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point_io.hpp
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point_io.hpp
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#ifndef POINTIO_H
#define POINTIO_H
#include <iostream>
#include <fstream>
#include <torch/torch.h>
#ifdef WITH_PDAL
#include <pdal/Options.hpp>
#include <pdal/PointTable.hpp>
#include <pdal/StageFactory.hpp>
#include <pdal/io/BufferReader.hpp>
#endif
#include <nanoflann.hpp>
struct XYZ {
float x;
float y;
float z;
};
#define KDTREE_MAX_LEAF 10
#define RELEASE_POINTSET(__POINTER) { if (__POINTER != nullptr) { __POINTER->freeIndex<KdTree>(); delete __POINTER; __POINTER = nullptr; } }
struct PointSet {
std::vector<std::array<float, 3> > points;
std::vector<std::array<uint8_t, 3> > colors;
std::vector<std::array<float, 3> > normals;
std::vector<uint8_t> views;
void *kdTree = nullptr;
#ifdef WITH_PDAL
pdal::PointViewPtr pointView = nullptr;
#endif
template <typename T>
inline T *getIndex() {
return kdTree != nullptr ? reinterpret_cast<T *>(kdTree) : buildIndex<T>();
}
template <typename T>
inline T *buildIndex() {
if (kdTree == nullptr) kdTree = static_cast<void *>(new T(3, *this, { KDTREE_MAX_LEAF }));
return reinterpret_cast<T *>(kdTree);
}
inline size_t count() const { return points.size(); }
inline size_t kdtree_get_point_count() const { return points.size(); }
inline float kdtree_get_pt(const size_t idx, const size_t dim) const {
return points[idx][dim];
};
template <class BBOX>
bool kdtree_get_bbox(BBOX & /* bb */) const
{
return false;
}
void appendPoint(PointSet &src, size_t idx) {
points.push_back(src.points[idx]);
colors.push_back(src.colors[idx]);
}
bool hasNormals() const { return normals.size() > 0; }
bool hasColors() const { return colors.size() > 0; }
bool hasViews() const { return views.size() > 0; }
double spacing(int kNeighbors = 3);
template <typename T>
void freeIndex() {
if (kdTree != nullptr) {
T *tree = getIndex<T>();
delete tree;
kdTree = nullptr;
}
}
inline torch::Tensor colorsTensor(){
return torch::from_blob(colors.data(), { static_cast<long int>(colors.size()), 3 }, torch::kU8);
}
inline torch::Tensor pointsTensor(){
return torch::from_blob(points.data(), { static_cast<long int>(points.size()), 3 }, torch::kFloat32);
}
~PointSet() {
}
private:
double m_spacing = -1.0;
};
using KdTree = nanoflann::KDTreeSingleIndexAdaptor<
nanoflann::L2_Simple_Adaptor<float, PointSet>,
PointSet, 3, size_t
>;
std::string getVertexLine(std::ifstream &reader);
size_t getVertexCount(const std::string &line);
inline void checkHeader(std::ifstream &reader, const std::string &prop);
inline bool hasHeader(const std::string &line, const std::string &prop);
template <typename T>
inline T readBinary(std::ifstream &s){
T data;
s.read(reinterpret_cast<char*>(&data), sizeof(T));
return data;
}
PointSet *fastPlyReadPointSet(const std::string &filename);
PointSet *pdalReadPointSet(const std::string &filename);
PointSet *colmapReadPointSet(const std::string &filename);
PointSet *readPointSet(const std::string &filename);
void fastPlySavePointSet(PointSet &pSet, const std::string &filename);
void pdalSavePointSet(PointSet &pSet, const std::string &filename);
void savePointSet(PointSet &pSet, const std::string &filename);
bool fileExists(const std::string &path);
#endif