主要用于提取地面点和非地面点,代码如下:
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/console/print.h>
#include <pcl/console/parse.h>
#include <pcl/console/time.h>
#include <pcl/filters/extract_indices.h>
#include <pcl/segmentation/approximate_progressive_morphological_filter.h>
#include <pcl/segmentation/progressive_morphological_filter.h>
using namespace std;
using namespace pcl;
using namespace pcl::io;
using namespace pcl::console;
typedef PointXYZ PointType;
typedef PointCloud<PointXYZ> Cloud;
typedef const Cloud::ConstPtr ConstCloudPtr;
int default_max_window_size = 33;
float default_slope = 0.7f;
float default_max_distance = 10.0f;
float default_initial_distance = 0.15f;
float default_cell_size = 1.0f;
float default_base = 2.0f;
bool default_exponential = true;
int default_verbosity_level = 3;
void
printHelp (int, char **argv)
{
print_error ("Syntax is: %s input.pcd output.pcd <options>\n", argv[0]);
print_info (" where options are:\n");
print_info (" -max_window_size X = maximum window size (default: ");
print_value ("%d", default_max_window_size); print_info (")\n");
print_info (" -slope X = slope value to compute threshold (default: ");
print_value ("%f", default_slope); print_info (")\n");
print_info (" -max_distnace X = maximum distance from parameterized ground surface to be considered ground (default: ");
print_value ("%f", default_max_distance); print_info (")\n");
print_info (" -initial_distance X = initial distance from parameterized ground surface to be considered ground (default: ");
print_value ("%f", default_initial_distance); print_info (")\n");
print_info (" -cell_size X = cell size (default: ");
print_value ("%f", default_cell_size); print_info (")\n");
print_info (" -base X = base to be used in computing progressive window sizes (default: ");
print_value ("%f", default_base); print_info (")\n");
print_info (" -exponential X = use exponential growth? (default: ");
print_value ("%s", default_exponential?"true":"false"); print_info (")\n");
print_info (" -approximate X = use approximate? (default: false\n");
print_info (" -input_dir X = batch process all PCD files found in input_dir\n");
print_info (" -output_dir X = save the processed files from input_dir in this directory\n");
print_info (" -verbosity X = verbosity level (default: ");
print_value ("%d", default_verbosity_level); print_info (")\n");
}
bool
loadCloud (const std::string &filename, Cloud &cloud)
{
TicToc tt;
print_highlight ("Loading "); print_value ("%s ", filename.c_str ());
tt.tic ();
if (loadPCDFile (filename, cloud) < 0)
return (false);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", cloud.width * cloud.height); print_info (" points]\n");
print_info ("Available dimensions: "); print_value ("%s\n", pcl::getFieldsList (cloud).c_str ());
return (true);
}
void
compute (ConstCloudPtr &input, Cloud &output, int max_window_size, float slope, float max_distance, float initial_distance, float cell_size, float base, bool exponential, bool approximate)
{
// Estimate
TicToc tt;
tt.tic ();
print_highlight (stderr, "Computing ");
std::vector<int> ground;
if (approximate)
{
PCL_DEBUG ("approx with %d points\n", input->points.size ());
ApproximateProgressiveMorphologicalFilter<PointType> pmf;
pmf.setInputCloud (input);
pmf.setMaxWindowSize (max_window_size);
pmf.setSlope (slope);
pmf.setMaxDistance (max_distance);
pmf.setInitialDistance (initial_distance);
pmf.setCellSize (cell_size);
pmf.setBase (base);
pmf.setExponential (exponential);
pmf.extract (ground);
}
else
{
PCL_DEBUG ("full\n");
ProgressiveMorphologicalFilter<PointType> pmf;
pmf.setInputCloud (input);
pmf.setMaxWindowSize (max_window_size);
pmf.setSlope (slope);
pmf.setMaxDistance (max_distance);
pmf.setInitialDistance (initial_distance);
pmf.setCellSize (cell_size);
pmf.setBase (base);
pmf.setExponential (exponential);
pmf.extract (ground);
}
PointIndicesPtr idx (new PointIndices);
idx->indices = ground;
ExtractIndices<PointType> extract;
extract.setInputCloud (input);
extract.setIndices (idx);
extract.setNegative (false);
extract.filter (output);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output.width * output.height); print_info (" points]\n");
}
void
saveCloud (const std::string &filename, const Cloud &output)
{
TicToc tt;
tt.tic ();
print_highlight ("Saving "); print_value ("%s ", filename.c_str ());
PCDWriter w;
w.writeBinaryCompressed (filename, output);
print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", output.width * output.height); print_info (" points]\n");
}
int
batchProcess (const vector<string> &pcd_files, string &output_dir, int max_window_size, float slope, float max_distance, float initial_distance, float cell_size, float base, bool exponential, bool approximate)
{
vector<string> st;
for (size_t i = 0; i < pcd_files.size (); ++i)
{
// Load the first file
Cloud::Ptr cloud (new Cloud);
if (!loadCloud (pcd_files[i], *cloud))
return (-1);
// Perform the feature estimation
Cloud output;
compute (cloud, output, max_window_size, slope, max_distance, initial_distance, cell_size, base, exponential, approximate);
// Prepare output file name
string filename = pcd_files[i];
boost::trim (filename);
boost::split (st, filename, boost::is_any_of ("/\\"), boost::token_compress_on);
// Save into the second file
stringstream ss;
ss << output_dir << "/" << st.at (st.size () - 1);
saveCloud (ss.str (), output);
}
return (0);
}
/* ---[ */
int
main (int argc, char** argv)
{
print_info ("Filter a point cloud using the pcl::ProgressiveMorphologicalFilter. For more information, use: %s -h\n", argv[0]);
if (argc < 3)
{
printHelp (argc, argv);
return (-1);
}
bool batch_mode = false;
// Command line parsing
int max_window_size = default_max_window_size;
float slope = default_slope;
float max_distance = default_max_distance;
float initial_distance = default_initial_distance;
float cell_size = default_cell_size;
float base = default_base;
bool exponential = default_exponential;
bool approximate;
int verbosity_level = default_verbosity_level;
parse_argument (argc, argv, "-max_window_size", max_window_size);
parse_argument (argc, argv, "-slope", slope);
parse_argument (argc, argv, "-max_distance", max_distance);
parse_argument (argc, argv, "-initial_distance", initial_distance);
parse_argument (argc, argv, "-cell_size", cell_size);
parse_argument (argc, argv, "-base", base);
parse_argument (argc, argv, "-exponential", exponential);
approximate = find_switch (argc, argv, "-approximate");
parse_argument (argc, argv, "-verbosity", verbosity_level);
string input_dir, output_dir;
if (parse_argument (argc, argv, "-input_dir", input_dir) != -1)
{
PCL_INFO ("Input directory given as %s. Batch process mode on.\n", input_dir.c_str ());
if (parse_argument (argc, argv, "-output_dir", output_dir) == -1)
{
PCL_ERROR ("Need an output directory! Please use -output_dir to continue.\n");
return (-1);
}
// Both input dir and output dir given, switch into batch processing mode
batch_mode = true;
}
switch (verbosity_level)
{
case 0:
pcl::console::setVerbosityLevel(pcl::console::L_ALWAYS);
break;
case 1:
pcl::console::setVerbosityLevel(pcl::console::L_ERROR);
break;
case 2:
pcl::console::setVerbosityLevel(pcl::console::L_WARN);
break;
case 3:
pcl::console::setVerbosityLevel(pcl::console::L_INFO);
break;
case 4:
pcl::console::setVerbosityLevel(pcl::console::L_DEBUG);
break;
default:
pcl::console::setVerbosityLevel(pcl::console::L_VERBOSE);
break;
}
if (!batch_mode)
{
// Parse the command line arguments for .pcd files
std::vector<int> p_file_indices;
p_file_indices = parse_file_extension_argument (argc, argv, ".pcd");
if (p_file_indices.size () != 2)
{
print_error ("Need one input PCD file and one output PCD file to continue.\n");
return (-1);
}
// Load the first file
Cloud::Ptr cloud (new Cloud);
if (!loadCloud (argv[p_file_indices[0]], *cloud))
return (-1);
// Perform the feature estimation
Cloud output;
compute (cloud, output, max_window_size, slope, max_distance, initial_distance, cell_size, base, exponential, approximate);
// Save into the second file
saveCloud (argv[p_file_indices[1]], output);
}
else
{
if (input_dir != "" && boost::filesystem::exists (input_dir))
{
vector<string> pcd_files;
boost::filesystem::directory_iterator end_itr;
for (boost::filesystem::directory_iterator itr (input_dir); itr != end_itr; ++itr)
{
// Only add PCD files
if (!is_directory (itr->status ()) && boost::algorithm::to_upper_copy (boost::filesystem::extension (itr->path ())) == ".PCD" )
{
pcd_files.push_back (itr->path ().string ());
PCL_INFO ("[Batch processing mode] Added %s for processing.\n", itr->path ().string ().c_str ());
}
}
batchProcess (pcd_files, output_dir, max_window_size, slope, max_distance, initial_distance, cell_size, base, exponential, approximate);
}
else
{
PCL_ERROR ("Batch processing mode enabled, but invalid input directory (%s) given!\n", input_dir.c_str ());
return (-1);
}
}
}
来源:PCL官方示例