Per installare ed usare PCL su Windows la cosa piu' comoda e' utilizzare il pacchetto PCL-1.11.1-AllInOne-msvc2019-win64
Una volta installato il file exe per esempio in C:\Program Files\PCL 1.11.1
Per creare un progetto in QT con le PCL si devono aggiungere nella path OpenNI2 (stranamente l'installer non la ha aggiunta nella PATH)
il file CMAKE e' il seguente
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cmake_minimum_required(VERSION 3.5)
project(t3 LANGUAGES CXX)
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
find_package(PCL 1.3 REQUIRED COMPONENTS common io features)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
add_executable(t3 main.cpp)
target_link_libraries(t3 ${PCL_LIBRARIES})
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mentre un programma di esempio e'
===============================================
#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/features/normal_3d.h>
using namespace std;
int main()
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
if (pcl::io::loadPCDFile<pcl::PointXYZ> ("c://gabriele.pcd", *cloud) == -1) //* load the file
{
PCL_ERROR ("Couldn't read file test_pcd.pcd \n");
return (-1);
}
//std::cout << "Loaded " << cloud->width * cloud->height << " data points from test_pcd.pcd with the following fields: " << std::endl;
/*for (size_t i = 0; i < cloud->points.size (); ++i)
std::cout << " " << cloud->points[i].x << " " << cloud->points[i].y << " " << cloud->points[i].z << std::endl;
*/
// Create the normal estimation class, and pass the input dataset to it
pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> ne;
ne.setInputCloud (cloud);
// Create an empty kdtree representation, and pass it to the normal estimation object.
// Its content will be filled inside the object, based on the given input dataset (as no other search surface is given).
pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ> ());
ne.setSearchMethod (tree);
// Output datasets
pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal>);
// Use all neighbors in a sphere of radius 3cm
ne.setRadiusSearch (0.03);
// Compute the features
ne.compute (*cloud_normals);
//std::cout << endl << cloud_normals->size() << endl;
// cloud_normals->size () should have the same size as the input cloud->size ()*
int i = 0;
for (pcl::Normal n : *cloud_normals) {
//std::cerr << i << " n = " << n.normal_x << ", " << n.normal_y << ", " << n.normal_z << "\n";
std::cout << n.normal_x << "," << n.normal_y << "," << n.normal_z << "\n";
i++;
}
return 0;
}