Significant performance improvements for elevated and non-elevated case
Apply bruteforce for elevated models
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d527122046
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@ -4,6 +4,7 @@
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#include "../AABBTreeIndirect.hpp"
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#include "FillBase.hpp"
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#include "TriangleMesh.hpp"
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namespace Slic3r {
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@ -1,11 +1,10 @@
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#include <limits>
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#include <exception>
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//#include <libnest2d/optimizers/nlopt/genetic.hpp>
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#include <libslic3r/Optimize/BruteforceOptimizer.hpp>
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#include <libslic3r/SLA/Rotfinder.hpp>
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#include <libslic3r/SLA/Concurrency.hpp>
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#include <libslic3r/Optimize/BruteforceOptimizer.hpp>
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#include "libslic3r/SLAPrint.hpp"
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#include "libslic3r/PrintConfig.hpp"
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@ -61,23 +60,25 @@ std::array<Vec3d, 3> get_transformed_triangle(const TriangleMesh &mesh,
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}
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// Get area and normal of a triangle
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struct Face { Vec3d normal; double area; };
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inline Face facestats(const std::array<Vec3d, 3> &triangle)
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{
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Vec3d U = triangle[1] - triangle[0];
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Vec3d V = triangle[2] - triangle[0];
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Vec3d C = U.cross(V);
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Vec3d N = C.normalized();
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double area = 0.5 * C.norm();
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struct Facestats {
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Vec3d normal;
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double area;
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return {N, area};
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}
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explicit Facestats(const std::array<Vec3d, 3> &triangle)
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{
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Vec3d U = triangle[1] - triangle[0];
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Vec3d V = triangle[2] - triangle[0];
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Vec3d 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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inline const Vec3d DOWN = {0., 0., -1.};
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constexpr double POINTS_PER_UNIT_AREA = 1.;
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// The score function for a particular face
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inline double get_score(const Face &fc)
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inline double get_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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@ -110,7 +111,7 @@ double get_model_supportedness(const TriangleMesh &mesh, const Transform3d &tr)
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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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Face fc = facestats(get_transformed_triangle(mesh, tr, fi));
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Facestats fc{get_transformed_triangle(mesh, tr, fi)};
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return get_score(fc);
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};
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@ -131,7 +132,7 @@ double get_model_supportedness_onfloor(const TriangleMesh &mesh,
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auto accessfn = [&mesh, &tr, zlvl](size_t fi) {
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std::array<Vec3d, 3> tri = get_transformed_triangle(mesh, tr, fi);
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Face fc = facestats(tri);
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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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@ -161,56 +162,91 @@ XYRotation from_transform3d(const Transform3d &tr)
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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 Cmp, class It>
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std::array<double, N> find_min_score(Fn &&fn, Cmp &&cmp, It from, It to)
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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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for (auto it = from; it != to; ++it) {
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double sc = fn(*it);
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if (cmp(sc, score)) {
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score = sc;
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ret = *it;
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}
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}
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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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ccr_par::for_each(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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}, dist / Nthreads);
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auto it = std::min_element(scores.begin(), scores.end());
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if (it != scores.end()) ret = *(from + std::distance(scores.begin(), it));
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return ret;
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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)
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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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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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auto inputs = reserve_vector<XYRotation>(facecount);
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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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Face fc = facestats(get_triangle_vertices(chull, 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::Quaterniond{}.FromTwoVectors(fc.normal, DOWN);
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inputs.emplace_back(from_transform3d(Transform3d::Identity() * q));
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XYRotation rot = from_transform3d(Transform3d::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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return inputs;
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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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XYRotation find_best_rotation(const SLAPrintObject & po,
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float accuracy,
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std::function<void(unsigned)> statuscb,
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std::function<bool()> stopcond)
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Vec2d find_best_rotation(const SLAPrintObject & po,
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float accuracy,
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std::function<void(unsigned)> statuscb,
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std::function<bool()> stopcond)
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{
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static const unsigned MAX_TRIES = 10000;
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static const unsigned MAX_TRIES = 1000;
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// return value
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std::array<double, 2> rot;
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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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@ -226,7 +262,7 @@ XYRotation find_best_rotation(const SLAPrintObject & po,
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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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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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@ -234,29 +270,26 @@ XYRotation find_best_rotation(const SLAPrintObject & po,
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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 inputs = get_chull_rotations(mesh);
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auto cmpfn = [](double a, double b) { return a < b; };
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auto objfn = [&mesh, &statusfn](const XYRotation &rot) {
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statusfn();
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// We actually need the reverserotation to make the object lie on
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// this face
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Transform3d tr = to_transform3d(rot);
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return get_model_supportedness_onfloor(mesh, tr);
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};
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rot = find_min_score<2>(objfn, cmpfn, inputs.begin(), inputs.end());
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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 grid_size = std::sqrt(max_tries);
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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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grid_size);
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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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@ -272,11 +305,9 @@ XYRotation find_best_rotation(const SLAPrintObject & po,
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// Save the result and fck off
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rot = result.optimum;
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std::cout << "best score: " << result.score << std::endl;
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}
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return rot;
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return {rot[0], rot[1]};
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}
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double get_model_supportedness(const SLAPrintObject &po, const Transform3d &tr)
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*
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* @return Returns the rotations around each axis (x, y, z)
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*/
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std::array<double, 2> find_best_rotation(
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Vec2d find_best_rotation(
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const SLAPrintObject& modelobj,
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float accuracy = 1.0f,
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std::function<void(unsigned)> statuscb = [] (unsigned) {},
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void RotoptimizeJob::process()
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{
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int obj_idx = m_plater->get_selected_object_idx();
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if (obj_idx < 0 || m_plater->sla_print().objects().size() <= obj_idx)
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if (obj_idx < 0 || int(m_plater->sla_print().objects().size()) <= obj_idx)
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return;
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ModelObject *o = m_plater->model().objects[size_t(obj_idx)];
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@ -35,15 +35,12 @@ void RotoptimizeJob::process()
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// std::cout << "Model supportedness before: " << score << std::endl;
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// }
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auto r = sla::find_best_rotation(
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*po,
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1.f,
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Vec2d r = sla::find_best_rotation(*po, 0.75f,
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[this](unsigned s) {
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if (s < 100)
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update_status(int(s),
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_(L("Searching for optimal orientation")));
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update_status(int(s), _(L("Searching for optimal orientation")));
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},
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[this]() { return was_canceled(); });
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[this] () { return was_canceled(); });
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double mindist = 6.0; // FIXME
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