739 lines
23 KiB
C++
739 lines
23 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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#include <boost/geometry/index/rtree.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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namespace bgi = boost::geometry::index;
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using SpatElement = std::pair<Box, unsigned>;
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using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >;
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std::tuple<double /*score*/, Box /*farthest point from bin center*/>
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objfunc(const PointImpl& bincenter,
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double bin_area,
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ShapeLike::Shapes<PolygonImpl>& pile, // The currently arranged pile
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double pile_area,
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const Item &item,
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double norm, // A norming factor for physical dimensions
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std::vector<double>& areacache, // pile item areas will be cached
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// a spatial index to quickly get neighbors of the candidate item
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SpatIndex& spatindex
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)
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{
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using pl = PointLike;
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using sl = ShapeLike;
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static const double BIG_ITEM_TRESHOLD = 0.02;
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static const double ROUNDNESS_RATIO = 0.5;
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static const double DENSITY_RATIO = 1.0 - ROUNDNESS_RATIO;
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// We will treat big items (compared to the print bed) differently
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auto isBig = [&areacache, bin_area](double a) {
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double farea = areacache.empty() ? 0 : areacache.front();
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bool fbig = farea / bin_area > BIG_ITEM_TRESHOLD;
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bool abig = a/bin_area > BIG_ITEM_TRESHOLD;
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bool rbig = fbig && a > 0.5*farea;
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return abig || rbig;
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};
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// If a new bin has been created:
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if(pile.size() < areacache.size()) {
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areacache.clear();
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spatindex.clear();
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}
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// We must fill the caches:
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int idx = 0;
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for(auto& p : pile) {
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if(idx == areacache.size()) {
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areacache.emplace_back(sl::area(p));
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if(isBig(areacache[idx]))
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spatindex.insert({sl::boundingBox(p), idx});
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}
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idx++;
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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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Box bigbb;
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if(spatindex.empty()) bigbb = fullbb;
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else {
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auto boostbb = spatindex.bounds();
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boost::geometry::convert(boostbb, bigbb);
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}
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// Will hold the resulting score
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double score = 0;
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if(isBig(item.area())) {
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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 some 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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// Now the distance 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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auto cc = fullbb.center(); // The gravity center
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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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// The smalles distance from the arranged pile center:
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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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// Prepare a variable for the alignment score.
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// This will indicate: how well is the candidate item aligned with
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// its neighbors. We will check the aligment with all neighbors and
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// return the score for the best alignment. So it is enough for the
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// candidate to be aligned with only one item.
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auto alignment_score = std::numeric_limits<double>::max();
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auto& trsh = item.transformedShape();
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auto querybb = item.boundingBox();
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// Query the spatial index for the neigbours
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std::vector<SpatElement> result;
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spatindex.query(bgi::intersects(querybb), std::back_inserter(result));
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for(auto& e : result) { // now get the score for the best alignment
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auto idx = e.second;
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auto& p = pile[idx];
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auto parea = areacache[idx];
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auto bb = sl::boundingBox(sl::Shapes<PolygonImpl>{p, trsh});
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auto bbarea = bb.area();
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auto ascore = 1.0 - (item.area() + parea)/bbarea;
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if(ascore < alignment_score) alignment_score = ascore;
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}
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// The final mix of the score is the balance between the distance
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// from the full pile center, the pack density and the
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// alignment with the neigbours
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score = 0.4 * dist + 0.4 * density + 0.2 * alignment_score;
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} else if( !isBig(item.area()) && spatindex.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(), bincenter) / norm;
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auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
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score = ROUNDNESS_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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return std::make_tuple(score, fullbb);
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}
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template<class PConf>
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void fillConfig(PConf& pcfg) {
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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.
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// Goes from 0.0 to 1.0 and scales performance as well
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pcfg.accuracy = 1.0f;
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}
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template<class TBin>
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class AutoArranger {};
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template<class TBin>
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class _ArrBase {
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protected:
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using Placer = strategies::_NofitPolyPlacer<PolygonImpl, TBin>;
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using Selector = FirstFitSelection;
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using Packer = Arranger<Placer, Selector>;
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using PConfig = typename Packer::PlacementConfig;
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using Distance = TCoord<PointImpl>;
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using Pile = ShapeLike::Shapes<PolygonImpl>;
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Packer pck_;
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PConfig pconf_; // Placement configuration
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double bin_area_;
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std::vector<double> areacache_;
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SpatIndex rtree_;
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public:
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_ArrBase(const TBin& bin, Distance dist,
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std::function<void(unsigned)> progressind):
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pck_(bin, dist), bin_area_(ShapeLike::area<PolygonImpl>(bin))
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{
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fillConfig(pconf_);
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pck_.progressIndicator(progressind);
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}
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template<class...Args> inline IndexedPackGroup operator()(Args&&...args) {
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areacache_.clear();
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rtree_.clear();
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return pck_.arrangeIndexed(std::forward<Args>(args)...);
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}
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};
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template<>
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class AutoArranger<Box>: public _ArrBase<Box> {
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public:
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AutoArranger(const Box& bin, Distance dist,
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std::function<void(unsigned)> progressind):
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_ArrBase<Box>(bin, dist, progressind)
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{
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pconf_.object_function = [this, bin] (
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Pile& pile,
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const Item &item,
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double pile_area,
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double norm,
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double /*penality*/) {
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auto result = objfunc(bin.center(), bin_area_, pile,
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pile_area, item, norm, areacache_, rtree_);
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double score = std::get<0>(result);
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auto& fullbb = std::get<1>(result);
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auto wdiff = fullbb.width() - bin.width();
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auto hdiff = fullbb.height() - bin.height();
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if(wdiff > 0) score += std::pow(wdiff, 2) / norm;
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if(hdiff > 0) score += std::pow(hdiff, 2) / norm;
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return score;
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};
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pck_.configure(pconf_);
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}
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};
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using lnCircle = libnest2d::_Circle<libnest2d::PointImpl>;
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template<>
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class AutoArranger<lnCircle>: public _ArrBase<lnCircle> {
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public:
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AutoArranger(const lnCircle& bin, Distance dist,
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std::function<void(unsigned)> progressind):
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_ArrBase<lnCircle>(bin, dist, progressind) {
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pconf_.object_function = [this, &bin] (
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Pile& pile,
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const Item &item,
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double pile_area,
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double norm,
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double /*penality*/) {
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auto result = objfunc(bin.center(), bin_area_, pile,
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pile_area, item, norm, areacache_, rtree_);
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double score = std::get<0>(result);
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auto& fullbb = std::get<1>(result);
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auto d = PointLike::distance(fullbb.minCorner(),
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fullbb.maxCorner());
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auto diff = d - 2*bin.radius();
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if(diff > 0) {
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if( item.area() > 0.01*bin_area_ && item.vertexCount() < 30) {
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pile.emplace_back(item.transformedShape());
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auto chull = ShapeLike::convexHull(pile);
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pile.pop_back();
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auto C = strategies::boundingCircle(chull);
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auto rdiff = C.radius() - bin.radius();
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if(rdiff > 0) {
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score += std::pow(rdiff, 3) / norm;
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}
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}
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}
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return score;
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};
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pck_.configure(pconf_);
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}
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};
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template<>
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class AutoArranger<PolygonImpl>: public _ArrBase<PolygonImpl> {
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public:
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AutoArranger(const PolygonImpl& bin, Distance dist,
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std::function<void(unsigned)> progressind):
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_ArrBase<PolygonImpl>(bin, dist, progressind)
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{
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pconf_.object_function = [this, &bin] (
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Pile& pile,
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const Item &item,
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double pile_area,
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double norm,
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double /*penality*/) {
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auto binbb = ShapeLike::boundingBox(bin);
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auto result = objfunc(binbb.center(), bin_area_, pile,
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pile_area, item, norm, areacache_, rtree_);
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double score = std::get<0>(result);
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return score;
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};
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pck_.configure(pconf_);
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}
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};
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template<> // Specialization with no bin
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class AutoArranger<bool>: public _ArrBase<Box> {
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public:
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AutoArranger(Distance dist, std::function<void(unsigned)> progressind):
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_ArrBase<Box>(Box(0, 0), dist, progressind)
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{
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this->pconf_.object_function = [this] (
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Pile& pile,
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const Item &item,
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double pile_area,
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double norm,
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double /*penality*/) {
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auto result = objfunc({0, 0}, 0, pile, pile_area,
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item, norm, areacache_, rtree_);
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return std::get<0>(result);
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};
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this->pck_.configure(pconf_);
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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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class Circle {
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Point center_;
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double radius_;
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public:
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inline Circle(): center_(0, 0), radius_(std::nan("")) {}
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inline Circle(const Point& c, double r): center_(c), radius_(r) {}
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inline double radius() const { return radius_; }
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inline const Point& center() const { return center_; }
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inline operator bool() { return !std::isnan(radius_); }
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};
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enum class BedShapeType {
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BOX,
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CIRCLE,
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IRREGULAR,
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WHO_KNOWS
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};
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struct BedShapeHint {
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BedShapeType type;
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/*union*/ struct { // I know but who cares...
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Circle circ;
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BoundingBox box;
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Polyline polygon;
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} shape;
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};
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BedShapeHint bedShape(const Polyline& bed) {
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static const double E = 10/SCALING_FACTOR;
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BedShapeHint ret;
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auto width = [](const BoundingBox& box) {
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return box.max.x - box.min.x;
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};
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auto height = [](const BoundingBox& box) {
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return box.max.y - box.min.y;
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};
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auto area = [&width, &height](const BoundingBox& box) {
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double w = width(box);
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double h = height(box);
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return w*h;
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};
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auto poly_area = [](Polyline p) {
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Polygon pp; pp.points.reserve(p.points.size() + 1);
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pp.points = std::move(p.points);
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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<double> 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<void(unsigned)> progressind)
|
|
{
|
|
using ArrangeResult = _IndexedPackGroup<PolygonImpl>;
|
|
|
|
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<std::reference_wrapper<Item>> 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<libnest2d::Coord>(bbb.min.x),
|
|
static_cast<libnest2d::Coord>(bbb.min.y)
|
|
},
|
|
{
|
|
static_cast<libnest2d::Coord>(bbb.max.x),
|
|
static_cast<libnest2d::Coord>(bbb.max.y)
|
|
});
|
|
|
|
switch(bedhint.type) {
|
|
case BedShapeType::BOX: {
|
|
|
|
// Create the arranger for the box shaped bed
|
|
AutoArranger<Box> 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<lnCircle> 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<PolygonImpl>(std::move(ctour));
|
|
|
|
AutoArranger<P> 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<Coord>(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
|