[:" << model.points << "]" << |
||||
"idx" << "[:"; |
||||
|
||||
for( size_t i = 0; i < model.didx.size(); i++ ) |
||||
fs << "[:" << model.didx[i] << "]"; |
||||
fs << "]" << "descriptors" << model.descriptors; |
||||
} |
||||
|
||||
|
||||
static void unpackPose(const Vec6f& pose, Mat& R, Mat& t) |
||||
{ |
||||
Mat rvec = (Mat_<double>(3,1) << pose[0], pose[1], pose[2]); |
||||
t = (Mat_<double>(3,1) << pose[3], pose[4], pose[5]); |
||||
Rodrigues(rvec, R); |
||||
} |
||||
|
||||
|
||||
static Mat getFundamentalMat( const Mat& R1, const Mat& t1, |
||||
const Mat& R2, const Mat& t2, |
||||
const Mat& cameraMatrix ) |
||||
{ |
||||
Mat_<double> R = R2*R1.t(), t = t2 - R*t1; |
||||
double tx = t.at<double>(0,0), ty = t.at<double>(1,0), tz = t.at<double>(2,0); |
||||
Mat E = (Mat_<double>(3,3) << 0, -tz, ty, tz, 0, -tx, -ty, tx, 0)*R; |
||||
Mat iK = cameraMatrix.inv(); |
||||
Mat F = iK.t()*E*iK; |
||||
|
||||
#if 0 |
||||
static bool checked = false; |
||||
if(!checked) |
||||
{ |
||||
vector<Point3f> objpoints(100); |
||||
Mat O(objpoints); |
||||
randu(O, Scalar::all(-10), Scalar::all(10)); |
||||
vector<Point2f> imgpoints1, imgpoints2; |
||||
projectPoints(Mat(objpoints), R1, t1, cameraMatrix, Mat(), imgpoints1); |
||||
projectPoints(Mat(objpoints), R2, t2, cameraMatrix, Mat(), imgpoints2); |
||||
double* f = (double*)F.data; |
||||
for( size_t i = 0; i < objpoints.size(); i++ ) |
||||
{ |
||||
Point2f p1 = imgpoints1[i], p2 = imgpoints2[i]; |
||||
double diff = p2.x*(f[0]*p1.x + f[1]*p1.y + f[2]) + |
||||
p2.y*(f[3]*p1.x + f[4]*p1.y + f[5]) + |
||||
f[6]*p1.x + f[7]*p1.y + f[8]; |
||||
CV_Assert(fabs(diff) < 1e-3); |
||||
} |
||||
checked = true; |
||||
} |
||||
#endif |
||||
return F; |
||||
} |
||||
|
||||
|
||||
static void findConstrainedCorrespondences(const Mat& _F, |
||||
const vector<KeyPoint>& keypoints1, |
||||
const vector<KeyPoint>& keypoints2, |
||||
const Mat& descriptors1, |
||||
const Mat& descriptors2, |
||||
vector<Vec2i>& matches, |
||||
double eps, double ratio) |
||||
{ |
||||
float F[9]={0}; |
||||
int dsize = descriptors1.cols; |
||||
|
||||
Mat Fhdr = Mat(3, 3, CV_32F, F); |
||||
_F.convertTo(Fhdr, CV_32F); |
||||
matches.clear(); |
||||
|
||||
for( size_t i = 0; i < keypoints1.size(); i++ ) |
||||
{ |
||||
Point2f p1 = keypoints1[i].pt; |
||||
double bestDist1 = DBL_MAX, bestDist2 = DBL_MAX; |
||||
int bestIdx1 = -1, bestIdx2 = -1; |
||||
const float* d1 = descriptors1.ptr<float>(i); |
||||
|
||||
for( size_t j = 0; j < keypoints2.size(); j++ ) |
||||
{ |
||||
Point2f p2 = keypoints2[j].pt; |
||||
double e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) + |
||||
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) + |
||||
F[6]*p1.x + F[7]*p1.y + F[8]; |
||||
if( fabs(e) > eps ) |
||||
continue; |
||||
const float* d2 = descriptors2.ptr<float>(j); |
||||
double dist = 0; |
||||
int k = 0; |
||||
|
||||
for( ; k <= dsize - 8; k += 8 ) |
||||
{ |
||||
float t0 = d1[k] - d2[k], t1 = d1[k+1] - d2[k+1]; |
||||
float t2 = d1[k+2] - d2[k+2], t3 = d1[k+3] - d2[k+3]; |
||||
float t4 = d1[k+4] - d2[k+4], t5 = d1[k+5] - d2[k+5]; |
||||
float t6 = d1[k+6] - d2[k+6], t7 = d1[k+7] - d2[k+7]; |
||||
dist += t0*t0 + t1*t1 + t2*t2 + t3*t3 + |
||||
t4*t4 + t5*t5 + t6*t6 + t7*t7; |
||||
|
||||
if( dist >= bestDist2 ) |
||||
break; |
||||
} |
||||
|
||||
if( dist < bestDist2 ) |
||||
{ |
||||
for( ; k < dsize; k++ ) |
||||
{ |
||||
float t = d1[k] - d2[k]; |
||||
dist += t*t; |
||||
} |
||||
|
||||
if( dist < bestDist1 ) |
||||
{ |
||||
bestDist2 = bestDist1; |
||||
bestIdx2 = bestIdx1; |
||||
bestDist1 = dist; |
||||
bestIdx1 = (int)j; |
||||
} |
||||
else if( dist < bestDist2 ) |
||||
{ |
||||
bestDist2 = dist; |
||||
bestIdx2 = (int)j; |
||||
} |
||||
} |
||||
} |
||||
|
||||
if( bestIdx1 >= 0 && bestDist1 < bestDist2*ratio ) |
||||
{ |
||||
Point2f p2 = keypoints1[bestIdx1].pt; |
||||
double e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) + |
||||
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) + |
||||
F[6]*p1.x + F[7]*p1.y + F[8]; |
||||
if( e > eps*0.25 ) |
||||
continue; |
||||
double threshold = bestDist1/ratio; |
||||
const float* d22 = descriptors2.ptr<float>(bestIdx1); |
||||
size_t i1 = 0; |
||||
for( ; i1 < keypoints1.size(); i1++ ) |
||||
{ |
||||
if( i1 == i ) |
||||
continue; |
||||
Point2f p1 = keypoints1[i1].pt; |
||||
const float* d11 = descriptors1.ptr<float>(i1); |
||||
double dist = 0; |
||||
|
||||
e = p2.x*(F[0]*p1.x + F[1]*p1.y + F[2]) + |
||||
p2.y*(F[3]*p1.x + F[4]*p1.y + F[5]) + |
||||
F[6]*p1.x + F[7]*p1.y + F[8]; |
||||
if( fabs(e) > eps ) |
||||
continue; |
||||
|
||||
for( int k = 0; k < dsize; k++ ) |
||||
{ |
||||
float t = d11[k] - d22[k]; |
||||
dist += t*t; |
||||
if( dist >= threshold ) |
||||
break; |
||||
} |
||||
|
||||
if( dist < threshold ) |
||||
break; |
||||
} |
||||
if( i1 == keypoints1.size() ) |
||||
matches.push_back(Vec2i(i,bestIdx1)); |
||||
} |
||||
} |
||||
} |
||||
|
||||
|
||||
static Point3f findRayIntersection(Point3f k1, Point3f b1, Point3f k2, Point3f b2) |
||||
{
|
||||
float a[4], b[2], x[2]; |
||||
a[0] = k1.dot(k1); |
||||
a[1] = a[2] = -k1.dot(k2); |
||||
a[3] = k2.dot(k2); |
||||
b[0] = k1.dot(b2 - b1); |
||||
b[1] = k2.dot(b1 - b2); |
||||
Mat_<float> A(2, 2, a), B(2, 1, b), X(2, 1, x); |
||||
solve(A, B, X); |
||||
|
||||
float s1 = X.at<float>(0, 0); |
||||
float s2 = X.at<float>(1, 0); |
||||
return (k1*s1 + b1 + k2*s2 + b2)*0.5f; |
||||
} |
||||
|
||||
|
||||
static Point3f triangulatePoint(const vector<Point2f>& ps, |
||||
const vector<Mat>& Rs, |
||||
const vector<Mat>& ts, |
||||
const Mat& cameraMatrix) |
||||
{ |
||||
Mat_<double> K(cameraMatrix); |
||||
|
||||
if( ps.size() > 2 ) |
||||
{ |
||||
Mat_<double> L(ps.size()*3, 4), U, evalues; |
||||
Mat_<double> P(3,4), Rt(3,4), Rt_part1=Rt.colRange(0,3), Rt_part2=Rt.colRange(3,4); |
||||
|
||||
for( size_t i = 0; i < ps.size(); i++ ) |
||||
{ |
||||
double x = ps[i].x, y = ps[i].y; |
||||
Rs[i].convertTo(Rt_part1, Rt_part1.type()); |
||||
ts[i].convertTo(Rt_part2, Rt_part2.type()); |
||||
P = K*Rt; |
||||
|
||||
for( int k = 0; k < 4; k++ ) |
||||
{ |
||||
L(i*3, k) = x*P(2,k) - P(0,k); |
||||
L(i*3+1, k) = y*P(2,k) - P(1,k); |
||||
L(i*3+2, k) = x*P(1,k) - y*P(0,k); |
||||
} |
||||
} |
||||
|
||||
eigen(L.t()*L, evalues, U); |
||||
CV_Assert(evalues(0,0) >= evalues(3,0)); |
||||
|
||||
double W = fabs(U(3,3)) > FLT_EPSILON ? 1./U(3,3) : 0; |
||||
return Point3f((float)(U(3,0)*W), (float)(U(3,1)*W), (float)(U(3,2)*W)); |
||||
} |
||||
else |
||||
{ |
||||
Mat_<float> iK = K.inv(); |
||||
Mat_<float> R1t = Mat_<float>(Rs[0]).t(); |
||||
Mat_<float> R2t = Mat_<float>(Rs[1]).t(); |
||||
Mat_<float> m1 = (Mat_<float>(3,1) << ps[0].x, ps[0].y, 1); |
||||
Mat_<float> m2 = (Mat_<float>(3,1) << ps[1].x, ps[1].y, 1); |
||||
Mat_<float> K1 = R1t*(iK*m1), K2 = R2t*(iK*m2); |
||||
Mat_<float> B1 = -R1t*Mat_<float>(ts[0]); |
||||
Mat_<float> B2 = -R2t*Mat_<float>(ts[1]); |
||||
return findRayIntersection(*K1.ptr<Point3f>(), *B1.ptr<Point3f>(), |
||||
*K2.ptr<Point3f>(), *B2.ptr<Point3f>()); |
||||
} |
||||
} |
||||
|
||||
|
||||
void triangulatePoint_test(void) |
||||
{ |
||||
int i, n = 100; |
||||
vector<Point3f> objpt(n), delta1(n), delta2(n); |
||||
Mat rvec1(3,1,CV_32F), tvec1(3,1,CV_64F); |
||||
Mat rvec2(3,1,CV_32F), tvec2(3,1,CV_64F); |
||||
Mat objptmat(objpt), deltamat1(delta1), deltamat2(delta2); |
||||
randu(rvec1, Scalar::all(-10), Scalar::all(10)); |
||||
randu(tvec1, Scalar::all(-10), Scalar::all(10)); |
||||
randu(rvec2, Scalar::all(-10), Scalar::all(10)); |
||||
randu(tvec2, Scalar::all(-10), Scalar::all(10)); |
||||
|
||||
randu(objptmat, Scalar::all(-10), Scalar::all(10)); |
||||
double eps = 1e-2; |
||||
randu(deltamat1, Scalar::all(-eps), Scalar::all(eps)); |
||||
randu(deltamat2, Scalar::all(-eps), Scalar::all(eps)); |
||||
vector<Point2f> imgpt1, imgpt2; |
||||
Mat_<float> cameraMatrix(3,3); |
||||
double fx = 1000., fy = 1010., cx = 400.5, cy = 300.5; |
||||
cameraMatrix << fx, 0, cx, 0, fy, cy, 0, 0, 1; |
||||
|
||||
projectPoints(Mat(objpt)+Mat(delta1), rvec1, tvec1, cameraMatrix, Mat(), imgpt1); |
||||
projectPoints(Mat(objpt)+Mat(delta2), rvec2, tvec2, cameraMatrix, Mat(), imgpt2); |
||||
|
||||
vector<Point3f> objptt(n); |
||||
vector<Point2f> pts(2); |
||||
vector<Mat> Rv(2), tv(2); |
||||
Rodrigues(rvec1, Rv[0]); |
||||
Rodrigues(rvec2, Rv[1]); |
||||
tv[0] = tvec1; tv[1] = tvec2; |
||||
for( i = 0; i < n; i++ ) |
||||
{ |
||||
pts[0] = imgpt1[i]; pts[1] = imgpt2[i]; |
||||
objptt[i] = triangulatePoint(pts, Rv, tv, cameraMatrix); |
||||
} |
||||
double err = norm(Mat(objpt), Mat(objptt), CV_C); |
||||
CV_Assert(err < 1e-1); |
||||
} |
||||
|
||||
typedef pair<int, int> Pair2i; |
||||
typedef map<Pair2i, int> Set2i; |
||||
|
||||
struct EqKeypoints |
||||
{ |
||||
EqKeypoints(const vector<int>* _dstart, const Set2i* _pairs) |
||||
: dstart(_dstart), pairs(_pairs) {} |
||||
|
||||
bool operator()(const Pair2i& a, const Pair2i& b) const |
||||
{ |
||||
return pairs->find(Pair2i(dstart->at(a.first) + a.second, |
||||
dstart->at(b.first) + b.second)) != pairs->end(); |
||||
} |
||||
|
||||
const vector<int>* dstart; |
||||
const Set2i* pairs; |
||||
}; |
||||
|
||||
static void build3dmodel( const Ptr<FeatureDetector>& detector, |
||||
const Ptr<DescriptorExtractor>& descriptorExtractor, |
||||
const vector<Point3f>& modelBox, |
||||
const vector<string>& imageList, |
||||
const vector<Rect>& roiList, |
||||
const vector<Vec6f>& poseList, |
||||
const Mat& cameraMatrix, |
||||
PointModel& model ) |
||||
{ |
||||
int progressBarSize = 10; |
||||
|
||||
const double Feps = 5; |
||||
const double DescriptorRatio = 0.7; |
||||
|
||||
vector<vector<KeyPoint> > allkeypoints; |
||||
vector<int> dstart; |
||||
vector<float> alldescriptorsVec; |
||||
vector<Vec2i> pairwiseMatches; |
||||
vector<Mat> Rs, ts; |
||||
int descriptorSize = 0; |
||||
Mat descriptorbuf; |
||||
Set2i pairs, keypointsIdxMap; |
||||
|
||||
model.points.clear(); |
||||
model.didx.clear(); |
||||
|
||||
dstart.push_back(0); |
||||
|
||||
size_t nimages = imageList.size(); |
||||
size_t nimagePairs = (nimages - 1)*nimages/2 - nimages; |
||||
|
||||
printf("\nComputing descriptors "); |
||||
|
||||
// 1. find all the keypoints and all the descriptors
|
||||
for( size_t i = 0; i < nimages; i++ ) |
||||
{ |
||||
Mat img = imread(imageList[i], 1), gray; |
||||
cvtColor(img, gray, CV_BGR2GRAY); |
||||
|
||||
vector<KeyPoint> keypoints; |
||||
detector->detect(gray, keypoints); |
||||
descriptorExtractor->compute(gray, keypoints, descriptorbuf); |
||||
Point2f roiofs = roiList[i].tl();
|
||||
for( size_t k = 0; k < keypoints.size(); k++ ) |
||||
keypoints[k].pt += roiofs; |
||||
allkeypoints.push_back(keypoints); |
||||
|
||||
Mat buf = descriptorbuf; |
||||
if( !buf.isContinuous() || buf.type() != CV_32F ) |
||||
{ |
||||
buf.release(); |
||||
descriptorbuf.convertTo(buf, CV_32F); |
||||
} |
||||
descriptorSize = buf.cols; |
||||
|
||||
size_t prev = alldescriptorsVec.size(); |
||||
size_t delta = buf.rows*buf.cols; |
||||
alldescriptorsVec.resize(prev + delta);
|
||||
std::copy(buf.ptr<float>(), buf.ptr<float>() + delta, |
||||
alldescriptorsVec.begin() + prev); |
||||
dstart.push_back(dstart.back() + keypoints.size()); |
||||
|
||||
Mat R, t; |
||||
unpackPose(poseList[i], R, t); |
||||
Rs.push_back(R); |
||||
ts.push_back(t); |
||||
|
||||
if( (i+1)*progressBarSize/nimages > i*progressBarSize/nimages ) |
||||
{ |
||||
putchar('.'); |
||||
fflush(stdout); |
||||
} |
||||
} |
||||
|
||||
Mat alldescriptors(alldescriptorsVec.size()/descriptorSize, descriptorSize, CV_32F, |
||||
&alldescriptorsVec[0]); |
||||
|
||||
printf("\nOk. total images = %d. total keypoints = %d\n", |
||||
(int)nimages, alldescriptors.rows); |
||||
|
||||
printf("\nFinding correspondences "); |
||||
|
||||
int pairsFound = 0; |
||||
|
||||
vector<Point2f> pts_k(2); |
||||
vector<Mat> Rs_k(2), ts_k(2); |
||||
//namedWindow("img1", 1);
|
||||
//namedWindow("img2", 1);
|
||||
|
||||
// 2. find pairwise correspondences
|
||||
for( size_t i = 0; i < nimages; i++ ) |
||||
for( size_t j = i+1; j < nimages; j++ ) |
||||
{ |
||||
const vector<KeyPoint>& keypoints1 = allkeypoints[i]; |
||||
const vector<KeyPoint>& keypoints2 = allkeypoints[j]; |
||||
Mat descriptors1 = alldescriptors.rowRange(dstart[i], dstart[i+1]); |
||||
Mat descriptors2 = alldescriptors.rowRange(dstart[j], dstart[j+1]); |
||||
|
||||
Mat F = getFundamentalMat(Rs[i], ts[i], Rs[j], ts[j], cameraMatrix); |
||||
|
||||
findConstrainedCorrespondences( F, keypoints1, keypoints2, |
||||
descriptors1, descriptors2, |
||||
pairwiseMatches, Feps, DescriptorRatio ); |
||||
|
||||
//pairsFound += (int)pairwiseMatches.size();
|
||||
|
||||
//Mat img1 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1);
|
||||
//Mat img2 = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)j), 1);
|
||||
|
||||
//double avg_err = 0;
|
||||
for( size_t k = 0; k < pairwiseMatches.size(); k++ ) |
||||
{ |
||||
int i1 = pairwiseMatches[k][0], i2 = pairwiseMatches[k][1]; |
||||
|
||||
pts_k[0] = keypoints1[i1].pt; |
||||
pts_k[1] = keypoints2[i2].pt; |
||||
Rs_k[0] = Rs[i]; Rs_k[1] = Rs[j]; |
||||
ts_k[0] = ts[i]; ts_k[1] = ts[j]; |
||||
Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix); |
||||
|
||||
vector<Point3f> objpts; |
||||
objpts.push_back(objpt); |
||||
vector<Point2f> imgpts1, imgpts2; |
||||
projectPoints(Mat(objpts), Rs_k[0], ts_k[0], cameraMatrix, Mat(), imgpts1); |
||||
projectPoints(Mat(objpts), Rs_k[1], ts_k[1], cameraMatrix, Mat(), imgpts2); |
||||
|
||||
double e1 = norm(imgpts1[0] - keypoints1[i1].pt); |
||||
double e2 = norm(imgpts2[0] - keypoints2[i2].pt); |
||||
if( e1 + e2 > 10 ) |
||||
continue; |
||||
|
||||
pairsFound++; |
||||
//pts_k[0] = imgpts1[0];
|
||||
//pts_k[1] = imgpts2[0];
|
||||
//objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix);
|
||||
//objpts[0] = objpt;
|
||||
//projectPoints(Mat(objpts), Rs_k[0], ts_k[0], cameraMatrix, Mat(), imgpts1);
|
||||
//projectPoints(Mat(objpts), Rs_k[1], ts_k[1], cameraMatrix, Mat(), imgpts2);
|
||||
//double e1 = norm(imgpts1[0] - keypoints1[i1].pt);
|
||||
//double e2 = norm(imgpts2[0] - keypoints2[i2].pt);
|
||||
|
||||
//model.points.push_back(objpt);
|
||||
pairs[Pair2i(i1+dstart[i], i2+dstart[j])] = 1; |
||||
pairs[Pair2i(i2+dstart[j], i1+dstart[i])] = 1; |
||||
keypointsIdxMap[Pair2i(i,i1)] = 1; |
||||
keypointsIdxMap[Pair2i(j,i2)] = 1; |
||||
//CV_Assert(e1 < 5 && e2 < 5);
|
||||
//Scalar color(rand()%256,rand()%256, rand()%256);
|
||||
//circle(img1, keypoints1[i1].pt, 2, color, -1, CV_AA);
|
||||
//circle(img2, keypoints2[i2].pt, 2, color, -1, CV_AA);
|
||||
} |
||||
//printf("avg err = %g\n", pairwiseMatches.size() ? avg_err/(2*pairwiseMatches.size()) : 0.);
|
||||
//imshow("img1", img1);
|
||||
//imshow("img2", img2);
|
||||
//waitKey();
|
||||
|
||||
if( (i+1)*progressBarSize/nimagePairs > i*progressBarSize/nimagePairs ) |
||||
{ |
||||
putchar('.'); |
||||
fflush(stdout); |
||||
} |
||||
} |
||||
|
||||
printf("\nOk. Total pairs = %d\n", pairsFound ); |
||||
|
||||
// 3. build the keypoint clusters
|
||||
vector<Pair2i> keypointsIdx; |
||||
Set2i::iterator kpidx_it = keypointsIdxMap.begin(), kpidx_end = keypointsIdxMap.end(); |
||||
|
||||
for( ; kpidx_it != kpidx_end; ++kpidx_it ) |
||||
keypointsIdx.push_back(kpidx_it->first); |
||||
|
||||
printf("\nClustering correspondences "); |
||||
|
||||
vector<int> labels; |
||||
int nclasses = partition( keypointsIdx, labels, EqKeypoints(&dstart, &pairs) ); |
||||
|
||||
printf("\nOk. Total classes (i.e. 3d points) = %d\n", nclasses ); |
||||
|
||||
model.descriptors.create(keypointsIdx.size(), descriptorSize, CV_32F); |
||||
model.didx.resize(nclasses); |
||||
model.points.resize(nclasses); |
||||
|
||||
vector<vector<Pair2i> > clusters(nclasses); |
||||
for( size_t i = 0; i < keypointsIdx.size(); i++ ) |
||||
clusters[labels[i]].push_back(keypointsIdx[i]); |
||||
|
||||
// 4. now compute 3D points corresponding to each cluster and fill in the model data
|
||||
printf("\nComputing 3D coordinates "); |
||||
|
||||
int globalDIdx = 0; |
||||
for( int k = 0; k < nclasses; k++ ) |
||||
{ |
||||
int i, n = (int)clusters[k].size(); |
||||
pts_k.resize(n); |
||||
Rs_k.resize(n); |
||||
ts_k.resize(n); |
||||
model.didx[k].resize(n); |
||||
for( i = 0; i < n; i++ ) |
||||
{ |
||||
int imgidx = clusters[k][i].first, ptidx = clusters[k][i].second; |
||||
Mat dstrow = model.descriptors.row(globalDIdx); |
||||
alldescriptors.row(dstart[imgidx] + ptidx).copyTo(dstrow); |
||||
|
||||
model.didx[k][i] = globalDIdx++; |
||||
pts_k[i] = allkeypoints[imgidx][ptidx].pt; |
||||
Rs_k[i] = Rs[imgidx]; |
||||
ts_k[i] = ts[imgidx]; |
||||
} |
||||
Point3f objpt = triangulatePoint(pts_k, Rs_k, ts_k, cameraMatrix); |
||||
model.points[k] = objpt; |
||||
|
||||
if( (i+1)*progressBarSize/nclasses > i*progressBarSize/nclasses ) |
||||
{ |
||||
putchar('.'); |
||||
fflush(stdout); |
||||
} |
||||
} |
||||
|
||||
Mat img(768, 1024, CV_8UC3); |
||||
vector<Point2f> imagePoints; |
||||
namedWindow("Test", 1); |
||||
|
||||
// visualize the cloud
|
||||
for( size_t i = 0; i < nimages; i++ ) |
||||
{ |
||||
img = imread(format("%s/frame%04d.jpg", model.name.c_str(), (int)i), 1); |
||||
projectPoints(Mat(model.points), Rs[i], ts[i], cameraMatrix, Mat(), imagePoints); |
||||
|
||||
for( int k = 0; k < (int)imagePoints.size(); k++ ) |
||||
circle(img, imagePoints[k], 2, Scalar(0,255,0), -1, CV_AA, 0); |
||||
|
||||
imshow("Test", img); |
||||
int c = waitKey(); |
||||
if( c == 'q' || c == 'Q' ) |
||||
break; |
||||
} |
||||
} |
||||
|
||||
|
||||
int main(int argc, char** argv) |
||||
{ |
||||
triangulatePoint_test(); |
||||
|
||||
const char* help = "Usage: build3dmodel -i <intrinsics_filename>\n" |
||||
"\t[-d <detector>] [-de <descriptor_extractor>] -m <model_name>\n"; |
||||
|
||||
if(argc < 3) |
||||
{ |
||||
puts(help); |
||||
return 0; |
||||
} |
||||
const char* intrinsicsFilename = 0; |
||||
const char* modelName = 0; |
||||
const char* detectorName = "SURF"; |
||||
const char* descriptorExtractorName = "SURF";
|
||||
vector<Point3f> modelBox; |
||||
vector<string> imageList; |
||||
vector<Rect> roiList; |
||||
vector<Vec6f> poseList; |
||||
|
||||
for( int i = 1; i < argc; i++ ) |
||||
{ |
||||
if( strcmp(argv[i], "-i") == 0 ) |
||||
intrinsicsFilename = argv[++i]; |
||||
else if( strcmp(argv[i], "-m") == 0 ) |
||||
modelName = argv[++i]; |
||||
else if( strcmp(argv[i], "-d") == 0 ) |
||||
detectorName = argv[++i]; |
||||
else if( strcmp(argv[i], "-de") == 0 ) |
||||
descriptorExtractorName = argv[++i]; |
||||
else |
||||
{ |
||||
printf("Incorrect option\n"); |
||||
puts(help); |
||||
return 0; |
||||
} |
||||
} |
||||
|
||||
if( !intrinsicsFilename || !modelName ) |
||||
{ |
||||
printf("Some of the required parameters are missing\n"); |
||||
puts(help); |
||||
return 0; |
||||
} |
||||
|
||||
Mat cameraMatrix, distCoeffs; |
||||
Size calibratedImageSize; |
||||
readCameraMatrix(intrinsicsFilename, cameraMatrix, distCoeffs, calibratedImageSize); |
||||
|
||||
Ptr<FeatureDetector> detector = createDetector(detectorName); |
||||
Ptr<DescriptorExtractor> descriptorExtractor = createDescriptorExtractor(descriptorExtractorName); |
||||
|
||||
string modelIndexFilename = format("%s_segm/frame_index.yml", modelName); |
||||
if(!readModelViews( modelIndexFilename, modelBox, imageList, roiList, poseList)) |
||||
{ |
||||
printf("Can not read the model. Check the parameters and the working directory\n"); |
||||
puts(help); |
||||
return 0; |
||||
} |
||||
|
||||
PointModel model; |
||||
model.name = modelName; |
||||
build3dmodel( detector, descriptorExtractor, modelBox, |
||||
imageList, roiList, poseList, cameraMatrix, model ); |
||||
string outputModelName = format("%s_model.yml.gz", modelName); |
||||
|
||||
|
||||
printf("\nDone! Now saving the model ...\n"); |
||||
writeModel(outputModelName, modelName, model); |
||||
|
||||
return 0; |
||||
} |
||||
Loading…
Reference in new issue