New object function considering item size categories (big and small)
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2 changed files with 91 additions and 34 deletions
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@ -78,7 +78,7 @@ struct NfpPConfig {
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* into the bin.
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*
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*/
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std::function<double(const Nfp::Shapes<RawShape>&, const _Item<RawShape>&,
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std::function<double(Nfp::Shapes<RawShape>&, const _Item<RawShape>&,
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double, double, double)>
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object_function;
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@ -163,18 +163,22 @@ template<class RawShape> class EdgeCache {
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void fetchCorners() const {
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if(!contour_.corners.empty()) return;
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// TODO Accuracy
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contour_.corners = contour_.distances;
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for(auto& d : contour_.corners) d /= contour_.full_distance;
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contour_.corners.reserve(contour_.distances.size() / 3 + 1);
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for(size_t i = 0; i < contour_.distances.size() - 1; i += 3) {
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contour_.corners.emplace_back(
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contour_.distances.at(i) / contour_.full_distance);
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}
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}
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void fetchHoleCorners(unsigned hidx) const {
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auto& hc = holes_[hidx];
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if(!hc.corners.empty()) return;
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// TODO Accuracy
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hc.corners = hc.distances;
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for(auto& d : hc.corners) d /= hc.full_distance;
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hc.corners.reserve(hc.distances.size() / 3 + 1);
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for(size_t i = 0; i < hc.distances.size() - 1; i += 3) {
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hc.corners.emplace_back(
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hc.distances.at(i) / hc.full_distance);
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}
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}
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inline Vertex coords(const ContourCache& cache, double distance) const {
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@ -433,7 +437,7 @@ class _NofitPolyPlacer: public PlacerBoilerplate<_NofitPolyPlacer<RawShape>,
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public:
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using Pile = const Nfp::Shapes<RawShape>&;
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using Pile = Nfp::Shapes<RawShape>;
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inline explicit _NofitPolyPlacer(const BinType& bin):
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Base(bin),
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@ -536,7 +540,7 @@ public:
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// customizable by the library client
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auto _objfunc = config_.object_function?
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config_.object_function :
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[this](const Nfp::Shapes<RawShape>& pile, Item,
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[this](Nfp::Shapes<RawShape>& pile, Item,
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double occupied_area, double /*norm*/,
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double penality)
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{
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@ -565,14 +569,14 @@ public:
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d += startpos;
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item.translation(d);
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pile.emplace_back(item.transformedShape());
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// pile.emplace_back(item.transformedShape());
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double occupied_area = pile_area + item.area();
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double score = _objfunc(pile, item, occupied_area,
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norm_, penality_);
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pile.pop_back();
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// pile.pop_back();
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return score;
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};
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@ -529,7 +529,6 @@ bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
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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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double norm_2 = std::nan("");
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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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@ -538,8 +537,8 @@ bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
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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, &norm_2](
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NfpPlacer::Pile pile, // The currently arranged pile
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pcfg.object_function = [bin, hasbin](
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NfpPlacer::Pile& pile, // The currently arranged pile
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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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@ -547,37 +546,91 @@ bool arrange(Model &model, coordf_t dist, const Slic3r::BoundingBoxf* bb,
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{
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using pl = PointLike;
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auto bb = ShapeLike::boundingBox(pile);
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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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auto minc = ibb.minCorner();
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auto maxc = ibb.maxCorner();
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if(std::isnan(norm_2)) norm_2 = pow(norm, 2);
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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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// We get the distance of the reference point from the center of the
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// heat bed
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auto cc = bb.center();
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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 a = pl::distance(ibb.maxCorner(), cc);
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auto b = pl::distance(ibb.minCorner(), cc);
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auto c = pl::distance(ibb.center(), cc);
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auto d = pl::distance(top_left, cc);
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auto e = pl::distance(bottom_right, cc);
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auto cc = fullbb.center(); // The gravity center
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auto area = bb.width() * bb.height() / norm_2;
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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 min_dist = std::min({a, b, c, d, e}) / norm;
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auto dist = *(std::min_element(dists.begin(), dists.end())) / norm;
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// The score will be the normalized distance which will be minimized,
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// effectively creating a circle shaped pile of items
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double score = 0.8*min_dist + 0.2*area;
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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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std::cout << "big " << std::endl;
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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(bb, bin)) score = 2*penality - score;
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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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