From c60e97c5b6d9e1a0997884aa2dea666c79185110 Mon Sep 17 00:00:00 2001 From: Levi Armstrong Date: Tue, 19 Sep 2017 07:09:18 -0500 Subject: [PATCH] Remove use of depreciated function setPolynomialFit in mls --- test/surface/test_moving_least_squares.cpp | 6 ++--- tools/mls_smoothing.cpp | 27 +++++++++------------- 2 files changed, 14 insertions(+), 19 deletions(-) diff --git a/test/surface/test_moving_least_squares.cpp b/test/surface/test_moving_least_squares.cpp index d8b874149f9..dc396885eb9 100644 --- a/test/surface/test_moving_least_squares.cpp +++ b/test/surface/test_moving_least_squares.cpp @@ -72,7 +72,7 @@ TEST (PCL, MovingLeastSquares) // Set parameters mls.setInputCloud (cloud); mls.setComputeNormals (true); - mls.setPolynomialFit (true); + mls.setPolynomialOrder (2); mls.setSearchMethod (tree); mls.setSearchRadius (0.03); @@ -92,7 +92,7 @@ TEST (PCL, MovingLeastSquares) MovingLeastSquaresOMP mls_omp; mls_omp.setInputCloud (cloud); mls_omp.setComputeNormals (true); - mls_omp.setPolynomialFit (true); + mls_omp.setPolynomialOrder (2); mls_omp.setSearchMethod (tree); mls_omp.setSearchRadius (0.03); mls_omp.setNumberOfThreads (4); @@ -123,7 +123,7 @@ TEST (PCL, MovingLeastSquares) // Set parameters mls_upsampling.setInputCloud (cloud); mls_upsampling.setComputeNormals (true); - mls_upsampling.setPolynomialFit (true); + mls_upsampling.setPolynomialOrder (2); mls_upsampling.setSearchMethod (tree); mls_upsampling.setSearchRadius (0.03); mls_upsampling.setUpsamplingMethod (MovingLeastSquares::SAMPLE_LOCAL_PLANE); diff --git a/tools/mls_smoothing.cpp b/tools/mls_smoothing.cpp index 1825b945bad..973fcb14e0e 100644 --- a/tools/mls_smoothing.cpp +++ b/tools/mls_smoothing.cpp @@ -49,7 +49,6 @@ using namespace pcl::io; using namespace pcl::console; int default_polynomial_order = 2; -bool default_use_polynomial_fit = false; double default_search_radius = 0.0, default_sqr_gauss_param = 0.0; @@ -63,9 +62,7 @@ printHelp (int, char **argv) print_value ("%f", default_search_radius); print_info (")\n"); print_info (" -sqr_gauss_param X = parameter used for the distance based weighting of neighbors (recommended = search_radius^2) (default: "); print_value ("%f", default_sqr_gauss_param); print_info (")\n"); - print_info (" -use_polynomial_fit X = decides whether the surface and normal are approximated using a polynomial or only via tangent estimation (default: "); - print_value ("%d", default_use_polynomial_fit); print_info (")\n"); - print_info (" -polynomial_order X = order of the polynomial to be fit (implicitly, use_polynomial_fit = 1) (default: "); + print_info (" -polynomial_order X = order of the polynomial to be fit (polynomial_order > 1, indicates using a polynomial fit) (default: "); print_value ("%d", default_polynomial_order); print_info (")\n"); } @@ -85,9 +82,12 @@ loadCloud (const std::string &filename, pcl::PCLPointCloud2 &cloud) } void -compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output, - double search_radius, bool sqr_gauss_param_set, double sqr_gauss_param, - bool use_polynomial_fit, int polynomial_order) +compute (const pcl::PCLPointCloud2::ConstPtr &input, + pcl::PCLPointCloud2 &output, + double search_radius, + bool sqr_gauss_param_set, + double sqr_gauss_param, + int polynomial_order) { PointCloud::Ptr xyz_cloud_pre (new pcl::PointCloud ()), @@ -111,7 +111,6 @@ compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output mls.setInputCloud (xyz_cloud); mls.setSearchRadius (search_radius); if (sqr_gauss_param_set) mls.setSqrGaussParam (sqr_gauss_param); - mls.setPolynomialFit (use_polynomial_fit); mls.setPolynomialOrder (polynomial_order); // mls.setUpsamplingMethod (MovingLeastSquares::SAMPLE_LOCAL_PLANE); @@ -128,8 +127,8 @@ compute (const pcl::PCLPointCloud2::ConstPtr &input, pcl::PCLPointCloud2 &output mls.setSearchMethod (tree); mls.setComputeNormals (true); - PCL_INFO ("Computing smoothed surface and normals with search_radius %f , sqr_gaussian_param %f, polynomial fitting %d, polynomial order %d\n", - mls.getSearchRadius(), mls.getSqrGaussParam(), mls.getPolynomialFit(), mls.getPolynomialOrder()); + PCL_INFO ("Computing smoothed surface and normals with search_radius %f , sqr_gaussian_param %f, polynomial order %d\n", + mls.getSearchRadius(), mls.getSqrGaussParam(), mls.getPolynomialOrder()); TicToc tt; tt.tic (); mls.process (*xyz_cloud_smoothed); @@ -178,14 +177,11 @@ main (int argc, char** argv) double sqr_gauss_param = default_sqr_gauss_param; bool sqr_gauss_param_set = true; int polynomial_order = default_polynomial_order; - bool use_polynomial_fit = default_use_polynomial_fit; parse_argument (argc, argv, "-radius", search_radius); + parse_argument (argc, argv, "-polynomial_order", polynomial_order); if (parse_argument (argc, argv, "-sqr_gauss_param", sqr_gauss_param) == -1) sqr_gauss_param_set = false; - if (parse_argument (argc, argv, "-polynomial_order", polynomial_order) != -1 ) - use_polynomial_fit = true; - parse_argument (argc, argv, "-use_polynomial_fit", use_polynomial_fit); // Load the first file pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2); @@ -194,8 +190,7 @@ main (int argc, char** argv) // Do the smoothing pcl::PCLPointCloud2 output; - compute (cloud, output, search_radius, sqr_gauss_param_set, sqr_gauss_param, - use_polynomial_fit, polynomial_order); + compute (cloud, output, search_radius, sqr_gauss_param_set, sqr_gauss_param, polynomial_order); // Save into the second file saveCloud (argv[p_file_indices[1]], output);