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Prepare integration for arbitrary shaped print beds.

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tamasmeszaros 2018-07-30 16:41:35 +02:00
commit 6cdec7ac9a
12 changed files with 555 additions and 549 deletions
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2
resources/profiles/PrusaResearch.idx
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@ -1,5 +1,5 @@
min_slic3r_version = 1.41.0-alpha
0.2.0-alpha3
0.2.0-alpha3 Adjusted machine limits for time estimates, added filament density and cost,
0.2.0-alpha2 Renamed the key MK3SMMU to MK3MMU2, added a generic PLA MMU2 material
0.2.0-alpha1 added initial profiles for the i3 MK3 Multi Material Upgrade 2.0
0.2.0-alpha moved machine limits from the start G-code to the new print profile parameters

2
xs/CMakeLists.txt
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@ -136,6 +136,7 @@ add_library(libslic3r STATIC
${LIBDIR}/libslic3r/Line.hpp
${LIBDIR}/libslic3r/Model.cpp
${LIBDIR}/libslic3r/Model.hpp
${LIBDIR}/libslic3r/ModelArrange.hpp
${LIBDIR}/libslic3r/MotionPlanner.cpp
${LIBDIR}/libslic3r/MotionPlanner.hpp
${LIBDIR}/libslic3r/MultiPoint.cpp
@ -729,6 +730,7 @@ set(LIBNEST2D_UNITTESTS ON CACHE BOOL "Force generating unittests for libnest2d"
add_subdirectory(${LIBDIR}/libnest2d)
target_include_directories(libslic3r PUBLIC BEFORE ${LIBNEST2D_INCLUDES})
target_include_directories(libslic3r_gui PUBLIC BEFORE ${LIBNEST2D_INCLUDES})
message(STATUS "Libnest2D Libraries: ${LIBNEST2D_LIBRARIES}")
target_link_libraries(libslic3r ${LIBNEST2D_LIBRARIES})

186
xs/src/libnest2d/examples/main.cpp
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@ -544,25 +544,25 @@ void arrangeRectangles() {
// input.insert(input.end(), proba.begin(), proba.end());
// input.insert(input.end(), crasher.begin(), crasher.end());
// Box bin(250*SCALE, 210*SCALE);
PolygonImpl bin = {
{
{25*SCALE, 0},
{0, 25*SCALE},
{0, 225*SCALE},
{25*SCALE, 250*SCALE},
{225*SCALE, 250*SCALE},
{250*SCALE, 225*SCALE},
{250*SCALE, 25*SCALE},
{225*SCALE, 0},
{25*SCALE, 0}
},
{}
};
Box bin(250*SCALE, 210*SCALE);
// PolygonImpl bin = {
// {
// {25*SCALE, 0},
// {0, 25*SCALE},
// {0, 225*SCALE},
// {25*SCALE, 250*SCALE},
// {225*SCALE, 250*SCALE},
// {250*SCALE, 225*SCALE},
// {250*SCALE, 25*SCALE},
// {225*SCALE, 0},
// {25*SCALE, 0}
// },
// {}
// };
auto min_obj_distance = static_cast<Coord>(0*SCALE);
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, PolygonImpl>;
using Placer = strategies::_NofitPolyPlacer<PolygonImpl, Box>;
using Packer = Arranger<Placer, FirstFitSelection>;
Packer arrange(bin, min_obj_distance);
@ -571,102 +571,102 @@ void arrangeRectangles() {
pconf.alignment = Placer::Config::Alignment::CENTER;
pconf.starting_point = Placer::Config::Alignment::CENTER;
pconf.rotations = {0.0/*, Pi/2.0, Pi, 3*Pi/2*/};
pconf.accuracy = 1.0;
pconf.accuracy = 0.5f;
auto bincenter = ShapeLike::boundingBox(bin).center();
pconf.object_function = [&bin, bincenter](
Placer::Pile pile, const Item& item,
double /*area*/, double norm, double penality) {
// auto bincenter = ShapeLike::boundingBox(bin).center();
// pconf.object_function = [&bin, bincenter](
// Placer::Pile pile, const Item& item,
// double /*area*/, double norm, double penality) {
using pl = PointLike;
// using pl = PointLike;
static const double BIG_ITEM_TRESHOLD = 0.2;
static const double GRAVITY_RATIO = 0.5;
static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
// static const double BIG_ITEM_TRESHOLD = 0.2;
// static const double GRAVITY_RATIO = 0.5;
// static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
// We will treat big items (compared to the print bed) differently
NfpPlacer::Pile bigs;
bigs.reserve(pile.size());
for(auto& p : pile) {
auto pbb = ShapeLike::boundingBox(p);
auto na = std::sqrt(pbb.width()*pbb.height())/norm;
if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
}
// // We will treat big items (compared to the print bed) differently
// NfpPlacer::Pile bigs;
// bigs.reserve(pile.size());
// for(auto& p : pile) {
// auto pbb = ShapeLike::boundingBox(p);
// auto na = std::sqrt(pbb.width()*pbb.height())/norm;
// if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
// }
// Candidate item bounding box
auto ibb = item.boundingBox();
// // Candidate item bounding box
// auto ibb = item.boundingBox();
// 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();
// // 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();
// The bounding box of the big items (they will accumulate in the center
// of the pile
auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
// // The bounding box of the big items (they will accumulate in the center
// // of the pile
// auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
// The size indicator of the candidate item. This is not the area,
// but almost...
auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
// // The size indicator of the candidate item. This is not the area,
// // but almost...
// auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
// Will hold the resulting score
double score = 0;
// // Will hold the resulting score
// double score = 0;
if(itemnormarea > BIG_ITEM_TRESHOLD) {
// 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 unwanted strange arrangements.
// if(itemnormarea > BIG_ITEM_TRESHOLD) {
// // 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 unwanted strange arrangements.
auto minc = ibb.minCorner(); // bottom left corner
auto maxc = ibb.maxCorner(); // top right corner
// 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)};
// // top left and bottom right corners
// auto top_left = PointImpl{getX(minc), getY(maxc)};
// auto bottom_right = PointImpl{getX(maxc), getY(minc)};
auto cc = fullbb.center(); // The gravity center
// auto cc = fullbb.center(); // The gravity center
// Now the distnce of the gravity center will be calculated to the
// five anchor points and the smallest will be chosen.
std::array<double, 5> dists;
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);
// // Now the distnce of the gravity center will be calculated to the
// // five anchor points and the smallest will be chosen.
// std::array<double, 5> dists;
// 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);
auto dist = *(std::min_element(dists.begin(), dists.end())) / norm;
// 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;
// // Density is the pack density: how big is the arranged pile
// auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
// The score is a weighted sum of the distance from pile center
// and the pile size
score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
// // The score is a weighted sum of the distance from pile center
// // and the pile size
// score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
} else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
// If there are no big items, only small, we should consider the
// density here as well to not get silly results
auto bindist = pl::distance(ibb.center(), bincenter) / norm;
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
} 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;
}
// } else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
// // If there are no big items, only small, we should consider the
// // density here as well to not get silly results
// auto bindist = pl::distance(ibb.center(), bincenter) / norm;
// auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
// score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
// } 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;
// }
// 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(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
// // 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(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
return score;
};
// return score;
// };
Packer::SelectionConfig sconf;
// sconf.allow_parallel = false;
@ -707,7 +707,7 @@ void arrangeRectangles() {
std::vector<double> eff;
eff.reserve(result.size());
auto bin_area = ShapeLike::area(bin);
auto bin_area = ShapeLike::area<PolygonImpl>(bin);
for(auto& r : result) {
double a = 0;
std::for_each(r.begin(), r.end(), [&a] (Item& e ){ a += e.area(); });

2
xs/src/libnest2d/libnest2d.h
View file

@ -6,7 +6,7 @@
#include <libnest2d/clipper_backend/clipper_backend.hpp>
// We include the stock optimizers for local and global optimization
#include <libnest2d/optimizers/simplex.hpp> // Local simplex for NfpPlacer
#include <libnest2d/optimizers/subplex.hpp> // Local subplex for NfpPlacer
#include <libnest2d/optimizers/genetic.hpp> // Genetic for min. bounding box
#include <libnest2d/libnest2d.hpp>

10
xs/src/libnest2d/libnest2d/libnest2d.hpp
View file

@ -53,8 +53,8 @@ class _Item {
enum class Convexity: char {
UNCHECKED,
TRUE,
FALSE
C_TRUE,
C_FALSE
};
mutable Convexity convexity_ = Convexity::UNCHECKED;
@ -213,10 +213,10 @@ public:
switch(convexity_) {
case Convexity::UNCHECKED:
ret = sl::isConvex<RawShape>(sl::getContour(transformedShape()));
convexity_ = ret? Convexity::TRUE : Convexity::FALSE;
convexity_ = ret? Convexity::C_TRUE : Convexity::C_FALSE;
break;
case Convexity::TRUE: ret = true; break;
case Convexity::FALSE:;
case Convexity::C_TRUE: ret = true; break;
case Convexity::C_FALSE:;
}
return ret;

2
xs/src/libnest2d/libnest2d/placers/nfpplacer.hpp
View file

@ -625,7 +625,7 @@ public:
opt::StopCriteria stopcr;
stopcr.max_iterations = 1000;
stopcr.absolute_score_difference = 1e-20*norm_;
opt::TOptimizer<opt::Method::L_SIMPLEX> solver(stopcr);
opt::TOptimizer<opt::Method::L_SUBPLEX> solver(stopcr);
Optimum optimum(0, 0);
double best_score = penality_;

455
xs/src/libslic3r/Model.cpp
View file

@ -7,11 +7,6 @@
#include "Format/STL.hpp"
#include "Format/3mf.hpp"
#include <numeric>
#include <libnest2d.h>
#include <ClipperUtils.hpp>
#include "slic3r/GUI/GUI.hpp"
#include <float.h>
#include <boost/algorithm/string/predicate.hpp>
@ -304,438 +299,36 @@ static bool _arrange(const Pointfs &sizes, coordf_t dist, const BoundingBoxf* bb
return result;
}
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;
tmpmesh.scale(objinst->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.x << ", "
<< v.y << "},\n";
{
auto v = expoly.contour.points.front();
ss << "\t\t\t{" << v.x << ", " << v.y << "},\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.x << ", "
<< v.y << "},\n";
{
auto v = h.points.front();
ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\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->scaling_factor);
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
svg.draw(expolys);
}
}
}
// 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(), 0,
[](size_t s, ModelObject* o){
return s + o->instances.size();
});
ret.reserve(s);
for(auto objptr : model.objects) {
if(objptr) {
auto rmesh = objptr->raw_mesh();
for(auto objinst : objptr->instances) {
if(objinst) {
Slic3r::TriangleMesh tmpmesh = rmesh;
ClipperLib::PolygonImpl pn;
tmpmesh.scale(objinst->scaling_factor);
// TODO export the exact 2D projection
auto p = tmpmesh.convex_hull();
p.make_clockwise();
p.append(p.first_point());
pn.Contour = Slic3rMultiPoint_to_ClipperPath( p );
// Efficient conversion to item.
Item item(std::move(pn));
// Invalid geometries would throw exceptions when arranging
if(item.vertexCount() > 3) {
item.rotation(objinst->rotation);
item.translation( {
ClipperLib::cInt(objinst->offset.x/SCALING_FACTOR),
ClipperLib::cInt(objinst->offset.y/SCALING_FACTOR)
});
ret.emplace_back(objinst, item);
}
}
}
}
}
return ret;
}
/**
* \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 dist, const Slic3r::BoundingBoxf* bb,
bool first_bin_only,
std::function<void(unsigned)> progressind)
{
using ArrangeResult = _IndexedPackGroup<PolygonImpl>;
bool ret = true;
// Create the arranger config
auto min_obj_distance = static_cast<Coord>(dist/SCALING_FACTOR);
// Get the 2D projected shapes with their 3D model instance pointers
auto shapemap = arr::projectModelFromTop(model);
bool hasbin = bb != nullptr && bb->defined;
double area_max = 0;
// 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, min_obj_distance, &area_max, hasbin]
(ShapeData2D::value_type& it)
{
shapes.push_back(std::ref(it.second));
});
Box bin;
if(hasbin) {
// Scale up the bounding box to clipper scale.
BoundingBoxf bbb = *bb;
bbb.scale(1.0/SCALING_FACTOR);
bin = 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)
});
}
// Will use the DJD selection heuristic with the BottomLeft placement
// strategy
using Arranger = Arranger<NfpPlacer, FirstFitSelection>;
using PConf = Arranger::PlacementConfig;
using SConf = Arranger::SelectionConfig;
PConf pcfg; // Placement configuration
SConf scfg; // Selection configuration
// 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
pcfg.accuracy = 0.8;
// Magic: we will specify what is the goal of arrangement... In this case
// we override the default object function to make the larger items go into
// the center of the pile and smaller items orbit it so the resulting pile
// has a circle-like shape. This is good for the print bed's heat profile.
// We alse sacrafice a bit of pack efficiency for this to work. As a side
// effect, the arrange procedure is a lot faster (we do not need to
// calculate the convex hulls)
pcfg.object_function = [bin, hasbin](
NfpPlacer::Pile& pile, // The currently arranged pile
const Item &item,
double /*area*/, // Sum area of items (not needed)
double norm, // A norming factor for physical dimensions
double penality) // Min penality in case of bad arrangement
{
using pl = PointLike;
static const double BIG_ITEM_TRESHOLD = 0.2;
static const double GRAVITY_RATIO = 0.5;
static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
// We will treat big items (compared to the print bed) differently
NfpPlacer::Pile bigs;
bigs.reserve(pile.size());
for(auto& p : pile) {
auto pbb = ShapeLike::boundingBox(p);
auto na = std::sqrt(pbb.width()*pbb.height())/norm;
if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
}
// Candidate item bounding box
auto ibb = item.boundingBox();
// 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();
// The bounding box of the big items (they will accumulate in the center
// of the pile
auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
// The size indicator of the candidate item. This is not the area,
// but almost...
auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
// Will hold the resulting score
double score = 0;
if(itemnormarea > BIG_ITEM_TRESHOLD) {
// 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 unwanted strange arrangements.
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)};
auto cc = fullbb.center(); // The gravity center
// Now the distnce of the gravity center will be calculated to the
// five anchor points and the smallest will be chosen.
std::array<double, 5> dists;
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);
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;
// The score is a weighted sum of the distance from pile center
// and the pile size
score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
} else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
// If there are no big items, only small, we should consider the
// density here as well to not get silly results
auto bindist = pl::distance(ibb.center(), bin.center()) / norm;
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
} 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;
}
// 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(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
return score;
};
// Create the arranger object
Arranger arranger(bin, min_obj_distance, pcfg, scfg);
// Set the progress indicator for the arranger.
arranger.progressIndicator(progressind);
// Arrange and return the items with their respective indices within the
// input sequence.
auto result = arranger.arrangeIndexed(shapes.begin(), shapes.end());
auto applyResult = [&shapemap](ArrangeResult::value_type& group,
Coord batch_offset)
{
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;
}
};
if(first_bin_only) {
applyResult(result.front(), 0);
} else {
const auto STRIDE_PADDING = 1.2;
Coord stride = static_cast<Coord>(STRIDE_PADDING*
bin.width()*SCALING_FACTOR);
Coord batch_offset = 0;
for(auto& group : result) {
applyResult(group, batch_offset);
// 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;
}
}
/* arrange objects preserving their instance count
but altering their instance positions */
bool Model::arrange_objects(coordf_t dist, const BoundingBoxf* bb,
std::function<void(unsigned)> progressind)
bool Model::arrange_objects(coordf_t dist, const BoundingBoxf* bb)
{
bool ret = false;
if(bb != nullptr && bb->defined) {
// Despite the new arrange is able to run without a specified bin,
// the perl testsuit still fails for this case. For now the safest
// thing to do is to use the new arrange only when a proper bin is
// specified.
ret = arr::arrange(*this, dist, bb, false, progressind);
} else {
// get the (transformed) size of each instance so that we take
// into account their different transformations when packing
Pointfs instance_sizes;
Pointfs instance_centers;
for (const ModelObject *o : this->objects)
for (size_t i = 0; i < o->instances.size(); ++ i) {
// an accurate snug bounding box around the transformed mesh.
BoundingBoxf3 bbox(o->instance_bounding_box(i, true));
instance_sizes.push_back(bbox.size());
instance_centers.push_back(bbox.center());
}
Pointfs positions;
if (! _arrange(instance_sizes, dist, bb, positions))
return false;
size_t idx = 0;
for (ModelObject *o : this->objects) {
for (ModelInstance *i : o->instances) {
i->offset = positions[idx] - instance_centers[idx];
++ idx;
}
o->invalidate_bounding_box();
// get the (transformed) size of each instance so that we take
// into account their different transformations when packing
Pointfs instance_sizes;
Pointfs instance_centers;
for (const ModelObject *o : this->objects)
for (size_t i = 0; i < o->instances.size(); ++ i) {
// an accurate snug bounding box around the transformed mesh.
BoundingBoxf3 bbox(o->instance_bounding_box(i, true));
instance_sizes.push_back(bbox.size());
instance_centers.push_back(bbox.center());
}
Pointfs positions;
if (! _arrange(instance_sizes, dist, bb, positions))
return false;
size_t idx = 0;
for (ModelObject *o : this->objects) {
for (ModelInstance *i : o->instances) {
i->offset = positions[idx] - instance_centers[idx];
++ idx;
}
o->invalidate_bounding_box();
}
return ret;
return true;
}
// Duplicate the entire model preserving instance relative positions.

3
xs/src/libslic3r/Model.hpp
View file

@ -290,8 +290,7 @@ public:
void center_instances_around_point(const Pointf &point);
void translate(coordf_t x, coordf_t y, coordf_t z) { for (ModelObject *o : this->objects) o->translate(x, y, z); }
TriangleMesh mesh() const;
bool arrange_objects(coordf_t dist, const BoundingBoxf* bb = NULL,
std::function<void(unsigned)> progressind = [](unsigned){});
bool arrange_objects(coordf_t dist, const BoundingBoxf* bb = NULL);
// Croaks if the duplicated objects do not fit the print bed.
void duplicate(size_t copies_num, coordf_t dist, const BoundingBoxf* bb = NULL);
void duplicate_objects(size_t copies_num, coordf_t dist, const BoundingBoxf* bb = NULL);

405
xs/src/libslic3r/ModelArrange.hpp Normal file
View file

@ -0,0 +1,405 @@
#ifndef MODELARRANGE_HPP
#define MODELARRANGE_HPP
#include "Model.hpp"
#include "SVG.hpp"
#include <libnest2d.h>
#include <numeric>
#include <ClipperUtils.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;
tmpmesh.scale(objinst->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.x << ", "
<< v.y << "},\n";
{
auto v = expoly.contour.points.front();
ss << "\t\t\t{" << v.x << ", " << v.y << "},\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.x << ", "
<< v.y << "},\n";
{
auto v = h.points.front();
ss << "\t\t\t\t{" << v.x << ", " << v.y << "},\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->scaling_factor);
objinst->transform_mesh(&tmpmesh);
ExPolygons expolys = tmpmesh.horizontal_projection();
svg.draw(expolys);
}
}
}
// 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(), 0,
[](size_t s, ModelObject* o){
return s + o->instances.size();
});
ret.reserve(s);
for(auto objptr : model.objects) {
if(objptr) {
auto rmesh = objptr->raw_mesh();
for(auto objinst : objptr->instances) {
if(objinst) {
Slic3r::TriangleMesh tmpmesh = rmesh;
ClipperLib::PolygonImpl pn;
tmpmesh.scale(objinst->scaling_factor);
// TODO export the exact 2D projection
auto p = tmpmesh.convex_hull();
p.make_clockwise();
p.append(p.first_point());
pn.Contour = Slic3rMultiPoint_to_ClipperPath( p );
// Efficient conversion to item.
Item item(std::move(pn));
// Invalid geometries would throw exceptions when arranging
if(item.vertexCount() > 3) {
item.rotation(objinst->rotation);
item.translation( {
ClipperLib::cInt(objinst->offset.x/SCALING_FACTOR),
ClipperLib::cInt(objinst->offset.y/SCALING_FACTOR)
});
ret.emplace_back(objinst, item);
}
}
}
}
}
return ret;
}
/**
* \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 dist, const Slic3r::BoundingBoxf* bb,
bool first_bin_only,
std::function<void(unsigned)> progressind)
{
using ArrangeResult = _IndexedPackGroup<PolygonImpl>;
bool ret = true;
// Create the arranger config
auto min_obj_distance = static_cast<Coord>(dist/SCALING_FACTOR);
// Get the 2D projected shapes with their 3D model instance pointers
auto shapemap = arr::projectModelFromTop(model);
bool hasbin = bb != nullptr && bb->defined;
double area_max = 0;
// 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, min_obj_distance, &area_max, hasbin]
(ShapeData2D::value_type& it)
{
shapes.push_back(std::ref(it.second));
});
Box bin;
if(hasbin) {
// Scale up the bounding box to clipper scale.
BoundingBoxf bbb = *bb;
bbb.scale(1.0/SCALING_FACTOR);
bin = 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)
});
}
// Will use the DJD selection heuristic with the BottomLeft placement
// strategy
using Arranger = Arranger<NfpPlacer, FirstFitSelection>;
using PConf = Arranger::PlacementConfig;
using SConf = Arranger::SelectionConfig;
PConf pcfg; // Placement configuration
SConf scfg; // Selection configuration
// 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
pcfg.accuracy = 0.4f;
// Magic: we will specify what is the goal of arrangement... In this case
// we override the default object function to make the larger items go into
// the center of the pile and smaller items orbit it so the resulting pile
// has a circle-like shape. This is good for the print bed's heat profile.
// We alse sacrafice a bit of pack efficiency for this to work. As a side
// effect, the arrange procedure is a lot faster (we do not need to
// calculate the convex hulls)
pcfg.object_function = [bin, hasbin](
NfpPlacer::Pile& pile, // The currently arranged pile
const Item &item,
double /*area*/, // Sum area of items (not needed)
double norm, // A norming factor for physical dimensions
double penality) // Min penality in case of bad arrangement
{
using pl = PointLike;
static const double BIG_ITEM_TRESHOLD = 0.2;
static const double GRAVITY_RATIO = 0.5;
static const double DENSITY_RATIO = 1.0 - GRAVITY_RATIO;
// We will treat big items (compared to the print bed) differently
NfpPlacer::Pile bigs;
bigs.reserve(pile.size());
for(auto& p : pile) {
auto pbb = ShapeLike::boundingBox(p);
auto na = std::sqrt(pbb.width()*pbb.height())/norm;
if(na > BIG_ITEM_TRESHOLD) bigs.emplace_back(p);
}
// Candidate item bounding box
auto ibb = item.boundingBox();
// 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();
// The bounding box of the big items (they will accumulate in the center
// of the pile
auto bigbb = bigs.empty()? fullbb : ShapeLike::boundingBox(bigs);
// The size indicator of the candidate item. This is not the area,
// but almost...
auto itemnormarea = std::sqrt(ibb.width()*ibb.height())/norm;
// Will hold the resulting score
double score = 0;
if(itemnormarea > BIG_ITEM_TRESHOLD) {
// 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 unwanted strange arrangements.
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)};
auto cc = fullbb.center(); // The gravity center
// Now the distnce of the gravity center will be calculated to the
// five anchor points and the smallest will be chosen.
std::array<double, 5> dists;
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);
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;
// The score is a weighted sum of the distance from pile center
// and the pile size
score = GRAVITY_RATIO * dist + DENSITY_RATIO * density;
} else if(itemnormarea < BIG_ITEM_TRESHOLD && bigs.empty()) {
// If there are no big items, only small, we should consider the
// density here as well to not get silly results
auto bindist = pl::distance(ibb.center(), bin.center()) / norm;
auto density = std::sqrt(fullbb.width()*fullbb.height()) / norm;
score = GRAVITY_RATIO * bindist + DENSITY_RATIO * density;
} 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;
}
// 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(!NfpPlacer::wouldFit(fullbb, bin)) score = 2*penality - score;
return score;
};
// Create the arranger object
Arranger arranger(bin, min_obj_distance, pcfg, scfg);
// Set the progress indicator for the arranger.
arranger.progressIndicator(progressind);
// Arrange and return the items with their respective indices within the
// input sequence.
auto result = arranger.arrangeIndexed(shapes.begin(), shapes.end());
auto applyResult = [&shapemap](ArrangeResult::value_type& group,
Coord batch_offset)
{
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;
}
};
if(first_bin_only) {
applyResult(result.front(), 0);
} else {
const auto STRIDE_PADDING = 1.2;
Coord stride = static_cast<Coord>(STRIDE_PADDING*
bin.width()*SCALING_FACTOR);
Coord batch_offset = 0;
for(auto& group : result) {
applyResult(group, batch_offset);
// 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

2
xs/src/libslic3r/libslic3r.h
View file

@ -14,7 +14,7 @@
#include <boost/thread.hpp>
#define SLIC3R_FORK_NAME "Slic3r Prusa Edition"
#define SLIC3R_VERSION "1.41.0-alpha2"
#define SLIC3R_VERSION "1.41.0-alpha3"
#define SLIC3R_BUILD "UNKNOWN"
typedef int32_t coord_t;

4
xs/src/slic3r/AppController.cpp
View file

@ -8,6 +8,7 @@
#include <unordered_map>
#include <slic3r/GUI/GUI.hpp>
#include <ModelArrange.hpp>
#include <slic3r/GUI/PresetBundle.hpp>
#include <Geometry.hpp>
@ -310,12 +311,13 @@ void AppController::arrange_model()
auto dist = print_ctl()->config().min_object_distance();
BoundingBoxf bb(print_ctl()->config().bed_shape.values);
if(pind) pind->update(0, _(L("Arranging objects...")));
try {
model_->arrange_objects(dist, &bb, [pind, count](unsigned rem){
arr::arrange(*model_, dist, &bb, false, [pind, count](unsigned rem){
if(pind) pind->update(count - rem, _(L("Arranging objects...")));
});
} catch(std::exception& e) {

31
xs/src/slic3r/GUI/GLCanvas3D.cpp
View file

@ -2697,9 +2697,9 @@ void GLCanvas3D::on_mouse(wxMouseEvent& evt)
}
else if (evt.Leaving())
{
// to remove hover when mouse goes out of this canvas
m_mouse.position = Pointf((coordf_t)pos.x, (coordf_t)pos.y);
render();
// to remove hover on objects when the mouse goes out of this canvas
m_mouse.position = Pointf(-1.0, -1.0);
m_dirty = true;
}
else if (evt.LeftDClick() && (m_hover_volume_id != -1))
m_on_double_click_callback.call();
@ -3403,20 +3403,22 @@ void GLCanvas3D::_picking_pass() const
if (m_multisample_allowed)
::glEnable(GL_MULTISAMPLE);
const Size& cnv_size = get_canvas_size();
GLubyte color[4];
::glReadPixels(pos.x, cnv_size.get_height() - pos.y - 1, 1, 1, GL_RGBA, GL_UNSIGNED_BYTE, (void*)color);
int volume_id = color[0] + color[1] * 256 + color[2] * 256 * 256;
m_hover_volume_id = -1;
int volume_id = -1;
for (GLVolume* vol : m_volumes.volumes)
{
vol->hover = false;
}
if (volume_id < (int)m_volumes.volumes.size())
GLubyte color[4] = { 0, 0, 0, 0 };
const Size& cnv_size = get_canvas_size();
bool inside = (0 <= pos.x) && (pos.x < cnv_size.get_width()) && (0 <= pos.y) && (pos.y < cnv_size.get_height());
if (inside)
{
::glReadPixels(pos.x, cnv_size.get_height() - pos.y - 1, 1, 1, GL_RGBA, GL_UNSIGNED_BYTE, (void*)color);
volume_id = color[0] + color[1] * 256 + color[2] * 256 * 256;
}
if ((0 <= volume_id) && (volume_id < (int)m_volumes.volumes.size()))
{
m_hover_volume_id = volume_id;
m_volumes.volumes[volume_id]->hover = true;
@ -3432,7 +3434,10 @@ void GLCanvas3D::_picking_pass() const
m_gizmos.set_hover_id(-1);
}
else
m_gizmos.set_hover_id(254 - (int)color[2]);
{
m_hover_volume_id = -1;
m_gizmos.set_hover_id(inside ? (254 - (int)color[2]) : -1);
}
// updates gizmos overlay
if (_get_first_selected_object_id() != -1)