#ifndef MODELARRANGE_HPP #define MODELARRANGE_HPP #include "Model.hpp" #include "SVG.hpp" #include #include #include #include namespace Slic3r { namespace arr { using namespace libnest2d; std::string toString(const Model& model, bool holes = true) { std::stringstream ss; ss << "{\n"; for(auto objptr : model.objects) { if(!objptr) continue; auto rmesh = objptr->raw_mesh(); for(auto objinst : objptr->instances) { if(!objinst) continue; Slic3r::TriangleMesh tmpmesh = rmesh; tmpmesh.scale(objinst->scaling_factor); objinst->transform_mesh(&tmpmesh); ExPolygons expolys = tmpmesh.horizontal_projection(); for(auto& expoly_complex : expolys) { auto tmp = expoly_complex.simplify(1.0/SCALING_FACTOR); if(tmp.empty()) continue; auto expoly = tmp.front(); expoly.contour.make_clockwise(); for(auto& h : expoly.holes) h.make_counter_clockwise(); ss << "\t{\n"; ss << "\t\t{\n"; for(auto v : expoly.contour.points) ss << "\t\t\t{" << v.x << ", " << v.y << "},\n"; { auto v = expoly.contour.points.front(); ss << "\t\t\t{" << v.x << ", " << v.y << "},\n"; } ss << "\t\t},\n"; // Holes: ss << "\t\t{\n"; if(holes) for(auto h : expoly.holes) { ss << "\t\t\t{\n"; for(auto v : h.points) ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\n"; { auto v = h.points.front(); ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\n"; } ss << "\t\t\t},\n"; } ss << "\t\t},\n"; ss << "\t},\n"; } } } ss << "}\n"; return ss.str(); } void toSVG(SVG& svg, const Model& model) { for(auto objptr : model.objects) { if(!objptr) continue; auto rmesh = objptr->raw_mesh(); for(auto objinst : objptr->instances) { if(!objinst) continue; Slic3r::TriangleMesh tmpmesh = rmesh; tmpmesh.scale(objinst->scaling_factor); objinst->transform_mesh(&tmpmesh); ExPolygons expolys = tmpmesh.horizontal_projection(); svg.draw(expolys); } } } namespace bgi = boost::geometry::index; using SpatElement = std::pair; using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >; std::tuple objfunc(const PointImpl& bincenter, double bin_area, ShapeLike::Shapes& pile, // The currently arranged pile double pile_area, const Item &item, double norm, // A norming factor for physical dimensions std::vector& areacache, // pile item areas will be cached // a spatial index to quickly get neighbors of the candidate item SpatIndex& spatindex ) { using pl = PointLike; using sl = ShapeLike; static const double BIG_ITEM_TRESHOLD = 0.04; static const double ROUNDNESS_RATIO = 0.5; static const double DENSITY_RATIO = 1.0 - ROUNDNESS_RATIO; // We will treat big items (compared to the print bed) differently auto isBig = [&areacache, bin_area](double a) { bool t = areacache.empty() ? true : a > 0.5*areacache.front(); return a/bin_area > BIG_ITEM_TRESHOLD || t; }; // If a new bin has been created: if(pile.size() < areacache.size()) { areacache.clear(); spatindex.clear(); } // We must fill the caches: int idx = 0; for(auto& p : pile) { if(idx == areacache.size()) { areacache.emplace_back(sl::area(p)); if(isBig(areacache[idx])) spatindex.insert({sl::boundingBox(p), idx}); } idx++; } // Candidate item bounding box auto ibb = item.boundingBox(); // Calculate the full bounding box of the pile with the candidate item pile.emplace_back(item.transformedShape()); auto fullbb = ShapeLike::boundingBox(pile); pile.pop_back(); // The bounding box of the big items (they will accumulate in the center // of the pile Box bigbb; if(spatindex.empty()) bigbb = fullbb; else { auto boostbb = spatindex.bounds(); boost::geometry::convert(boostbb, bigbb); } // Will hold the resulting score double score = 0; if(isBig(item.area())) { // This branch is for the bigger items.. // Here we will use the closest point of the item bounding box to // the already arranged pile. So not the bb center nor the a choosen // corner but whichever is the closest to the center. This will // prevent some unwanted strange arrangements. auto minc = ibb.minCorner(); // bottom left corner auto maxc = ibb.maxCorner(); // top right corner // top left and bottom right corners auto top_left = PointImpl{getX(minc), getY(maxc)}; auto bottom_right = PointImpl{getX(maxc), getY(minc)}; // Now the distance of the gravity center will be calculated to the // five anchor points and the smallest will be chosen. std::array dists; auto cc = fullbb.center(); // The gravity center dists[0] = pl::distance(minc, cc); dists[1] = pl::distance(maxc, cc); dists[2] = pl::distance(ibb.center(), cc); dists[3] = pl::distance(top_left, cc); dists[4] = pl::distance(bottom_right, cc); // The smalles distance from the arranged pile center: auto dist = *(std::min_element(dists.begin(), dists.end())) / norm; // Density is the pack density: how big is the arranged pile auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm; // Prepare a variable for the alignment score. // This will indicate: how well is the candidate item aligned with // its neighbors. We will check the aligment with all neighbors and // return the score for the best alignment. So it is enough for the // candidate to be aligned with only one item. auto alignment_score = std::numeric_limits::max(); auto& trsh = item.transformedShape(); auto querybb = item.boundingBox(); // Query the spatial index for the neigbours std::vector result; spatindex.query(bgi::intersects(querybb), std::back_inserter(result)); for(auto& e : result) { // now get the score for the best alignment auto idx = e.second; auto& p = pile[idx]; auto parea = areacache[idx]; auto bb = sl::boundingBox(sl::Shapes{p, trsh}); auto bbarea = bb.area(); auto ascore = 1.0 - (item.area() + parea)/bbarea; if(ascore < alignment_score) alignment_score = ascore; } // The final mix of the score is the balance between the distance // from the full pile center, the pack density and the // alignment with the neigbours score = 0.4 * dist + 0.4 * density + 0.2 * alignment_score; } else if( !isBig(item.area()) && spatindex.empty()) { // If there are no big items, only small, we should consider the // density here as well to not get silly results auto bindist = pl::distance(ibb.center(), bincenter) / norm; auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm; score = ROUNDNESS_RATIO * bindist + DENSITY_RATIO * density; } else { // Here there are the small items that should be placed around the // already processed bigger items. // No need to play around with the anchor points, the center will be // just fine for small items score = pl::distance(ibb.center(), bigbb.center()) / norm; } return std::make_tuple(score, fullbb); } template void fillConfig(PConf& pcfg) { // Align the arranged pile into the center of the bin pcfg.alignment = PConf::Alignment::CENTER; // Start placing the items from the center of the print bed pcfg.starting_point = PConf::Alignment::CENTER; // TODO cannot use rotations until multiple objects of same geometry can // handle different rotations // arranger.useMinimumBoundigBoxRotation(); pcfg.rotations = { 0.0 }; // The accuracy of optimization. // Goes from 0.0 to 1.0 and scales performance as well pcfg.accuracy = 0.6f; } template class AutoArranger {}; template class _ArrBase { protected: using Placer = strategies::_NofitPolyPlacer; using Selector = FirstFitSelection; using Packer = Arranger; using PConfig = typename Packer::PlacementConfig; using Distance = TCoord; using Pile = ShapeLike::Shapes; Packer pck_; PConfig pconf_; // Placement configuration double bin_area_; std::vector areacache_; SpatIndex rtree_; public: _ArrBase(const TBin& bin, Distance dist, std::function progressind): pck_(bin, dist), bin_area_(ShapeLike::area(bin)) { fillConfig(pconf_); pck_.progressIndicator(progressind); } template inline IndexedPackGroup operator()(Args&&...args) { areacache_.clear(); rtree_.clear(); return pck_.arrangeIndexed(std::forward(args)...); } }; template<> class AutoArranger: public _ArrBase { public: AutoArranger(const Box& bin, Distance dist, std::function progressind): _ArrBase(bin, dist, progressind) { pconf_.object_function = [this, bin] ( Pile& pile, const Item &item, double pile_area, double norm, double /*penality*/) { auto result = objfunc(bin.center(), bin_area_, pile, pile_area, item, norm, areacache_, rtree_); double score = std::get<0>(result); auto& fullbb = std::get<1>(result); auto wdiff = fullbb.width() - bin.width(); auto hdiff = fullbb.height() - bin.height(); if(wdiff > 0) score += std::pow(wdiff, 2) / norm; if(hdiff > 0) score += std::pow(hdiff, 2) / norm; return score; }; pck_.configure(pconf_); } }; using lnCircle = libnest2d::_Circle; template<> class AutoArranger: public _ArrBase { public: AutoArranger(const lnCircle& bin, Distance dist, std::function progressind): _ArrBase(bin, dist, progressind) { pconf_.object_function = [this, &bin] ( Pile& pile, const Item &item, double pile_area, double norm, double /*penality*/) { auto result = objfunc(bin.center(), bin_area_, pile, pile_area, item, norm, areacache_, rtree_); double score = std::get<0>(result); auto& fullbb = std::get<1>(result); auto d = PointLike::distance(fullbb.minCorner(), fullbb.maxCorner()); auto diff = d - 2*bin.radius(); if(diff > 0) { if( item.area() > 0.01*bin_area_ && item.vertexCount() < 20) { pile.emplace_back(item.transformedShape()); auto chull = ShapeLike::convexHull(pile); pile.pop_back(); auto C = strategies::boundingCircle(chull); auto rdiff = C.radius() - bin.radius(); if(rdiff > 0) { score += std::pow(rdiff, 3) / norm; } } } return score; }; pck_.configure(pconf_); } }; template<> class AutoArranger: public _ArrBase { public: AutoArranger(const PolygonImpl& bin, Distance dist, std::function progressind): _ArrBase(bin, dist, progressind) { pconf_.object_function = [this, &bin] ( Pile& pile, const Item &item, double pile_area, double norm, double /*penality*/) { auto binbb = ShapeLike::boundingBox(bin); auto result = objfunc(binbb.center(), bin_area_, pile, pile_area, item, norm, areacache_, rtree_); double score = std::get<0>(result); return score; }; pck_.configure(pconf_); } }; template<> // Specialization with no bin class AutoArranger: public _ArrBase { public: AutoArranger(Distance dist, std::function progressind): _ArrBase(Box(0, 0), dist, progressind) { this->pconf_.object_function = [this] ( Pile& pile, const Item &item, double pile_area, double norm, double /*penality*/) { auto result = objfunc({0, 0}, 0, pile, pile_area, item, norm, areacache_, rtree_); return std::get<0>(result); }; this->pck_.configure(pconf_); } }; // A container which stores a pointer to the 3D object and its projected // 2D shape from top view. using ShapeData2D = std::vector>; ShapeData2D projectModelFromTop(const Slic3r::Model &model) { ShapeData2D ret; auto s = std::accumulate(model.objects.begin(), model.objects.end(), 0, [](size_t s, ModelObject* o){ return s + o->instances.size(); }); ret.reserve(s); for(auto objptr : model.objects) { if(objptr) { auto rmesh = objptr->raw_mesh(); for(auto objinst : objptr->instances) { if(objinst) { Slic3r::TriangleMesh tmpmesh = rmesh; ClipperLib::PolygonImpl pn; tmpmesh.scale(objinst->scaling_factor); // TODO export the exact 2D projection auto p = tmpmesh.convex_hull(); p.make_clockwise(); p.append(p.first_point()); pn.Contour = Slic3rMultiPoint_to_ClipperPath( p ); // Efficient conversion to item. Item item(std::move(pn)); // Invalid geometries would throw exceptions when arranging if(item.vertexCount() > 3) { item.rotation(objinst->rotation); item.translation( { ClipperLib::cInt(objinst->offset.x/SCALING_FACTOR), ClipperLib::cInt(objinst->offset.y/SCALING_FACTOR) }); ret.emplace_back(objinst, item); } } } } } return ret; } class Circle { Point center_; double radius_; public: inline Circle(): center_(0, 0), radius_(std::nan("")) {} inline Circle(const Point& c, double r): center_(c), radius_(r) {} inline double radius() const { return radius_; } inline const Point& center() const { return center_; } inline operator bool() { return !std::isnan(radius_); } }; enum class BedShapeType { BOX, CIRCLE, IRREGULAR, WHO_KNOWS }; struct BedShapeHint { BedShapeType type; /*union*/ struct { // I know but who cares... Circle circ; BoundingBox box; Polyline polygon; } shape; }; BedShapeHint bedShape(const Polyline& bed) { static const double E = 10/SCALING_FACTOR; BedShapeHint ret; auto width = [](const BoundingBox& box) { return box.max.x - box.min.x; }; auto height = [](const BoundingBox& box) { return box.max.y - box.min.y; }; auto area = [&width, &height](const BoundingBox& box) { double w = width(box); double h = height(box); return w*h; }; auto poly_area = [](Polyline p) { Polygon pp; pp.points.reserve(p.points.size() + 1); pp.points = std::move(p.points); pp.points.emplace_back(pp.points.front()); return std::abs(pp.area()); }; auto bb = bed.bounding_box(); auto isCircle = [bb](const Polyline& polygon) { auto center = bb.center(); std::vector vertex_distances; double avg_dist = 0; for (auto pt: polygon.points) { double distance = center.distance_to(pt); vertex_distances.push_back(distance); avg_dist += distance; } avg_dist /= vertex_distances.size(); Circle ret(center, avg_dist); for (auto el: vertex_distances) { if (abs(el - avg_dist) > 10 * SCALED_EPSILON) ret = Circle(); break; } return ret; }; auto parea = poly_area(bed); if( (1.0 - parea/area(bb)) < 1e-3 ) { ret.type = BedShapeType::BOX; ret.shape.box = bb; } else if(auto c = isCircle(bed)) { ret.type = BedShapeType::CIRCLE; ret.shape.circ = c; } else { ret.type = BedShapeType::IRREGULAR; ret.shape.polygon = bed; } // Determine the bed shape by hand return ret; } void applyResult( IndexedPackGroup::value_type& group, Coord batch_offset, ShapeData2D& shapemap) { for(auto& r : group) { auto idx = r.first; // get the original item index Item& item = r.second; // get the item itself // Get the model instance from the shapemap using the index ModelInstance *inst_ptr = shapemap[idx].first; // Get the tranformation data from the item object and scale it // appropriately auto off = item.translation(); Radians rot = item.rotation(); Pointf foff(off.X*SCALING_FACTOR + batch_offset, off.Y*SCALING_FACTOR); // write the tranformation data into the model instance inst_ptr->rotation = rot; inst_ptr->offset = foff; } } /** * \brief Arranges the model objects on the screen. * * The arrangement considers multiple bins (aka. print beds) for placing all * the items provided in the model argument. If the items don't fit on one * print bed, the remaining will be placed onto newly created print beds. * The first_bin_only parameter, if set to true, disables this behaviour and * makes sure that only one print bed is filled and the remaining items will be * untouched. When set to false, the items which could not fit onto the * print bed will be placed next to the print bed so the user should see a * pile of items on the print bed and some other piles outside the print * area that can be dragged later onto the print bed as a group. * * \param model The model object with the 3D content. * \param dist The minimum distance which is allowed for any pair of items * on the print bed in any direction. * \param bb The bounding box of the print bed. It corresponds to the 'bin' * for bin packing. * \param first_bin_only This parameter controls whether to place the * remaining items which do not fit onto the print area next to the print * bed or leave them untouched (let the user arrange them by hand or remove * them). */ bool arrange(Model &model, coordf_t min_obj_distance, const Slic3r::Polyline& bed, BedShapeHint bedhint, bool first_bin_only, std::function progressind) { using ArrangeResult = _IndexedPackGroup; bool ret = true; // Get the 2D projected shapes with their 3D model instance pointers auto shapemap = arr::projectModelFromTop(model); // Copy the references for the shapes only as the arranger expects a // sequence of objects convertible to Item or ClipperPolygon std::vector> shapes; shapes.reserve(shapemap.size()); std::for_each(shapemap.begin(), shapemap.end(), [&shapes] (ShapeData2D::value_type& it) { shapes.push_back(std::ref(it.second)); }); IndexedPackGroup result; if(bedhint.type == BedShapeType::WHO_KNOWS) bedhint = bedShape(bed); BoundingBox bbb(bed); auto binbb = Box({ static_cast(bbb.min.x), static_cast(bbb.min.y) }, { static_cast(bbb.max.x), static_cast(bbb.max.y) }); switch(bedhint.type) { case BedShapeType::BOX: { // Create the arranger for the box shaped bed AutoArranger arrange(binbb, min_obj_distance, progressind); // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } case BedShapeType::CIRCLE: { auto c = bedhint.shape.circ; auto cc = lnCircle({c.center().x, c.center().y} , c.radius()); AutoArranger arrange(cc, min_obj_distance, progressind); result = arrange(shapes.begin(), shapes.end()); break; } case BedShapeType::IRREGULAR: case BedShapeType::WHO_KNOWS: { using P = libnest2d::PolygonImpl; auto ctour = Slic3rMultiPoint_to_ClipperPath(bed); P irrbed = ShapeLike::create(std::move(ctour)); AutoArranger

arrange(irrbed, min_obj_distance, progressind); // Arrange and return the items with their respective indices within the // input sequence. result = arrange(shapes.begin(), shapes.end()); break; } }; if(result.empty()) return false; if(first_bin_only) { applyResult(result.front(), 0, shapemap); } else { const auto STRIDE_PADDING = 1.2; Coord stride = static_cast(STRIDE_PADDING* binbb.width()*SCALING_FACTOR); Coord batch_offset = 0; for(auto& group : result) { applyResult(group, batch_offset, shapemap); // Only the first pack group can be placed onto the print bed. The // other objects which could not fit will be placed next to the // print bed batch_offset += stride; } } for(auto objptr : model.objects) objptr->invalidate_bounding_box(); return ret && result.size() == 1; } } } #endif // MODELARRANGE_HPP