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Merge remote-tracking branch 'origin/feature_arrange_with_libnest2d' into dev

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# Conflicts:
#	xs/src/slic3r/AppController.cpp
This commit is contained in:
tamasmeszaros 2018-08-31 10:55:55 +02:00
commit 6e2ed48e5a
30 changed files with 3273 additions and 1687 deletions
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455
xs/src/libslic3r/ModelArrange.hpp
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@ -99,54 +99,55 @@ namespace bgi = boost::geometry::index;
using SpatElement = std::pair<Box, unsigned>;
using SpatIndex = bgi::rtree< SpatElement, bgi::rstar<16, 4> >;
using ItemGroup = std::vector<std::reference_wrapper<Item>>;
template<class TBin>
using TPacker = typename placers::_NofitPolyPlacer<PolygonImpl, TBin>;
const double BIG_ITEM_TRESHOLD = 0.02;
Box boundingBox(const Box& pilebb, const Box& ibb ) {
auto& pminc = pilebb.minCorner();
auto& pmaxc = pilebb.maxCorner();
auto& iminc = ibb.minCorner();
auto& imaxc = ibb.maxCorner();
PointImpl minc, maxc;
setX(minc, std::min(getX(pminc), getX(iminc)));
setY(minc, std::min(getY(pminc), getY(iminc)));
setX(maxc, std::max(getX(pmaxc), getX(imaxc)));
setY(maxc, std::max(getY(pmaxc), getY(imaxc)));
return Box(minc, maxc);
}
std::tuple<double /*score*/, Box /*farthest point from bin center*/>
objfunc(const PointImpl& bincenter,
double /*bin_area*/,
ShapeLike::Shapes<PolygonImpl>& pile, // The currently arranged pile
double /*pile_area*/,
const shapelike::Shapes<PolygonImpl>& merged_pile,
const Box& pilebb,
const ItemGroup& items,
const Item &item,
double bin_area,
double norm, // A norming factor for physical dimensions
std::vector<double>& areacache, // pile item areas will be cached
// a spatial index to quickly get neighbors of the candidate item
SpatIndex& spatindex
const SpatIndex& spatindex,
const ItemGroup& remaining
)
{
using pl = PointLike;
using sl = ShapeLike;
using Coord = TCoord<PointImpl>;
static const double BIG_ITEM_TRESHOLD = 0.2;
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 normarea = [norm](double area) { return std::sqrt(area)/norm; };
// 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(normarea(areacache[idx]) > BIG_ITEM_TRESHOLD)
spatindex.insert({sl::boundingBox(p), idx});
}
idx++;
}
auto isBig = [bin_area](double a) {
return a/bin_area > BIG_ITEM_TRESHOLD ;
};
// Candidate item bounding box
auto ibb = item.boundingBox();
auto ibb = sl::boundingBox(item.transformedShape());
// 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();
auto fullbb = boundingBox(pilebb, ibb);
// The bounding box of the big items (they will accumulate in the center
// of the pile
@ -157,19 +158,11 @@ objfunc(const PointImpl& bincenter,
boost::geometry::convert(boostbb, bigbb);
}
// The size indicator of the candidate item. This is not the area,
// but almost...
double item_normarea = normarea(item.area());
// Will hold the resulting score
double score = 0;
if(item_normarea > BIG_ITEM_TRESHOLD) {
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
@ -192,46 +185,62 @@ objfunc(const PointImpl& bincenter,
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;
double density = 0;
// 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<double>::max();
if(remaining.empty()) {
auto& trsh = item.transformedShape();
auto mp = merged_pile;
mp.emplace_back(item.transformedShape());
auto chull = sl::convexHull(mp);
auto querybb = item.boundingBox();
placers::EdgeCache<PolygonImpl> ec(chull);
// Query the spatial index for the neigbours
std::vector<SpatElement> result;
spatindex.query(bgi::intersects(querybb), std::back_inserter(result));
double circ = ec.circumference() / norm;
double bcirc = 2.0*(fullbb.width() + fullbb.height()) / norm;
score = 0.5*circ + 0.5*bcirc;
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<PolygonImpl>{p, trsh});
auto bbarea = bb.area();
auto ascore = 1.0 - (item.area() + parea)/bbarea;
} else {
// Prepare a variable for the alignment score.
// This will indicate: how well is the candidate item aligned with
// its neighbors. We will check the alignment 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 = 1.0;
if(ascore < alignment_score) alignment_score = ascore;
density = (fullbb.width()*fullbb.height()) / (norm*norm);
auto querybb = item.boundingBox();
// Query the spatial index for the neighbors
std::vector<SpatElement> result;
result.reserve(spatindex.size());
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;
Item& p = items[idx];
auto parea = p.area();
if(std::abs(1.0 - parea/item.area()) < 1e-6) {
auto bb = boundingBox(p.boundingBox(), ibb);
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 neighbors
if(result.empty())
score = 0.5 * dist + 0.5 * density;
else
score = 0.45 * dist + 0.45 * density + 0.1 * alignment_score;
}
// 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
auto C = 0.33;
score = C * dist + C * density + C * alignment_score;
} else if( item_normarea < BIG_ITEM_TRESHOLD && spatindex.empty()) {
// If there are no big items, only small, we should consider the
// density here as well to not get silly results
} else if( !isBig(item.area()) && spatindex.empty()) {
auto bindist = pl::distance(ibb.center(), bincenter) / norm;
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
score = ROUNDNESS_RATIO * bindist + DENSITY_RATIO * density;
// Bindist is surprisingly enough...
score = bindist;
} else {
// Here there are the small items that should be placed around the
// already processed bigger items.
@ -259,7 +268,9 @@ void fillConfig(PConf& pcfg) {
// The accuracy of optimization.
// Goes from 0.0 to 1.0 and scales performance as well
pcfg.accuracy = 0.6f;
pcfg.accuracy = 0.65f;
pcfg.parallel = true;
}
template<class TBin>
@ -268,31 +279,62 @@ class AutoArranger {};
template<class TBin>
class _ArrBase {
protected:
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, TBin>;
using Placer = TPacker<TBin>;
using Selector = FirstFitSelection;
using Packer = Arranger<Placer, Selector>;
using Packer = Nester<Placer, Selector>;
using PConfig = typename Packer::PlacementConfig;
using Distance = TCoord<PointImpl>;
using Pile = ShapeLike::Shapes<PolygonImpl>;
using Pile = sl::Shapes<PolygonImpl>;
Packer pck_;
PConfig pconf_; // Placement configuration
double bin_area_;
std::vector<double> areacache_;
SpatIndex rtree_;
double norm_;
Pile merged_pile_;
Box pilebb_;
ItemGroup remaining_;
ItemGroup items_;
public:
_ArrBase(const TBin& bin, Distance dist,
std::function<void(unsigned)> progressind):
pck_(bin, dist), bin_area_(ShapeLike::area<PolygonImpl>(bin))
pck_(bin, dist), bin_area_(sl::area(bin)),
norm_(std::sqrt(sl::area(bin)))
{
fillConfig(pconf_);
pconf_.before_packing =
[this](const Pile& merged_pile, // merged pile
const ItemGroup& items, // packed items
const ItemGroup& remaining) // future items to be packed
{
items_ = items;
merged_pile_ = merged_pile;
remaining_ = remaining;
pilebb_ = sl::boundingBox(merged_pile);
rtree_.clear();
// We will treat big items (compared to the print bed) differently
auto isBig = [this](double a) {
return a/bin_area_ > BIG_ITEM_TRESHOLD ;
};
for(unsigned idx = 0; idx < items.size(); ++idx) {
Item& itm = items[idx];
if(isBig(itm.area())) rtree_.insert({itm.boundingBox(), idx});
}
};
pck_.progressIndicator(progressind);
}
template<class...Args> inline IndexedPackGroup operator()(Args&&...args) {
areacache_.clear();
return pck_.arrangeIndexed(std::forward<Args>(args)...);
rtree_.clear();
return pck_.executeIndexed(std::forward<Args>(args)...);
}
};
@ -304,22 +346,69 @@ public:
std::function<void(unsigned)> progressind):
_ArrBase<Box>(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_);
pconf_.object_function = [this, bin] (const Item &item) {
auto result = objfunc(bin.center(),
merged_pile_,
pilebb_,
items_,
item,
bin_area_,
norm_,
rtree_,
remaining_);
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;
double miss = Placer::overfit(fullbb, bin);
miss = miss > 0? miss : 0;
score += miss*miss;
return score;
};
pck_.configure(pconf_);
}
};
using lnCircle = libnest2d::_Circle<libnest2d::PointImpl>;
template<>
class AutoArranger<lnCircle>: public _ArrBase<lnCircle> {
public:
AutoArranger(const lnCircle& bin, Distance dist,
std::function<void(unsigned)> progressind):
_ArrBase<lnCircle>(bin, dist, progressind) {
pconf_.object_function = [this, &bin] (const Item &item) {
auto result = objfunc(bin.center(),
merged_pile_,
pilebb_,
items_,
item,
bin_area_,
norm_,
rtree_,
remaining_);
double score = std::get<0>(result);
auto isBig = [this](const Item& itm) {
return itm.area()/bin_area_ > BIG_ITEM_TRESHOLD ;
};
if(isBig(item)) {
auto mp = merged_pile_;
mp.push_back(item.transformedShape());
auto chull = sl::convexHull(mp);
double miss = Placer::overfit(chull, bin);
if(miss < 0) miss = 0;
score += miss*miss;
}
return score;
};
@ -335,27 +424,20 @@ public:
std::function<void(unsigned)> progressind):
_ArrBase<PolygonImpl>(bin, dist, progressind)
{
pconf_.object_function = [this, &bin] (
Pile& pile,
const Item &item,
double pile_area,
double norm,
double /*penality*/) {
pconf_.object_function = [this, &bin] (const Item &item) {
auto binbb = ShapeLike::boundingBox(bin);
auto result = objfunc(binbb.center(), bin_area_, pile,
pile_area, item, norm, areacache_, rtree_);
auto binbb = sl::boundingBox(bin);
auto result = objfunc(binbb.center(),
merged_pile_,
pilebb_,
items_,
item,
bin_area_,
norm_,
rtree_,
remaining_);
double score = std::get<0>(result);
pile.emplace_back(item.transformedShape());
auto chull = ShapeLike::convexHull(pile);
pile.pop_back();
// If it does not fit into the print bed we will beat it with a
// large penality. If we would not do this, there would be only one
// big pile that doesn't care whether it fits onto the print bed.
if(!Placer::wouldFit(chull, bin)) score += norm;
return score;
};
@ -370,15 +452,17 @@ public:
AutoArranger(Distance dist, std::function<void(unsigned)> progressind):
_ArrBase<Box>(Box(0, 0), dist, progressind)
{
this->pconf_.object_function = [this] (
Pile& pile,
const Item &item,
double pile_area,
double norm,
double /*penality*/) {
this->pconf_.object_function = [this] (const Item &item) {
auto result = objfunc({0, 0}, 0, pile, pile_area,
item, norm, areacache_, rtree_);
auto result = objfunc({0, 0},
merged_pile_,
pilebb_,
items_,
item,
0,
norm_,
rtree_,
remaining_);
return std::get<0>(result);
};
@ -440,16 +524,113 @@ ShapeData2D projectModelFromTop(const Slic3r::Model &model) {
return ret;
}
enum BedShapeHint {
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_); }
inline operator lnCircle() {
return lnCircle({center_(0), center_(1)}, radius_);
}
};
enum class BedShapeType {
BOX,
CIRCLE,
IRREGULAR,
WHO_KNOWS
};
BedShapeHint bedShape(const Slic3r::Polyline& /*bed*/) {
struct BedShapeHint {
BedShapeType type;
/*union*/ struct { // I know but who cares...
Circle circ;
BoundingBox box;
Polyline polygon;
} shape;
};
BedShapeHint bedShape(const Polyline& bed) {
BedShapeHint ret;
auto x = [](const Point& p) { return p(0); };
auto y = [](const Point& p) { return p(1); };
auto width = [x](const BoundingBox& box) {
return x(box.max) - x(box.min);
};
auto height = [y](const BoundingBox& box) {
return y(box.max) - y(box.min);
};
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 distance_to = [x, y](const Point& p1, const Point& p2) {
double dx = x(p2) - x(p1);
double dy = y(p2) - y(p1);
return std::sqrt(dx*dx + dy*dy);
};
auto bb = bed.bounding_box();
auto isCircle = [bb, distance_to](const Polyline& polygon) {
auto center = bb.center();
std::vector<double> vertex_distances;
double avg_dist = 0;
for (auto pt: polygon.points)
{
double distance = distance_to(center, 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 BOX;
return ret;
}
void applyResult(
@ -468,8 +649,7 @@ void applyResult(
// appropriately
auto off = item.translation();
Radians rot = item.rotation();
Vec2d foff(off.X*SCALING_FACTOR + batch_offset,
off.Y*SCALING_FACTOR);
Vec2d foff(off.X*SCALING_FACTOR + batch_offset, off.Y*SCALING_FACTOR);
// write the tranformation data into the model instance
inst_ptr->rotation = rot;
@ -525,7 +705,10 @@ bool arrange(Model &model, coordf_t min_obj_distance,
});
IndexedPackGroup result;
BoundingBox bbb(bed.points);
if(bedhint.type == BedShapeType::WHO_KNOWS) bedhint = bedShape(bed);
BoundingBox bbb(bed);
auto binbb = Box({
static_cast<libnest2d::Coord>(bbb.min(0)),
@ -536,8 +719,8 @@ bool arrange(Model &model, coordf_t min_obj_distance,
static_cast<libnest2d::Coord>(bbb.max(1))
});
switch(bedhint) {
case BOX: {
switch(bedhint.type) {
case BedShapeType::BOX: {
// Create the arranger for the box shaped bed
AutoArranger<Box> arrange(binbb, min_obj_distance, progressind);
@ -547,16 +730,22 @@ bool arrange(Model &model, coordf_t min_obj_distance,
result = arrange(shapes.begin(), shapes.end());
break;
}
case CIRCLE:
case BedShapeType::CIRCLE: {
auto c = bedhint.shape.circ;
auto cc = lnCircle(c);
AutoArranger<lnCircle> arrange(cc, min_obj_distance, progressind);
result = arrange(shapes.begin(), shapes.end());
break;
case IRREGULAR:
case WHO_KNOWS: {
}
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));
// std::cout << ShapeLike::toString(irrbed) << std::endl;
P irrbed = sl::create<PolygonImpl>(std::move(ctour));
AutoArranger<P> arrange(irrbed, min_obj_distance, progressind);
@ -567,6 +756,8 @@ bool arrange(Model &model, coordf_t min_obj_distance,
}
};
if(result.empty()) return false;
if(first_bin_only) {
applyResult(result.front(), 0, shapemap);
} else {