Least supports optimization revived.
Fix missing include on Win32 Cleanup benchmarking code
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tamasmeszaros
parent
0194094afa
commit
f3e3aabec7
@ -11,16 +11,16 @@
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#include "libslic3r/PrintConfig.hpp"
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#include <libslic3r/Geometry.hpp>
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#include "Model.hpp"
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#include <thread>
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#include <libnest2d/tools/benchmark.h>
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namespace Slic3r { namespace sla {
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namespace {
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inline const Vec3f DOWN = {0.f, 0.f, -1.f};
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constexpr double POINTS_PER_UNIT_AREA = 1.f;
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// Get the vertices of a triangle directly in an array of 3 points
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std::array<Vec3f, 3> get_triangle_vertices(const TriangleMesh &mesh,
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size_t faceidx)
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@ -54,11 +54,11 @@ T sum_score(AccessFn &&accessfn, size_t facecount, size_t Nthreads)
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size_t grainsize = facecount / Nthreads;
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size_t from = 0, to = facecount;
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return execution::reduce(ex_seq, from, to, initv, mergefn, accessfn, grainsize);
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return execution::reduce(ex_tbb, from, to, initv, mergefn, accessfn, grainsize);
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}
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// Try to guess the number of support points needed to support a mesh
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double get_model_supportedness(const TriangleMesh &mesh, const Transform3f &tr)
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double get_misalginment_score(const TriangleMesh &mesh, const Transform3f &tr)
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{
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if (mesh.its.vertices.empty()) return std::nan("");
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@ -78,6 +78,100 @@ double get_model_supportedness(const TriangleMesh &mesh, const Transform3f &tr)
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return S / facecount;
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}
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// Get area and normal of a triangle
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struct Facestats {
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Vec3f normal;
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double area;
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explicit Facestats(const std::array<Vec3f, 3> &triangle)
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{
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Vec3f U = triangle[1] - triangle[0];
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Vec3f V = triangle[2] - triangle[0];
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Vec3f C = U.cross(V);
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normal = C.normalized();
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area = 0.5 * C.norm();
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}
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};
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// The score function for a particular face
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inline double get_supportedness_score(const Facestats &fc)
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{
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// Simply get the angle (acos of dot product) between the face normal and
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// the DOWN vector.
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float phi = 1. - std::acos(fc.normal.dot(DOWN)) / float(PI);
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// Only consider faces that have have slopes below 90 deg:
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phi = phi * (phi > 0.5);
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// Make the huge slopes more significant than the smaller slopes
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phi = phi * phi * phi;
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// Multiply with the area of the current face
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return fc.area * POINTS_PER_UNIT_AREA * phi;
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}
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// Try to guess the number of support points needed to support a mesh
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double get_supportedness_score(const TriangleMesh &mesh, const Transform3f &tr)
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{
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if (mesh.its.vertices.empty()) return std::nan("");
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auto accessfn = [&mesh, &tr](size_t fi) {
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Facestats fc{get_transformed_triangle(mesh, tr, fi)};
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return get_supportedness_score(fc);
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};
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size_t facecount = mesh.its.indices.size();
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size_t Nthreads = std::thread::hardware_concurrency();
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double S = unscaled(sum_score<int_fast64_t>(accessfn, facecount, Nthreads));
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return S / facecount;
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}
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// Find transformed mesh ground level without copy and with parallel reduce.
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float find_ground_level(const TriangleMesh &mesh,
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const Transform3f & tr,
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size_t threads)
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{
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size_t vsize = mesh.its.vertices.size();
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auto minfn = [](float a, float b) { return std::min(a, b); };
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auto accessfn = [&mesh, &tr] (size_t vi) {
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return (tr * mesh.its.vertices[vi]).z();
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};
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auto zmin = std::numeric_limits<float>::max();
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size_t granularity = vsize / threads;
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return execution::reduce(ex_tbb, size_t(0), vsize, zmin, minfn, accessfn, granularity);
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}
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float get_supportedness_onfloor_score(const TriangleMesh &mesh,
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const Transform3f & tr)
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{
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if (mesh.its.vertices.empty()) return std::nan("");
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size_t Nthreads = std::thread::hardware_concurrency();
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float zmin = find_ground_level(mesh, tr, Nthreads);
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float zlvl = zmin + 0.1f; // Set up a slight tolerance from z level
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auto accessfn = [&mesh, &tr, zlvl](size_t fi) {
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std::array<Vec3f, 3> tri = get_transformed_triangle(mesh, tr, fi);
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Facestats fc{tri};
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if (tri[0].z() <= zlvl && tri[1].z() <= zlvl && tri[2].z() <= zlvl)
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return -fc.area * POINTS_PER_UNIT_AREA;
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return get_supportedness_score(fc);
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};
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size_t facecount = mesh.its.indices.size();
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double S = unscaled(sum_score<int_fast64_t>(accessfn, facecount, Nthreads));
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return S / facecount;
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}
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using XYRotation = std::array<double, 2>;
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// prepare the rotation transformation
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@ -90,13 +184,107 @@ Transform3f to_transform3f(const XYRotation &rot)
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return rt;
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}
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XYRotation from_transform3f(const Transform3f &tr)
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{
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Vec3d rot3 = Geometry::Transformation{tr.cast<double>()}.get_rotation();
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return {rot3.x(), rot3.y()};
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}
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inline bool is_on_floor(const SLAPrintObject &mo)
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{
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auto opt_elevation = mo.config().support_object_elevation.getFloat();
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auto opt_padaround = mo.config().pad_around_object.getBool();
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return opt_elevation < EPSILON || opt_padaround;
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}
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// collect the rotations for each face of the convex hull
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std::vector<XYRotation> get_chull_rotations(const TriangleMesh &mesh, size_t max_count)
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{
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TriangleMesh chull = mesh.convex_hull_3d();
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chull.require_shared_vertices();
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double chull2d_area = chull.convex_hull().area();
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double area_threshold = chull2d_area / (scaled<double>(1e3) * scaled(1.));
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size_t facecount = chull.its.indices.size();
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struct RotArea { XYRotation rot; double area; };
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auto inputs = reserve_vector<RotArea>(facecount);
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auto rotcmp = [](const RotArea &r1, const RotArea &r2) {
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double xdiff = r1.rot[X] - r2.rot[X], ydiff = r1.rot[Y] - r2.rot[Y];
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return std::abs(xdiff) < EPSILON ? ydiff < 0. : xdiff < 0.;
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};
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auto eqcmp = [](const XYRotation &r1, const XYRotation &r2) {
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double xdiff = r1[X] - r2[X], ydiff = r1[Y] - r2[Y];
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return std::abs(xdiff) < EPSILON && std::abs(ydiff) < EPSILON;
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};
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for (size_t fi = 0; fi < facecount; ++fi) {
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Facestats fc{get_triangle_vertices(chull, fi)};
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if (fc.area > area_threshold) {
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auto q = Eigen::Quaternionf{}.FromTwoVectors(fc.normal, DOWN);
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XYRotation rot = from_transform3f(Transform3f::Identity() * q);
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RotArea ra = {rot, fc.area};
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auto it = std::lower_bound(inputs.begin(), inputs.end(), ra, rotcmp);
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if (it == inputs.end() || !eqcmp(it->rot, rot))
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inputs.insert(it, ra);
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}
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}
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inputs.shrink_to_fit();
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if (!max_count) max_count = inputs.size();
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std::sort(inputs.begin(), inputs.end(),
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[](const RotArea &ra, const RotArea &rb) {
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return ra.area > rb.area;
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});
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auto ret = reserve_vector<XYRotation>(std::min(max_count, inputs.size()));
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for (const RotArea &ra : inputs) ret.emplace_back(ra.rot);
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return ret;
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}
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// Find the best score from a set of function inputs. Evaluate for every point.
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template<size_t N, class Fn, class It, class StopCond>
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std::array<double, N> find_min_score(Fn &&fn, It from, It to, StopCond &&stopfn)
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{
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std::array<double, N> ret = {};
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double score = std::numeric_limits<double>::max();
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size_t Nthreads = std::thread::hardware_concurrency();
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size_t dist = std::distance(from, to);
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std::vector<double> scores(dist, score);
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execution::for_each(
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ex_tbb, size_t(0), dist, [&stopfn, &scores, &fn, &from](size_t i) {
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if (stopfn()) return;
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scores[i] = fn(*(from + i));
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},
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dist / Nthreads);
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auto it = std::min_element(scores.begin(), scores.end());
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if (it != scores.end())
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ret = *(from + std::distance(scores.begin(), it));
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return ret;
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}
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} // namespace
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Vec2d find_best_misalignment_rotation(const SLAPrintObject & po,
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float accuracy,
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std::function<bool(int)> statuscb)
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Vec2d find_best_misalignment_rotation(const SLAPrintObject & po,
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float accuracy,
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RotOptimizeStatusCB statuscb)
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{
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static const unsigned MAX_TRIES = 1000;
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static constexpr unsigned MAX_TRIES = 1000;
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// return value
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XYRotation rot;
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@ -136,22 +324,91 @@ Vec2d find_best_misalignment_rotation(const SLAPrintObject & po,
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// We can specify the bounds for a dimension in the following way:
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auto bounds = opt::bounds({ {-PI/2, PI/2}, {-PI/2, PI/2} });
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Benchmark bench;
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bench.start();
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auto result = solver.to_max().optimize(
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[&mesh, &statusfn] (const XYRotation &rot)
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{
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statusfn();
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return get_model_supportedness(mesh, to_transform3f(rot));
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return get_misalginment_score(mesh, to_transform3f(rot));
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}, opt::initvals({0., 0.}), bounds);
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bench.stop();
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rot = result.optimum;
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std::cout << "Optimum score: " << result.score << std::endl;
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std::cout << "Optimum rotation: " << result.optimum[0] << " " << result.optimum[1] << std::endl;
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std::cout << "Optimization took: " << bench.getElapsedSec() << " seconds" << std::endl;
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return {rot[0], rot[1]};
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}
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Vec2d find_least_supports_rotation(const SLAPrintObject & po,
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float accuracy,
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RotOptimizeStatusCB statuscb)
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{
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static const unsigned MAX_TRIES = 1000;
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// return value
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XYRotation rot;
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// We will use only one instance of this converted mesh to examine different
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// rotations
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TriangleMesh mesh = po.model_object()->raw_mesh();
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mesh.require_shared_vertices();
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// To keep track of the number of iterations
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unsigned status = 0;
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// The maximum number of iterations
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auto max_tries = unsigned(accuracy * MAX_TRIES);
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// call status callback with zero, because we are at the start
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statuscb(status);
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auto statusfn = [&statuscb, &status, &max_tries] {
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// report status
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statuscb(unsigned(++status * 100.0/max_tries) );
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};
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auto stopcond = [&statuscb] {
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return ! statuscb(-1);
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};
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// Different search methods have to be used depending on the model elevation
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if (is_on_floor(po)) {
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std::vector<XYRotation> inputs = get_chull_rotations(mesh, max_tries);
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max_tries = inputs.size();
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// If the model can be placed on the bed directly, we only need to
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// check the 3D convex hull face rotations.
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auto objfn = [&mesh, &statusfn](const XYRotation &rot) {
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statusfn();
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Transform3f tr = to_transform3f(rot);
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return get_supportedness_onfloor_score(mesh, tr);
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};
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rot = find_min_score<2>(objfn, inputs.begin(), inputs.end(), stopcond);
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} else {
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// Preparing the optimizer.
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size_t gridsize = std::sqrt(max_tries); // 2D grid has gridsize^2 calls
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opt::Optimizer<opt::AlgBruteForce> solver(opt::StopCriteria{}
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.max_iterations(max_tries)
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.stop_condition(stopcond),
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gridsize);
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// We are searching rotations around only two axes x, y. Thus the
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// problem becomes a 2 dimensional optimization task.
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// We can specify the bounds for a dimension in the following way:
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auto bounds = opt::bounds({ {-PI, PI}, {-PI, PI} });
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auto result = solver.to_min().optimize(
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[&mesh, &statusfn] (const XYRotation &rot)
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{
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statusfn();
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return get_supportedness_score(mesh, to_transform3f(rot));
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}, opt::initvals({0., 0.}), bounds);
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// Save the result
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rot = result.optimum;
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}
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return {rot[0], rot[1]};
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}
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@ -37,7 +37,11 @@ Vec2d find_best_misalignment_rotation(
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RotOptimizeStatusCB statuscb = [] (int) { return true; }
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);
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Vec2d find_least_supports_rotation(
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const SLAPrintObject& modelobj,
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float accuracy = 1.0f,
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RotOptimizeStatusCB statuscb = [] (int) { return true; }
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);
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} // namespace sla
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} // namespace Slic3r
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@ -21,7 +21,7 @@ class RotoptimizeJob : public PlaterJob
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static inline const FindMethod Methods[] = {
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{ L("Best misalignment"), sla::find_best_misalignment_rotation },
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{ L("Least supports"), sla::find_best_misalignment_rotation }
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{ L("Least supports"), sla::find_least_supports_rotation }
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};
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size_t m_method_id = 0;
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@ -1,6 +1,7 @@
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#include <unordered_set>
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#include <unordered_map>
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#include <random>
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#include <numeric>
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#include <cstdint>
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#include "sla_test_utils.hpp"
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