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https://git.mirrors.martin98.com/https://github.com/prusa3d/PrusaSlicer.git
synced 2025-05-20 01:28:07 +08:00
406 lines
15 KiB
C++
406 lines
15 KiB
C++
#ifndef MODELARRANGE_HPP
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#define MODELARRANGE_HPP
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#include "Model.hpp"
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#include "SVG.hpp"
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#include <libnest2d.h>
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#include <numeric>
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#include <ClipperUtils.hpp>
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namespace Slic3r {
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namespace arr {
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using namespace libnest2d;
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std::string toString(const Model& model, bool holes = true) {
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std::stringstream ss;
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ss << "{\n";
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for(auto objptr : model.objects) {
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if(!objptr) continue;
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auto rmesh = objptr->raw_mesh();
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for(auto objinst : objptr->instances) {
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if(!objinst) continue;
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Slic3r::TriangleMesh tmpmesh = rmesh;
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tmpmesh.scale(objinst->scaling_factor);
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objinst->transform_mesh(&tmpmesh);
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ExPolygons expolys = tmpmesh.horizontal_projection();
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for(auto& expoly_complex : expolys) {
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auto tmp = expoly_complex.simplify(1.0/SCALING_FACTOR);
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if(tmp.empty()) continue;
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auto expoly = tmp.front();
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expoly.contour.make_clockwise();
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for(auto& h : expoly.holes) h.make_counter_clockwise();
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ss << "\t{\n";
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ss << "\t\t{\n";
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for(auto v : expoly.contour.points) ss << "\t\t\t{"
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<< v.x << ", "
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<< v.y << "},\n";
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{
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auto v = expoly.contour.points.front();
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ss << "\t\t\t{" << v.x << ", " << v.y << "},\n";
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}
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ss << "\t\t},\n";
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// Holes:
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ss << "\t\t{\n";
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if(holes) for(auto h : expoly.holes) {
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ss << "\t\t\t{\n";
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for(auto v : h.points) ss << "\t\t\t\t{"
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<< v.x << ", "
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<< v.y << "},\n";
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{
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auto v = h.points.front();
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ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\n";
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}
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ss << "\t\t\t},\n";
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}
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ss << "\t\t},\n";
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ss << "\t},\n";
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}
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}
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}
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ss << "}\n";
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return ss.str();
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}
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void toSVG(SVG& svg, const Model& model) {
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for(auto objptr : model.objects) {
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if(!objptr) continue;
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auto rmesh = objptr->raw_mesh();
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for(auto objinst : objptr->instances) {
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if(!objinst) continue;
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Slic3r::TriangleMesh tmpmesh = rmesh;
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tmpmesh.scale(objinst->scaling_factor);
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objinst->transform_mesh(&tmpmesh);
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ExPolygons expolys = tmpmesh.horizontal_projection();
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svg.draw(expolys);
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}
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}
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}
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// A container which stores a pointer to the 3D object and its projected
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// 2D shape from top view.
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using ShapeData2D =
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std::vector<std::pair<Slic3r::ModelInstance*, Item>>;
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ShapeData2D projectModelFromTop(const Slic3r::Model &model) {
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ShapeData2D ret;
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auto s = std::accumulate(model.objects.begin(), model.objects.end(), 0,
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[](size_t s, ModelObject* o){
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return s + o->instances.size();
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});
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ret.reserve(s);
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for(auto objptr : model.objects) {
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if(objptr) {
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auto rmesh = objptr->raw_mesh();
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for(auto objinst : objptr->instances) {
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if(objinst) {
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Slic3r::TriangleMesh tmpmesh = rmesh;
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ClipperLib::PolygonImpl pn;
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tmpmesh.scale(objinst->scaling_factor);
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// TODO export the exact 2D projection
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auto p = tmpmesh.convex_hull();
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p.make_clockwise();
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p.append(p.first_point());
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pn.Contour = Slic3rMultiPoint_to_ClipperPath( p );
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// Efficient conversion to item.
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Item item(std::move(pn));
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// Invalid geometries would throw exceptions when arranging
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if(item.vertexCount() > 3) {
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item.rotation(objinst->rotation);
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item.translation( {
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ClipperLib::cInt(objinst->offset.x/SCALING_FACTOR),
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ClipperLib::cInt(objinst->offset.y/SCALING_FACTOR)
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});
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ret.emplace_back(objinst, item);
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}
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}
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}
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}
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}
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return ret;
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}
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/**
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* \brief Arranges the model objects on the screen.
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*
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* The arrangement considers multiple bins (aka. print beds) for placing all
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* the items provided in the model argument. If the items don't fit on one
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* print bed, the remaining will be placed onto newly created print beds.
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* The first_bin_only parameter, if set to true, disables this behaviour and
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* makes sure that only one print bed is filled and the remaining items will be
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* untouched. When set to false, the items which could not fit onto the
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* print bed will be placed next to the print bed so the user should see a
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* pile of items on the print bed and some other piles outside the print
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* area that can be dragged later onto the print bed as a group.
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*
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* \param model The model object with the 3D content.
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* \param dist The minimum distance which is allowed for any pair of items
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* on the print bed in any direction.
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* \param bb The bounding box of the print bed. It corresponds to the 'bin'
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* for bin packing.
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* \param first_bin_only This parameter controls whether to place the
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* remaining items which do not fit onto the print area next to the print
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* bed or leave them untouched (let the user arrange them by hand or remove
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* them).
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*/
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bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
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bool first_bin_only,
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std::function<void(unsigned)> progressind)
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{
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using ArrangeResult = _IndexedPackGroup<PolygonImpl>;
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bool ret = true;
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// Create the arranger config
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auto min_obj_distance = static_cast<Coord>(dist/SCALING_FACTOR);
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// Get the 2D projected shapes with their 3D model instance pointers
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auto shapemap = arr::projectModelFromTop(model);
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bool hasbin = bb != nullptr && bb->defined;
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double area_max = 0;
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// Copy the references for the shapes only as the arranger expects a
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// sequence of objects convertible to Item or ClipperPolygon
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std::vector<std::reference_wrapper<Item>> shapes;
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shapes.reserve(shapemap.size());
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std::for_each(shapemap.begin(), shapemap.end(),
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[&shapes, min_obj_distance, &area_max, hasbin]
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(ShapeData2D::value_type& it)
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{
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shapes.push_back(std::ref(it.second));
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});
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Box bin;
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if(hasbin) {
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// Scale up the bounding box to clipper scale.
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BoundingBoxf bbb = *bb;
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bbb.scale(1.0/SCALING_FACTOR);
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bin = Box({
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static_cast<libnest2d::Coord>(bbb.min.x),
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static_cast<libnest2d::Coord>(bbb.min.y)
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},
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{
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static_cast<libnest2d::Coord>(bbb.max.x),
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static_cast<libnest2d::Coord>(bbb.max.y)
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});
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}
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// Will use the DJD selection heuristic with the BottomLeft placement
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// strategy
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using Arranger = Arranger<NfpPlacer, FirstFitSelection>;
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using PConf = Arranger::PlacementConfig;
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using SConf = Arranger::SelectionConfig;
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PConf pcfg; // Placement configuration
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SConf scfg; // Selection configuration
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// Align the arranged pile into the center of the bin
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pcfg.alignment = PConf::Alignment::CENTER;
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// Start placing the items from the center of the print bed
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pcfg.starting_point = PConf::Alignment::CENTER;
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// TODO cannot use rotations until multiple objects of same geometry can
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// handle different rotations
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// arranger.useMinimumBoundigBoxRotation();
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pcfg.rotations = { 0.0 };
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// The accuracy of optimization. Goes from 0.0 to 1.0 and scales performance
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pcfg.accuracy = 0.4f;
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// Magic: we will specify what is the goal of arrangement... In this case
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// we override the default object function to make the larger items go into
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// the center of the pile and smaller items orbit it so the resulting pile
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// has a circle-like shape. This is good for the print bed's heat profile.
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// We alse sacrafice a bit of pack efficiency for this to work. As a side
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// effect, the arrange procedure is a lot faster (we do not need to
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// calculate the convex hulls)
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pcfg.object_function = [bin, hasbin](
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NfpPlacer::Pile& pile, // The currently arranged pile
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const Item &item,
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double /*area*/, // Sum area of items (not needed)
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double norm, // A norming factor for physical dimensions
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double penality) // Min penality in case of bad arrangement
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{
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using pl = PointLike;
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static const double BIG_ITEM_TRESHOLD = 0.2;
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static const double GRAVITY_RATIO = 0.5;
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static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
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// We will treat big items (compared to the print bed) differently
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NfpPlacer::Pile bigs;
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bigs.reserve(pile.size());
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for(auto& p : pile) {
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auto pbb = ShapeLike::boundingBox(p);
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auto na = std::sqrt(pbb.width()*pbb.height())/norm;
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if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
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}
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// Candidate item bounding box
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auto ibb = item.boundingBox();
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// Calculate the full bounding box of the pile with the candidate item
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pile.emplace_back(item.transformedShape());
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auto fullbb = ShapeLike::boundingBox(pile);
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pile.pop_back();
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// The bounding box of the big items (they will accumulate in the center
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// of the pile
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auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
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// The size indicator of the candidate item. This is not the area,
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// but almost...
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auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
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// Will hold the resulting score
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double score = 0;
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if(itemnormarea > BIG_ITEM_TRESHOLD) {
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// This branch is for the bigger items..
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// Here we will use the closest point of the item bounding box to
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// the already arranged pile. So not the bb center nor the a choosen
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// corner but whichever is the closest to the center. This will
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// prevent unwanted strange arrangements.
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auto minc = ibb.minCorner(); // bottom left corner
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auto maxc = ibb.maxCorner(); // top right corner
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// top left and bottom right corners
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auto top_left = PointImpl{getX(minc), getY(maxc)};
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auto bottom_right = PointImpl{getX(maxc), getY(minc)};
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auto cc = fullbb.center(); // The gravity center
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// Now the distnce of the gravity center will be calculated to the
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// five anchor points and the smallest will be chosen.
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std::array<double, 5> dists;
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dists[0] = pl::distance(minc, cc);
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dists[1] = pl::distance(maxc, cc);
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dists[2] = pl::distance(ibb.center(), cc);
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dists[3] = pl::distance(top_left, cc);
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dists[4] = pl::distance(bottom_right, cc);
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auto dist = *(std::min_element(dists.begin(), dists.end())) / norm;
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// Density is the pack density: how big is the arranged pile
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auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
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// The score is a weighted sum of the distance from pile center
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// and the pile size
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score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
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} else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
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// If there are no big items, only small, we should consider the
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// density here as well to not get silly results
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auto bindist = pl::distance(ibb.center(), bin.center()) / norm;
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auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
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score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
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} else {
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// Here there are the small items that should be placed around the
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// already processed bigger items.
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// No need to play around with the anchor points, the center will be
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// just fine for small items
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score = pl::distance(ibb.center(), bigbb.center()) / norm;
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}
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// If it does not fit into the print bed we will beat it
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// with a large penality. If we would not do this, there would be only
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// one big pile that doesn't care whether it fits onto the print bed.
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if(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
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return score;
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};
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// Create the arranger object
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Arranger arranger(bin, min_obj_distance, pcfg, scfg);
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// Set the progress indicator for the arranger.
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arranger.progressIndicator(progressind);
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// Arrange and return the items with their respective indices within the
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// input sequence.
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auto result = arranger.arrangeIndexed(shapes.begin(), shapes.end());
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auto applyResult = [&shapemap](ArrangeResult::value_type& group,
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Coord batch_offset)
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{
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for(auto& r : group) {
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auto idx = r.first; // get the original item index
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Item& item = r.second; // get the item itself
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// Get the model instance from the shapemap using the index
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ModelInstance *inst_ptr = shapemap[idx].first;
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// Get the tranformation data from the item object and scale it
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// appropriately
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auto off = item.translation();
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Radians rot = item.rotation();
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Pointf foff(off.X*SCALING_FACTOR + batch_offset,
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off.Y*SCALING_FACTOR);
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// write the tranformation data into the model instance
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inst_ptr->rotation = rot;
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inst_ptr->offset = foff;
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}
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};
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if(first_bin_only) {
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applyResult(result.front(), 0);
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} else {
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const auto STRIDE_PADDING = 1.2;
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Coord stride = static_cast<Coord>(STRIDE_PADDING*
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bin.width()*SCALING_FACTOR);
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Coord batch_offset = 0;
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for(auto& group : result) {
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applyResult(group, batch_offset);
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// Only the first pack group can be placed onto the print bed. The
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// other objects which could not fit will be placed next to the
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// print bed
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batch_offset += stride;
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}
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}
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for(auto objptr : model.objects) objptr->invalidate_bounding_box();
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return ret && result.size() == 1;
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}
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}
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}
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#endif // MODELARRANGE_HPP
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