PrusaSlicer-NonPlainar/src/libslic3r/SLA/SLASupportTreeIGL.cpp

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#include <cmath>
#include "SLA/SLASupportTree.hpp"
#include "SLA/SLABoilerPlate.hpp"
#include "SLA/SLASpatIndex.hpp"
// Workaround: IGL signed_distance.h will define PI in the igl namespace.
#undef PI
// HEAVY headers... takes eternity to compile
// for concave hull merging decisions
#include "SLABoostAdapter.hpp"
#include "boost/geometry/index/rtree.hpp"
#include <igl/ray_mesh_intersect.h>
#include <igl/point_mesh_squared_distance.h>
#include <igl/remove_duplicate_vertices.h>
#include <igl/signed_distance.h>
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#include "SLASpatIndex.hpp"
#include "ClipperUtils.hpp"
namespace Slic3r {
namespace sla {
// Bring back PI from the igl namespace
using igl::PI;
/* **************************************************************************
* SpatIndex implementation
* ************************************************************************** */
class SpatIndex::Impl {
public:
using BoostIndex = boost::geometry::index::rtree< SpatElement,
boost::geometry::index::rstar<16, 4> /* ? */ >;
BoostIndex m_store;
};
SpatIndex::SpatIndex(): m_impl(new Impl()) {}
SpatIndex::~SpatIndex() {}
SpatIndex::SpatIndex(const SpatIndex &cpy): m_impl(new Impl(*cpy.m_impl)) {}
SpatIndex::SpatIndex(SpatIndex&& cpy): m_impl(std::move(cpy.m_impl)) {}
SpatIndex& SpatIndex::operator=(const SpatIndex &cpy)
{
m_impl.reset(new Impl(*cpy.m_impl));
return *this;
}
SpatIndex& SpatIndex::operator=(SpatIndex &&cpy)
{
m_impl.swap(cpy.m_impl);
return *this;
}
void SpatIndex::insert(const SpatElement &el)
{
m_impl->m_store.insert(el);
}
bool SpatIndex::remove(const SpatElement& el)
{
return m_impl->m_store.remove(el) == 1;
}
std::vector<SpatElement>
SpatIndex::query(std::function<bool(const SpatElement &)> fn)
{
namespace bgi = boost::geometry::index;
std::vector<SpatElement> ret;
m_impl->m_store.query(bgi::satisfies(fn), std::back_inserter(ret));
return ret;
}
std::vector<SpatElement> SpatIndex::nearest(const Vec3d &el, unsigned k = 1)
{
namespace bgi = boost::geometry::index;
std::vector<SpatElement> ret; ret.reserve(k);
m_impl->m_store.query(bgi::nearest(el, k), std::back_inserter(ret));
return ret;
}
size_t SpatIndex::size() const
{
return m_impl->m_store.size();
}
/* ****************************************************************************
* EigenMesh3D implementation
* ****************************************************************************/
class EigenMesh3D::AABBImpl: public igl::AABB<Eigen::MatrixXd, 3> {
public:
igl::WindingNumberAABB<Vec3d, Eigen::MatrixXd, Eigen::MatrixXi> windtree;
};
EigenMesh3D::EigenMesh3D(): m_aabb(new AABBImpl()) {}
EigenMesh3D::EigenMesh3D(const TriangleMesh& tmesh): m_aabb(new AABBImpl()) {
static const double dEPS = 1e-6;
const stl_file& stl = tmesh.stl;
auto&& bb = tmesh.bounding_box();
m_ground_level += bb.min(Z);
Eigen::MatrixXd V;
Eigen::MatrixXi F;
V.resize(3*stl.stats.number_of_facets, 3);
F.resize(stl.stats.number_of_facets, 3);
for (unsigned int i = 0; i < stl.stats.number_of_facets; ++i) {
const stl_facet* facet = stl.facet_start+i;
V(3*i+0, 0) = double(facet->vertex[0](0));
V(3*i+0, 1) = double(facet->vertex[0](1));
V(3*i+0, 2) = double(facet->vertex[0](2));
V(3*i+1, 0) = double(facet->vertex[1](0));
V(3*i+1, 1) = double(facet->vertex[1](1));
V(3*i+1, 2) = double(facet->vertex[1](2));
V(3*i+2, 0) = double(facet->vertex[2](0));
V(3*i+2, 1) = double(facet->vertex[2](1));
V(3*i+2, 2) = double(facet->vertex[2](2));
F(i, 0) = int(3*i+0);
F(i, 1) = int(3*i+1);
F(i, 2) = int(3*i+2);
}
// We will convert this to a proper 3d mesh with no duplicate points.
Eigen::VectorXi SVI, SVJ;
igl::remove_duplicate_vertices(V, F, dEPS, m_V, SVI, SVJ, m_F);
// Build the AABB accelaration tree
m_aabb->init(m_V, m_F);
m_aabb->windtree.set_mesh(m_V, m_F);
m_aabb->windtree.init();
}
EigenMesh3D::~EigenMesh3D() {}
EigenMesh3D::EigenMesh3D(const EigenMesh3D &other):
m_V(other.m_V), m_F(other.m_F), m_ground_level(other.m_ground_level),
m_aabb( new AABBImpl(*other.m_aabb) ) {}
EigenMesh3D &EigenMesh3D::operator=(const EigenMesh3D &other)
{
m_V = other.m_V;
m_F = other.m_F;
m_ground_level = other.m_ground_level;
m_aabb.reset(new AABBImpl(*other.m_aabb)); return *this;
}
double EigenMesh3D::query_ray_hit(const Vec3d &s, const Vec3d &dir) const
{
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igl::Hit hit;
hit.t = std::numeric_limits<float>::infinity();
m_aabb->intersect_ray(m_V, m_F, s, dir, hit);
return double(hit.t);
}
std::tuple<double, unsigned, Vec3d>
EigenMesh3D::signed_distance(const Vec3d &/*p*/) const {
// TODO: implement
return std::make_tuple(0.0, 0, Vec3d());
}
bool EigenMesh3D::inside(const Vec3d &p) const {
return m_aabb->windtree.inside(p);
}
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/* ****************************************************************************
* Misc functions
* ****************************************************************************/
bool point_on_edge(const Vec3d& p, const Vec3d& e1, const Vec3d& e2,
double eps = 0.05)
{
using Line3D = Eigen::ParametrizedLine<double, 3>;
auto line = Line3D::Through(e1, e2);
double d = line.distance(p);
return std::abs(d) < eps;
}
template<class Vec> double distance(const Vec& pp1, const Vec& pp2) {
auto p = pp2 - pp1;
return std::sqrt(p.transpose() * p);
}
PointSet normals(const PointSet& points, const EigenMesh3D& mesh,
double eps,
std::function<void()> throw_on_cancel) {
if(points.rows() == 0 || mesh.V().rows() == 0 || mesh.F().rows() == 0)
return {};
Eigen::VectorXd dists;
Eigen::VectorXi I;
PointSet C;
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// We need to remove duplicate vertices and have a true index triangle
// structure
/*
EigenMesh3D mesh;
Eigen::VectorXi SVI, SVJ;
static const double dEPS = 1e-6;
igl::remove_duplicate_vertices(emesh.V, emesh.F, dEPS,
mesh.V, SVI, SVJ, mesh.F);*/
igl::point_mesh_squared_distance( points, mesh.V(), mesh.F(), dists, I, C);
PointSet ret(I.rows(), 3);
for(int i = 0; i < I.rows(); i++) {
throw_on_cancel();
auto idx = I(i);
auto trindex = mesh.F().row(idx);
const Vec3d& p1 = mesh.V().row(trindex(0));
const Vec3d& p2 = mesh.V().row(trindex(1));
const Vec3d& p3 = mesh.V().row(trindex(2));
// We should check if the point lies on an edge of the hosting triangle.
// If it does than all the other triangles using the same two points
// have to be searched and the final normal should be some kind of
// aggregation of the participating triangle normals. We should also
// consider the cases where the support point lies right on a vertex
// of its triangle. The procedure is the same, get the neighbor
// triangles and calculate an average normal.
const Vec3d& p = C.row(i);
// mark the vertex indices of the edge. ia and ib marks and edge ic
// will mark a single vertex.
int ia = -1, ib = -1, ic = -1;
if(std::abs(distance(p, p1)) < eps) {
ic = trindex(0);
}
else if(std::abs(distance(p, p2)) < eps) {
ic = trindex(1);
}
else if(std::abs(distance(p, p3)) < eps) {
ic = trindex(2);
}
else if(point_on_edge(p, p1, p2, eps)) {
ia = trindex(0); ib = trindex(1);
}
else if(point_on_edge(p, p2, p3, eps)) {
ia = trindex(1); ib = trindex(2);
}
else if(point_on_edge(p, p1, p3, eps)) {
ia = trindex(0); ib = trindex(2);
}
// vector for the neigboring triangles including the detected one.
std::vector<Vec3i> neigh;
if(ic >= 0) { // The point is right on a vertex of the triangle
for(int n = 0; n < mesh.F().rows(); ++n) {
throw_on_cancel();
Vec3i ni = mesh.F().row(n);
if((ni(X) == ic || ni(Y) == ic || ni(Z) == ic))
neigh.emplace_back(ni);
}
}
else if(ia >= 0 && ib >= 0) { // the point is on and edge
// now get all the neigboring triangles
for(int n = 0; n < mesh.F().rows(); ++n) {
throw_on_cancel();
Vec3i ni = mesh.F().row(n);
if((ni(X) == ia || ni(Y) == ia || ni(Z) == ia) &&
(ni(X) == ib || ni(Y) == ib || ni(Z) == ib))
neigh.emplace_back(ni);
}
}
// Calculate the normals for the neighboring triangles
std::vector<Vec3d> neighnorms; neighnorms.reserve(neigh.size());
for(const Vec3i& tri : neigh) {
const Vec3d& pt1 = mesh.V().row(tri(0));
const Vec3d& pt2 = mesh.V().row(tri(1));
const Vec3d& pt3 = mesh.V().row(tri(2));
Eigen::Vector3d U = pt2 - pt1;
Eigen::Vector3d V = pt3 - pt1;
neighnorms.emplace_back(U.cross(V).normalized());
}
// Throw out duplicates. They would cause trouble with summing. We will
// use std::unique which works on sorted ranges. We will sort by the
// coefficient-wise sum of the normals. It should force the same
// elements to be consecutive.
std::sort(neighnorms.begin(), neighnorms.end(),
[](const Vec3d& v1, const Vec3d& v2){
return v1.sum() < v2.sum();
});
auto lend = std::unique(neighnorms.begin(), neighnorms.end(),
[](const Vec3d& n1, const Vec3d& n2) {
// Compare normals for equivalence. This is controvers stuff.
auto deq = [](double a, double b) { return std::abs(a-b) < 1e-3; };
return deq(n1(X), n2(X)) && deq(n1(Y), n2(Y)) && deq(n1(Z), n2(Z));
});
if(!neighnorms.empty()) { // there were neighbors to count with
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// sum up the normals and then normalize the result again.
// This unification seems to be enough.
Vec3d sumnorm(0, 0, 0);
sumnorm = std::accumulate(neighnorms.begin(), lend, sumnorm);
sumnorm.normalize();
ret.row(i) = sumnorm;
}
else { // point lies safely within its triangle
Eigen::Vector3d U = p2 - p1;
Eigen::Vector3d V = p3 - p1;
ret.row(i) = U.cross(V).normalized();
}
}
return ret;
}
// Clustering a set of points by the given criteria
ClusteredPoints cluster(
const sla::PointSet& points,
std::function<bool(const SpatElement&, const SpatElement&)> pred,
unsigned max_points = 0)
{
namespace bgi = boost::geometry::index;
using Index3D = bgi::rtree< SpatElement, bgi::rstar<16, 4> /* ? */ >;
// A spatial index for querying the nearest points
Index3D sindex;
// Build the index
for(unsigned idx = 0; idx < points.rows(); idx++)
sindex.insert( std::make_pair(points.row(idx), idx));
using Elems = std::vector<SpatElement>;
// Recursive function for visiting all the points in a given distance to
// each other
std::function<void(Elems&, Elems&)> group =
[&sindex, &group, pred, max_points](Elems& pts, Elems& cluster)
{
for(auto& p : pts) {
std::vector<SpatElement> tmp;
sindex.query(
bgi::satisfies([p, pred](const SpatElement& se) {
return pred(p, se);
}),
std::back_inserter(tmp)
);
auto cmp = [](const SpatElement& e1, const SpatElement& e2){
return e1.second < e2.second;
};
std::sort(tmp.begin(), tmp.end(), cmp);
Elems newpts;
std::set_difference(tmp.begin(), tmp.end(),
cluster.begin(), cluster.end(),
std::back_inserter(newpts), cmp);
int c = max_points && newpts.size() + cluster.size() > max_points?
int(max_points - cluster.size()) : int(newpts.size());
cluster.insert(cluster.end(), newpts.begin(), newpts.begin() + c);
std::sort(cluster.begin(), cluster.end(), cmp);
if(!newpts.empty() && (!max_points || cluster.size() < max_points))
group(newpts, cluster);
}
};
std::vector<Elems> clusters;
for(auto it = sindex.begin(); it != sindex.end();) {
Elems cluster = {};
Elems pts = {*it};
group(pts, cluster);
for(auto& c : cluster) sindex.remove(c);
it = sindex.begin();
clusters.emplace_back(cluster);
}
ClusteredPoints result;
for(auto& cluster : clusters) {
result.emplace_back();
for(auto c : cluster) result.back().emplace_back(c.second);
}
return result;
}
}
}