cleaned dls code
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@@ -39,9 +39,6 @@ dls::dls(const cv::Mat& opoints, const cv::Mat& ipoints)
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init_points<cv::Point3f, cv::Point2d>(opoints, ipoints);
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else
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init_points<cv::Point3d, cv::Point2f>(opoints, ipoints);
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//norm_z_vector();
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}
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dls::~dls()
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@@ -57,13 +54,10 @@ bool dls::compute_pose(cv::Mat& R, cv::Mat& t)
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R_.push_back(roty(CV_PI/2));
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R_.push_back(rotz(CV_PI/2));
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//cv::Mat t_mean = this->mean(p);
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// version that calls dls 3 times, to avoid Cayley singularity
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for (int i = 0; i < 3; ++i)
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{
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// Make a random rotation
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//cv::Mat pp = R_[i] * ( p - cv::repeat(t_mean, 1, p.cols) );
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cv::Mat pp = R_[i] * ( p - cv::repeat(mn, 1, p.cols) );
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// clear for new data
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@@ -78,7 +72,6 @@ bool dls::compute_pose(cv::Mat& R, cv::Mat& t)
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{
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if( cost_[j] < cost__ )
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{
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//t_est__ = t_est_[j] - C_est_[j] * R_[i] * t_mean;
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t_est__ = t_est_[j] - C_est_[j] * R_[i] * mn;
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C_est__ = C_est_[j] * R_[i];
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cost__ = cost_[j];
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@@ -223,11 +216,6 @@ void dls::build_coeff_matrix(const cv::Mat& pp, cv::Mat& Mtilde, cv::Mat& D)
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cv::Mat A = cv::Mat::zeros(3, 9, CV_64F);
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cv::Mat pp_i(3, 1, CV_64F);
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//Parallel_compute_A comp_A(&A, &pp, &z);
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//cv::parallel_for_(cv::Range(0, N), comp_A);
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//exit(-1);
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cv::Mat z_i(3, 1, CV_64F);
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for (int i = 0; i < N; ++i)
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{
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