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rotation finder experiments

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This commit is contained in:
tamasmeszaros
2020-08-26 10:25:09 +02:00
parent 8e490c7e56
commit dce0053631
4 changed files with 108 additions and 54 deletions
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1
src/libslic3r/Optimizer.hpp
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@@ -368,6 +368,7 @@ template<size_t N> auto score_gradient(double s, const double (&grad)[N])
using AlgNLoptGenetic = detail::NLoptAlgComb<NLOPT_GN_ESCH>;
using AlgNLoptSubplex = detail::NLoptAlg<NLOPT_LN_SBPLX>;
using AlgNLoptSimplex = detail::NLoptAlg<NLOPT_LN_NELDERMEAD>;
using AlgNLoptDIRECT = detail::NLoptAlg<NLOPT_GN_DIRECT>;
// TODO: define others if needed...

155
src/libslic3r/SLA/Rotfinder.cpp
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@@ -1,33 +1,113 @@
#include <limits>
#include <exception>
#include <libnest2d/optimizers/nlopt/genetic.hpp>
//#include <libnest2d/optimizers/nlopt/genetic.hpp>
#include <libslic3r/Optimizer.hpp>
#include <libslic3r/SLA/Rotfinder.hpp>
#include <libslic3r/SLA/SupportTree.hpp>
#include <libslic3r/SLA/SupportPointGenerator.hpp>
#include <libslic3r/SimplifyMesh.hpp>
#include "Model.hpp"
namespace Slic3r {
namespace sla {
std::array<double, 3> find_best_rotation(const ModelObject& modelobj,
double area(const Vec3d &p1, const Vec3d &p2, const Vec3d &p3) {
Vec3d a = p2 - p1;
Vec3d b = p3 - p1;
Vec3d c = a.cross(b);
return 0.5 * c.norm();
}
using VertexFaceMap = std::vector<std::vector<size_t>>;
VertexFaceMap create_vertex_face_map(const TriangleMesh &mesh) {
std::vector<std::vector<size_t>> vmap(mesh.its.vertices.size());
size_t fi = 0;
for (const Vec3i &tri : mesh.its.indices) {
for (int vi = 0; vi < tri.size(); ++vi) {
auto from = vmap[tri(vi)].begin(), to = vmap[tri(vi)].end();
vmap[tri(vi)].insert(std::lower_bound(from, to, fi), fi);
}
}
return vmap;
}
// Try to guess the number of support points needed to support a mesh
double calculate_model_supportedness(const TriangleMesh & mesh,
const VertexFaceMap &vmap,
const Transform3d & tr)
{
static const double POINTS_PER_UNIT_AREA = 1.;
static const Vec3d DOWN = {0., 0., -1.};
double score = 0.;
// double zmin = mesh.bounding_box().min.z();
// std::vector<Vec3d> normals(mesh.its.indices.size(), Vec3d::Zero());
double zmin = 0;
for (auto & v : mesh.its.vertices)
zmin = std::min(zmin, double((tr * v.cast<double>()).z()));
for (size_t fi = 0; fi < mesh.its.indices.size(); ++fi) {
const auto &face = mesh.its.indices[fi];
Vec3d p1 = tr * mesh.its.vertices[face(0)].cast<double>();
Vec3d p2 = tr * mesh.its.vertices[face(1)].cast<double>();
Vec3d p3 = tr * mesh.its.vertices[face(2)].cast<double>();
// auto triang = std::array<Vec3d, 3> {p1, p2, p3};
// double a = area(triang.begin(), triang.end());
double a = area(p1, p2, p3);
double zlvl = zmin + 0.1;
if (p1.z() <= zlvl && p2.z() <= zlvl && p3.z() <= zlvl) {
score += a * POINTS_PER_UNIT_AREA;
continue;
}
Eigen::Vector3d U = p2 - p1;
Eigen::Vector3d V = p3 - p1;
Vec3d N = U.cross(V).normalized();
double phi = std::acos(N.dot(DOWN)) / PI;
std::cout << "area: " << a << std::endl;
score += a * POINTS_PER_UNIT_AREA * phi;
// normals[fi] = N;
}
// for (size_t vi = 0; vi < mesh.its.vertices.size(); ++vi) {
// const std::vector<size_t> &neighbors = vmap[vi];
// const auto &v = mesh.its.vertices[vi];
// Vec3d vt = tr * v.cast<double>();
// }
return score;
}
std::array<double, 2> find_best_rotation(const ModelObject& modelobj,
float accuracy,
std::function<void(unsigned)> statuscb,
std::function<bool()> stopcond)
{
using libnest2d::opt::Method;
using libnest2d::opt::bound;
using libnest2d::opt::Optimizer;
using libnest2d::opt::TOptimizer;
using libnest2d::opt::StopCriteria;
static const unsigned MAX_TRIES = 100000;
static const unsigned MAX_TRIES = 1000000;
// return value
std::array<double, 3> rot;
std::array<double, 2> rot;
// We will use only one instance of this converted mesh to examine different
// rotations
const TriangleMesh& mesh = modelobj.raw_mesh();
TriangleMesh mesh = modelobj.raw_mesh();
mesh.require_shared_vertices();
// auto vmap = create_vertex_face_map(mesh);
// simplify_mesh(mesh);
// For current iteration number
unsigned status = 0;
@@ -44,40 +124,15 @@ std::array<double, 3> find_best_rotation(const ModelObject& modelobj,
// the same for subsequent iterations (status goes from 0 to 100 but
// iterations can be many more)
auto objfunc = [&mesh, &status, &statuscb, &stopcond, max_tries]
(double rx, double ry, double rz)
(const opt::Input<2> &in)
{
const TriangleMesh& m = mesh;
// prepare the rotation transformation
Transform3d rt = Transform3d::Identity();
rt.rotate(Eigen::AngleAxisd(in[1], Vec3d::UnitY()));
rt.rotate(Eigen::AngleAxisd(in[0], Vec3d::UnitX()));
rt.rotate(Eigen::AngleAxisd(rz, Vec3d::UnitZ()));
rt.rotate(Eigen::AngleAxisd(ry, Vec3d::UnitY()));
rt.rotate(Eigen::AngleAxisd(rx, Vec3d::UnitX()));
double score = 0;
// For all triangles we calculate the normal and sum up the dot product
// (a scalar indicating how much are two vectors aligned) with each axis
// this will result in a value that is greater if a normal is aligned
// with all axes. If the normal is aligned than the triangle itself is
// orthogonal to the axes and that is good for print quality.
// TODO: some applications optimize for minimum z-axis cross section
// area. The current function is only an example of how to optimize.
// Later we can add more criteria like the number of overhangs, etc...
for(size_t i = 0; i < m.stl.facet_start.size(); i++) {
Vec3d n = m.stl.facet_start[i].normal.cast<double>();
// rotate the normal with the current rotation given by the solver
n = rt * n;
// We should score against the alignment with the reference planes
score += std::abs(n.dot(Vec3d::UnitX()));
score += std::abs(n.dot(Vec3d::UnitY()));
score += std::abs(n.dot(Vec3d::UnitZ()));
}
double score = sla::calculate_model_supportedness(mesh, {}, rt);
std::cout << score << std::endl;
// report status
if(!stopcond()) statuscb( unsigned(++status * 100.0/max_tries) );
@@ -86,26 +141,24 @@ std::array<double, 3> find_best_rotation(const ModelObject& modelobj,
};
// Firing up the genetic optimizer. For now it uses the nlopt library.
StopCriteria stc;
stc.max_iterations = max_tries;
stc.relative_score_difference = 1e-3;
stc.stop_condition = stopcond; // stop when stopcond returns true
TOptimizer<Method::G_GENETIC> solver(stc);
opt::Optimizer<opt::AlgNLoptDIRECT> solver(opt::StopCriteria{}
.max_iterations(max_tries)
.rel_score_diff(1e-3)
.stop_condition(stopcond));
// We are searching rotations around the three axes x, y, z. Thus the
// problem becomes a 3 dimensional optimization task.
// We can specify the bounds for a dimension in the following way:
auto b = bound(-PI/2, PI/2);
auto b = opt::Bound{-PI, PI};
// Now we start the optimization process with initial angles (0, 0, 0)
auto result = solver.optimize_max(objfunc,
libnest2d::opt::initvals(0.0, 0.0, 0.0),
b, b, b);
auto result = solver.to_max().optimize(objfunc, opt::initvals({0.0, 0.0}),
opt::bounds({b, b}));
// Save the result and fck off
rot[0] = std::get<0>(result.optimum);
rot[1] = std::get<1>(result.optimum);
rot[2] = std::get<2>(result.optimum);
return rot;
}

2
src/libslic3r/SLA/Rotfinder.hpp
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@@ -25,7 +25,7 @@ namespace sla {
*
* @return Returns the rotations around each axis (x, y, z)
*/
std::array<double, 3> find_best_rotation(
std::array<double, 2> find_best_rotation(
const ModelObject& modelobj,
float accuracy = 1.0f,
std::function<void(unsigned)> statuscb = [] (unsigned) {},

4
src/slic3r/GUI/Jobs/RotoptimizeJob.cpp
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@@ -18,7 +18,7 @@ void RotoptimizeJob::process()
auto r = sla::find_best_rotation(
*o,
.005f,
1.f,
[this](unsigned s) {
if (s < 100)
update_status(int(s),
@@ -31,7 +31,7 @@ void RotoptimizeJob::process()
if (!was_canceled()) {
for(ModelInstance * oi : o->instances) {
oi->set_rotation({r[X], r[Y], r[Z]});
oi->set_rotation({r[X], r[Y], 0.});
auto trmatrix = oi->get_transformation().get_matrix();
Polygon trchull = o->convex_hull_2d(trmatrix);