PrusaSlicer-NonPlainar/src/libslic3r/ModelArrange.cpp

769 lines
24 KiB
C++

#include "ModelArrange.hpp"
#include "Model.hpp"
#include "SVG.hpp"
#include <libnest2d.h>
#include <numeric>
#include <ClipperUtils.hpp>
#include <boost/geometry/index/rtree.hpp>
namespace Slic3r {
namespace arr {
using namespace libnest2d;
std::string toString(const Model& model, bool holes = true) {
std::stringstream ss;
ss << "{\n";
for(auto objptr : model.objects) {
if(!objptr) continue;
auto rmesh = objptr->raw_mesh();
for(auto objinst : objptr->instances) {
if(!objinst) continue;
Slic3r::TriangleMesh tmpmesh = rmesh;
// CHECK_ME -> Is the following correct ?
tmpmesh.scale(objinst->get_scaling_factor());
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
for(auto& expoly_complex : expolys) {
auto tmp = expoly_complex.simplify(1.0/SCALING_FACTOR);
if(tmp.empty()) continue;
auto expoly = tmp.front();
expoly.contour.make_clockwise();
for(auto& h : expoly.holes) h.make_counter_clockwise();
ss << "\t{\n";
ss << "\t\t{\n";
for(auto v : expoly.contour.points) ss << "\t\t\t{"
<< v(0) << ", "
<< v(1) << "},\n";
{
auto v = expoly.contour.points.front();
ss << "\t\t\t{" << v(0) << ", " << v(1) << "},\n";
}
ss << "\t\t},\n";
// Holes:
ss << "\t\t{\n";
if(holes) for(auto h : expoly.holes) {
ss << "\t\t\t{\n";
for(auto v : h.points) ss << "\t\t\t\t{"
<< v(0) << ", "
<< v(1) << "},\n";
{
auto v = h.points.front();
ss << "\t\t\t\t{" << v(0) << ", " << v(1) << "},\n";
}
ss << "\t\t\t},\n";
}
ss << "\t\t},\n";
ss << "\t},\n";
}
}
}
ss << "}\n";
return ss.str();
}
void toSVG(SVG& svg, const Model& model) {
for(auto objptr : model.objects) {
if(!objptr) continue;
auto rmesh = objptr->raw_mesh();
for(auto objinst : objptr->instances) {
if(!objinst) continue;
Slic3r::TriangleMesh tmpmesh = rmesh;
tmpmesh.scale(objinst->get_scaling_factor());
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
svg.draw(expolys);
}
}
}
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,
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
// a spatial index to quickly get neighbors of the candidate item
const SpatIndex& spatindex,
const SpatIndex& smalls_spatindex,
const ItemGroup& remaining
)
{
using Coord = TCoord<PointImpl>;
static const double ROUNDNESS_RATIO = 0.5;
static const double DENSITY_RATIO = 1.0 - ROUNDNESS_RATIO;
// We will treat big items (compared to the print bed) differently
auto isBig = [bin_area](double a) {
return a/bin_area > BIG_ITEM_TRESHOLD ;
};
// Candidate item bounding box
auto ibb = sl::boundingBox(item.transformedShape());
// Calculate the full bounding box of the pile with the candidate item
auto fullbb = boundingBox(pilebb, ibb);
// The bounding box of the big items (they will accumulate in the center
// of the pile
Box bigbb;
if(spatindex.empty()) bigbb = fullbb;
else {
auto boostbb = spatindex.bounds();
boost::geometry::convert(boostbb, bigbb);
}
// Will hold the resulting score
double score = 0;
if(isBig(item.area()) || spatindex.empty()) {
// This branch is for the bigger items..
auto minc = ibb.minCorner(); // bottom left corner
auto maxc = ibb.maxCorner(); // top right corner
// top left and bottom right corners
auto top_left = PointImpl{getX(minc), getY(maxc)};
auto bottom_right = PointImpl{getX(maxc), getY(minc)};
// Now the distance of the gravity center will be calculated to the
// five anchor points and the smallest will be chosen.
std::array<double, 5> dists;
auto cc = fullbb.center(); // The gravity center
dists[0] = pl::distance(minc, cc);
dists[1] = pl::distance(maxc, cc);
dists[2] = pl::distance(ibb.center(), cc);
dists[3] = pl::distance(top_left, cc);
dists[4] = pl::distance(bottom_right, cc);
// The smalles distance from the arranged pile center:
auto dist = *(std::min_element(dists.begin(), dists.end())) / norm;
auto bindist = pl::distance(ibb.center(), bincenter) / norm;
dist = 0.8*dist + 0.2*bindist;
// Density is the pack density: how big is the arranged pile
double density = 0;
if(remaining.empty()) {
auto mp = merged_pile;
mp.emplace_back(item.transformedShape());
auto chull = sl::convexHull(mp);
placers::EdgeCache<PolygonImpl> ec(chull);
double circ = ec.circumference() / norm;
double bcirc = 2.0*(fullbb.width() + fullbb.height()) / norm;
score = 0.5*circ + 0.5*bcirc;
} 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;
density = std::sqrt((fullbb.width() / norm )*
(fullbb.height() / norm));
auto querybb = item.boundingBox();
// Query the spatial index for the neighbors
std::vector<SpatElement> result;
result.reserve(spatindex.size());
if(isBig(item.area())) {
spatindex.query(bgi::intersects(querybb),
std::back_inserter(result));
} else {
smalls_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 = 0.40 * dist + 0.40 * density + 0.2 * alignment_score;
}
} else {
// Here there are the small items that should be placed around the
// already processed bigger items.
// No need to play around with the anchor points, the center will be
// just fine for small items
score = pl::distance(ibb.center(), bigbb.center()) / norm;
}
return std::make_tuple(score, fullbb);
}
template<class PConf>
void fillConfig(PConf& pcfg) {
// Align the arranged pile into the center of the bin
pcfg.alignment = PConf::Alignment::CENTER;
// Start placing the items from the center of the print bed
pcfg.starting_point = PConf::Alignment::CENTER;
// TODO cannot use rotations until multiple objects of same geometry can
// handle different rotations
// arranger.useMinimumBoundigBoxRotation();
pcfg.rotations = { 0.0 };
// The accuracy of optimization.
// Goes from 0.0 to 1.0 and scales performance as well
pcfg.accuracy = 0.65f;
pcfg.parallel = true;
}
template<class TBin>
class AutoArranger {};
template<class TBin>
class _ArrBase {
protected:
using Placer = TPacker<TBin>;
using Selector = FirstFitSelection;
using Packer = Nester<Placer, Selector>;
using PConfig = typename Packer::PlacementConfig;
using Distance = TCoord<PointImpl>;
using Pile = sl::Shapes<PolygonImpl>;
Packer m_pck;
PConfig m_pconf; // Placement configuration
double m_bin_area;
SpatIndex m_rtree;
SpatIndex m_smallsrtree;
double m_norm;
Pile m_merged_pile;
Box m_pilebb;
ItemGroup m_remaining;
ItemGroup m_items;
public:
_ArrBase(const TBin& bin, Distance dist,
std::function<void(unsigned)> progressind,
std::function<bool(void)> stopcond):
m_pck(bin, dist), m_bin_area(sl::area(bin)),
m_norm(std::sqrt(sl::area(bin)))
{
fillConfig(m_pconf);
m_pconf.before_packing =
[this](const Pile& merged_pile, // merged pile
const ItemGroup& items, // packed items
const ItemGroup& remaining) // future items to be packed
{
m_items = items;
m_merged_pile = merged_pile;
m_remaining = remaining;
m_pilebb = sl::boundingBox(merged_pile);
m_rtree.clear();
m_smallsrtree.clear();
// We will treat big items (compared to the print bed) differently
auto isBig = [this](double a) {
return a/m_bin_area > BIG_ITEM_TRESHOLD ;
};
for(unsigned idx = 0; idx < items.size(); ++idx) {
Item& itm = items[idx];
if(isBig(itm.area())) m_rtree.insert({itm.boundingBox(), idx});
m_smallsrtree.insert({itm.boundingBox(), idx});
}
};
m_pck.progressIndicator(progressind);
m_pck.stopCondition(stopcond);
}
template<class...Args> inline IndexedPackGroup operator()(Args&&...args) {
m_rtree.clear();
return m_pck.executeIndexed(std::forward<Args>(args)...);
}
};
template<>
class AutoArranger<Box>: public _ArrBase<Box> {
public:
AutoArranger(const Box& bin, Distance dist,
std::function<void(unsigned)> progressind,
std::function<bool(void)> stopcond):
_ArrBase<Box>(bin, dist, progressind, stopcond)
{
m_pconf.object_function = [this, bin] (const Item &item) {
auto result = objfunc(bin.center(),
m_merged_pile,
m_pilebb,
m_items,
item,
m_bin_area,
m_norm,
m_rtree,
m_smallsrtree,
m_remaining);
double score = std::get<0>(result);
auto& fullbb = std::get<1>(result);
double miss = Placer::overfit(fullbb, bin);
miss = miss > 0? miss : 0;
score += miss*miss;
return score;
};
m_pck.configure(m_pconf);
}
};
using lnCircle = libnest2d::_Circle<libnest2d::PointImpl>;
inline lnCircle to_lnCircle(const Circle& circ) {
return lnCircle({circ.center()(0), circ.center()(1)}, circ.radius());
}
template<>
class AutoArranger<lnCircle>: public _ArrBase<lnCircle> {
public:
AutoArranger(const lnCircle& bin, Distance dist,
std::function<void(unsigned)> progressind,
std::function<bool(void)> stopcond):
_ArrBase<lnCircle>(bin, dist, progressind, stopcond) {
m_pconf.object_function = [this, &bin] (const Item &item) {
auto result = objfunc(bin.center(),
m_merged_pile,
m_pilebb,
m_items,
item,
m_bin_area,
m_norm,
m_rtree,
m_smallsrtree,
m_remaining);
double score = std::get<0>(result);
auto isBig = [this](const Item& itm) {
return itm.area()/m_bin_area > BIG_ITEM_TRESHOLD ;
};
if(isBig(item)) {
auto mp = m_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;
};
m_pck.configure(m_pconf);
}
};
template<>
class AutoArranger<PolygonImpl>: public _ArrBase<PolygonImpl> {
public:
AutoArranger(const PolygonImpl& bin, Distance dist,
std::function<void(unsigned)> progressind,
std::function<bool(void)> stopcond):
_ArrBase<PolygonImpl>(bin, dist, progressind, stopcond)
{
m_pconf.object_function = [this, &bin] (const Item &item) {
auto binbb = sl::boundingBox(bin);
auto result = objfunc(binbb.center(),
m_merged_pile,
m_pilebb,
m_items,
item,
m_bin_area,
m_norm,
m_rtree,
m_smallsrtree,
m_remaining);
double score = std::get<0>(result);
return score;
};
m_pck.configure(m_pconf);
}
};
template<> // Specialization with no bin
class AutoArranger<bool>: public _ArrBase<Box> {
public:
AutoArranger(Distance dist, std::function<void(unsigned)> progressind,
std::function<bool(void)> stopcond):
_ArrBase<Box>(Box(0, 0), dist, progressind, stopcond)
{
this->m_pconf.object_function = [this] (const Item &item) {
auto result = objfunc({0, 0},
m_merged_pile,
m_pilebb,
m_items,
item,
0,
m_norm,
m_rtree,
m_smallsrtree,
m_remaining);
return std::get<0>(result);
};
this->m_pck.configure(m_pconf);
}
};
// A container which stores a pointer to the 3D object and its projected
// 2D shape from top view.
using ShapeData2D =
std::vector<std::pair<Slic3r::ModelInstance*, Item>>;
ShapeData2D projectModelFromTop(const Slic3r::Model &model) {
ShapeData2D ret;
auto s = std::accumulate(model.objects.begin(), model.objects.end(), size_t(0),
[](size_t s, ModelObject* o){
return s + o->instances.size();
});
ret.reserve(s);
for(ModelObject* objptr : model.objects) {
if(objptr) {
TriangleMesh rmesh = objptr->raw_mesh();
ModelInstance * finst = objptr->instances.front();
// Object instances should carry the same scaling and
// x, y rotation that is why we use the first instance
rmesh.scale(finst->get_scaling_factor());
rmesh.rotate_x(float(finst->get_rotation()(X)));
rmesh.rotate_y(float(finst->get_rotation()(Y)));
// TODO export the exact 2D projection
auto p = rmesh.convex_hull();
p.make_clockwise();
p.append(p.first_point());
auto clpath = Slic3rMultiPoint_to_ClipperPath(p);
for(ModelInstance* objinst : objptr->instances) {
if(objinst) {
ClipperLib::PolygonImpl pn;
pn.Contour = clpath;
// Efficient conversion to item.
Item item(std::move(pn));
// Invalid geometries would throw exceptions when arranging
if(item.vertexCount() > 3) {
item.rotation(objinst->get_rotation(Z));
item.translation({
ClipperLib::cInt(objinst->get_offset(X)/SCALING_FACTOR),
ClipperLib::cInt(objinst->get_offset(Y)/SCALING_FACTOR)
});
ret.emplace_back(objinst, item);
}
}
}
}
}
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 transformation data from the item object and scale it
// appropriately
auto off = item.translation();
Radians rot = item.rotation();
Vec3d foff(off.X*SCALING_FACTOR + batch_offset,
off.Y*SCALING_FACTOR,
inst_ptr->get_offset()(Z));
// write the transformation data into the model instance
inst_ptr->set_rotation(Z, rot);
inst_ptr->set_offset(foff);
}
}
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 ret;
}
bool arrange(Model &model,
coord_t min_obj_distance,
const Polyline &bed,
BedShapeHint bedhint,
bool first_bin_only,
std::function<void (unsigned)> progressind,
std::function<bool ()> stopcondition)
{
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 there is no hint about the shape, we will try to guess
if(bedhint.type == BedShapeType::WHO_KNOWS) bedhint = bedShape(bed);
BoundingBox bbb(bed);
auto& cfn = stopcondition;
auto binbb = Box({
static_cast<libnest2d::Coord>(bbb.min(0)),
static_cast<libnest2d::Coord>(bbb.min(1))
},
{
static_cast<libnest2d::Coord>(bbb.max(0)),
static_cast<libnest2d::Coord>(bbb.max(1))
});
switch(bedhint.type) {
case BedShapeType::BOX: {
// Create the arranger for the box shaped bed
AutoArranger<Box> arrange(binbb, min_obj_distance, progressind, cfn);
// 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 = to_lnCircle(c);
AutoArranger<lnCircle> arrange(cc, min_obj_distance, progressind, cfn);
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 = sl::create<PolygonImpl>(std::move(ctour));
AutoArranger<P> arrange(irrbed, min_obj_distance, progressind, cfn);
// Arrange and return the items with their respective indices within the
// input sequence.
result = arrange(shapes.begin(), shapes.end());
break;
}
};
if(result.empty() || stopcondition()) 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;
}
}
}