Least supports optimization revived.

Fix missing include on Win32


Cleanup benchmarking code
This commit is contained in:
tamasmeszaros 2021-03-19 10:01:50 +01:00
parent 0194094afa
commit f3e3aabec7
4 changed files with 281 additions and 19 deletions

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@ -11,16 +11,16 @@
#include "libslic3r/PrintConfig.hpp"
#include <libslic3r/Geometry.hpp>
#include "Model.hpp"
#include <thread>
#include <libnest2d/tools/benchmark.h>
namespace Slic3r { namespace sla {
namespace {
inline const Vec3f DOWN = {0.f, 0.f, -1.f};
constexpr double POINTS_PER_UNIT_AREA = 1.f;
// Get the vertices of a triangle directly in an array of 3 points
std::array<Vec3f, 3> get_triangle_vertices(const TriangleMesh &mesh,
size_t faceidx)
@ -54,11 +54,11 @@ T sum_score(AccessFn &&accessfn, size_t facecount, size_t Nthreads)
size_t grainsize = facecount / Nthreads;
size_t from = 0, to = facecount;
return execution::reduce(ex_seq, from, to, initv, mergefn, accessfn, grainsize);
return execution::reduce(ex_tbb, from, to, initv, mergefn, accessfn, grainsize);
}
// Try to guess the number of support points needed to support a mesh
double get_model_supportedness(const TriangleMesh &mesh, const Transform3f &tr)
double get_misalginment_score(const TriangleMesh &mesh, const Transform3f &tr)
{
if (mesh.its.vertices.empty()) return std::nan("");
@ -78,6 +78,100 @@ double get_model_supportedness(const TriangleMesh &mesh, const Transform3f &tr)
return S / facecount;
}
// Get area and normal of a triangle
struct Facestats {
Vec3f normal;
double area;
explicit Facestats(const std::array<Vec3f, 3> &triangle)
{
Vec3f U = triangle[1] - triangle[0];
Vec3f V = triangle[2] - triangle[0];
Vec3f C = U.cross(V);
normal = C.normalized();
area = 0.5 * C.norm();
}
};
// The score function for a particular face
inline double get_supportedness_score(const Facestats &fc)
{
// Simply get the angle (acos of dot product) between the face normal and
// the DOWN vector.
float phi = 1. - std::acos(fc.normal.dot(DOWN)) / float(PI);
// Only consider faces that have have slopes below 90 deg:
phi = phi * (phi > 0.5);
// Make the huge slopes more significant than the smaller slopes
phi = phi * phi * phi;
// Multiply with the area of the current face
return fc.area * POINTS_PER_UNIT_AREA * phi;
}
// Try to guess the number of support points needed to support a mesh
double get_supportedness_score(const TriangleMesh &mesh, const Transform3f &tr)
{
if (mesh.its.vertices.empty()) return std::nan("");
auto accessfn = [&mesh, &tr](size_t fi) {
Facestats fc{get_transformed_triangle(mesh, tr, fi)};
return get_supportedness_score(fc);
};
size_t facecount = mesh.its.indices.size();
size_t Nthreads = std::thread::hardware_concurrency();
double S = unscaled(sum_score<int_fast64_t>(accessfn, facecount, Nthreads));
return S / facecount;
}
// Find transformed mesh ground level without copy and with parallel reduce.
float find_ground_level(const TriangleMesh &mesh,
const Transform3f & tr,
size_t threads)
{
size_t vsize = mesh.its.vertices.size();
auto minfn = [](float a, float b) { return std::min(a, b); };
auto accessfn = [&mesh, &tr] (size_t vi) {
return (tr * mesh.its.vertices[vi]).z();
};
auto zmin = std::numeric_limits<float>::max();
size_t granularity = vsize / threads;
return execution::reduce(ex_tbb, size_t(0), vsize, zmin, minfn, accessfn, granularity);
}
float get_supportedness_onfloor_score(const TriangleMesh &mesh,
const Transform3f & tr)
{
if (mesh.its.vertices.empty()) return std::nan("");
size_t Nthreads = std::thread::hardware_concurrency();
float zmin = find_ground_level(mesh, tr, Nthreads);
float zlvl = zmin + 0.1f; // Set up a slight tolerance from z level
auto accessfn = [&mesh, &tr, zlvl](size_t fi) {
std::array<Vec3f, 3> tri = get_transformed_triangle(mesh, tr, fi);
Facestats fc{tri};
if (tri[0].z() <= zlvl && tri[1].z() <= zlvl && tri[2].z() <= zlvl)
return -fc.area * POINTS_PER_UNIT_AREA;
return get_supportedness_score(fc);
};
size_t facecount = mesh.its.indices.size();
double S = unscaled(sum_score<int_fast64_t>(accessfn, facecount, Nthreads));
return S / facecount;
}
using XYRotation = std::array<double, 2>;
// prepare the rotation transformation
@ -90,13 +184,107 @@ Transform3f to_transform3f(const XYRotation &rot)
return rt;
}
XYRotation from_transform3f(const Transform3f &tr)
{
Vec3d rot3 = Geometry::Transformation{tr.cast<double>()}.get_rotation();
return {rot3.x(), rot3.y()};
}
inline bool is_on_floor(const SLAPrintObject &mo)
{
auto opt_elevation = mo.config().support_object_elevation.getFloat();
auto opt_padaround = mo.config().pad_around_object.getBool();
return opt_elevation < EPSILON || opt_padaround;
}
// collect the rotations for each face of the convex hull
std::vector<XYRotation> get_chull_rotations(const TriangleMesh &mesh, size_t max_count)
{
TriangleMesh chull = mesh.convex_hull_3d();
chull.require_shared_vertices();
double chull2d_area = chull.convex_hull().area();
double area_threshold = chull2d_area / (scaled<double>(1e3) * scaled(1.));
size_t facecount = chull.its.indices.size();
struct RotArea { XYRotation rot; double area; };
auto inputs = reserve_vector<RotArea>(facecount);
auto rotcmp = [](const RotArea &r1, const RotArea &r2) {
double xdiff = r1.rot[X] - r2.rot[X], ydiff = r1.rot[Y] - r2.rot[Y];
return std::abs(xdiff) < EPSILON ? ydiff < 0. : xdiff < 0.;
};
auto eqcmp = [](const XYRotation &r1, const XYRotation &r2) {
double xdiff = r1[X] - r2[X], ydiff = r1[Y] - r2[Y];
return std::abs(xdiff) < EPSILON && std::abs(ydiff) < EPSILON;
};
for (size_t fi = 0; fi < facecount; ++fi) {
Facestats fc{get_triangle_vertices(chull, fi)};
if (fc.area > area_threshold) {
auto q = Eigen::Quaternionf{}.FromTwoVectors(fc.normal, DOWN);
XYRotation rot = from_transform3f(Transform3f::Identity() * q);
RotArea ra = {rot, fc.area};
auto it = std::lower_bound(inputs.begin(), inputs.end(), ra, rotcmp);
if (it == inputs.end() || !eqcmp(it->rot, rot))
inputs.insert(it, ra);
}
}
inputs.shrink_to_fit();
if (!max_count) max_count = inputs.size();
std::sort(inputs.begin(), inputs.end(),
[](const RotArea &ra, const RotArea &rb) {
return ra.area > rb.area;
});
auto ret = reserve_vector<XYRotation>(std::min(max_count, inputs.size()));
for (const RotArea &ra : inputs) ret.emplace_back(ra.rot);
return ret;
}
// Find the best score from a set of function inputs. Evaluate for every point.
template<size_t N, class Fn, class It, class StopCond>
std::array<double, N> find_min_score(Fn &&fn, It from, It to, StopCond &&stopfn)
{
std::array<double, N> ret = {};
double score = std::numeric_limits<double>::max();
size_t Nthreads = std::thread::hardware_concurrency();
size_t dist = std::distance(from, to);
std::vector<double> scores(dist, score);
execution::for_each(
ex_tbb, size_t(0), dist, [&stopfn, &scores, &fn, &from](size_t i) {
if (stopfn()) return;
scores[i] = fn(*(from + i));
},
dist / Nthreads);
auto it = std::min_element(scores.begin(), scores.end());
if (it != scores.end())
ret = *(from + std::distance(scores.begin(), it));
return ret;
}
} // namespace
Vec2d find_best_misalignment_rotation(const SLAPrintObject & po,
float accuracy,
std::function<bool(int)> statuscb)
RotOptimizeStatusCB statuscb)
{
static const unsigned MAX_TRIES = 1000;
static constexpr unsigned MAX_TRIES = 1000;
// return value
XYRotation rot;
@ -136,22 +324,91 @@ Vec2d find_best_misalignment_rotation(const SLAPrintObject & po,
// We can specify the bounds for a dimension in the following way:
auto bounds = opt::bounds({ {-PI/2, PI/2}, {-PI/2, PI/2} });
Benchmark bench;
bench.start();
auto result = solver.to_max().optimize(
[&mesh, &statusfn] (const XYRotation &rot)
{
statusfn();
return get_model_supportedness(mesh, to_transform3f(rot));
return get_misalginment_score(mesh, to_transform3f(rot));
}, opt::initvals({0., 0.}), bounds);
bench.stop();
rot = result.optimum;
std::cout << "Optimum score: " << result.score << std::endl;
std::cout << "Optimum rotation: " << result.optimum[0] << " " << result.optimum[1] << std::endl;
std::cout << "Optimization took: " << bench.getElapsedSec() << " seconds" << std::endl;
return {rot[0], rot[1]};
}
Vec2d find_least_supports_rotation(const SLAPrintObject & po,
float accuracy,
RotOptimizeStatusCB statuscb)
{
static const unsigned MAX_TRIES = 1000;
// return value
XYRotation rot;
// We will use only one instance of this converted mesh to examine different
// rotations
TriangleMesh mesh = po.model_object()->raw_mesh();
mesh.require_shared_vertices();
// To keep track of the number of iterations
unsigned status = 0;
// The maximum number of iterations
auto max_tries = unsigned(accuracy * MAX_TRIES);
// call status callback with zero, because we are at the start
statuscb(status);
auto statusfn = [&statuscb, &status, &max_tries] {
// report status
statuscb(unsigned(++status * 100.0/max_tries) );
};
auto stopcond = [&statuscb] {
return ! statuscb(-1);
};
// Different search methods have to be used depending on the model elevation
if (is_on_floor(po)) {
std::vector<XYRotation> inputs = get_chull_rotations(mesh, max_tries);
max_tries = inputs.size();
// If the model can be placed on the bed directly, we only need to
// check the 3D convex hull face rotations.
auto objfn = [&mesh, &statusfn](const XYRotation &rot) {
statusfn();
Transform3f tr = to_transform3f(rot);
return get_supportedness_onfloor_score(mesh, tr);
};
rot = find_min_score<2>(objfn, inputs.begin(), inputs.end(), stopcond);
} else {
// Preparing the optimizer.
size_t gridsize = std::sqrt(max_tries); // 2D grid has gridsize^2 calls
opt::Optimizer<opt::AlgBruteForce> solver(opt::StopCriteria{}
.max_iterations(max_tries)
.stop_condition(stopcond),
gridsize);
// We are searching rotations around only two axes x, y. Thus the
// problem becomes a 2 dimensional optimization task.
// We can specify the bounds for a dimension in the following way:
auto bounds = opt::bounds({ {-PI, PI}, {-PI, PI} });
auto result = solver.to_min().optimize(
[&mesh, &statusfn] (const XYRotation &rot)
{
statusfn();
return get_supportedness_score(mesh, to_transform3f(rot));
}, opt::initvals({0., 0.}), bounds);
// Save the result
rot = result.optimum;
}
return {rot[0], rot[1]};
}

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@ -37,7 +37,11 @@ Vec2d find_best_misalignment_rotation(
RotOptimizeStatusCB statuscb = [] (int) { return true; }
);
Vec2d find_least_supports_rotation(
const SLAPrintObject& modelobj,
float accuracy = 1.0f,
RotOptimizeStatusCB statuscb = [] (int) { return true; }
);
} // namespace sla
} // namespace Slic3r

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@ -21,7 +21,7 @@ class RotoptimizeJob : public PlaterJob
static inline const FindMethod Methods[] = {
{ L("Best misalignment"), sla::find_best_misalignment_rotation },
{ L("Least supports"), sla::find_best_misalignment_rotation }
{ L("Least supports"), sla::find_least_supports_rotation }
};
size_t m_method_id = 0;

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@ -1,6 +1,7 @@
#include <unordered_set>
#include <unordered_map>
#include <random>
#include <numeric>
#include <cstdint>
#include "sla_test_utils.hpp"