Restructured a bit the stratified sampling approaches
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@ -536,47 +536,94 @@ static int SingleFaceSimilar(FacePointer fp, VertexSampler &ps, int n_samples_pe
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}
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return n_samples;
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}
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static int SingleFaceSimilarDual(FacePointer fp, VertexSampler &ps, int n_samples_per_edge, bool randomFlag)
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{
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int n_samples=0;
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float i, j;
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float segmentNum=n_samples_per_edge -1 ;
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float segmentLen = 1.0/segmentNum;
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// face sampling.
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for(i=0; i < n_samples_per_edge-1; i++)
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for(j=0; j < n_samples_per_edge-1-i; j++)
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{
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//AddSample( v0 + (V1*(double)i + V2*(double)j) );
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CoordType V0((i+0)*segmentLen,(j+0)*segmentLen, 1.0 - ((i+0)*segmentLen+(j+0)*segmentLen) ) ;
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CoordType V1((i+1)*segmentLen,(j+0)*segmentLen, 1.0 - ((i+1)*segmentLen+(j+0)*segmentLen) ) ;
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CoordType V2((i+0)*segmentLen,(j+1)*segmentLen, 1.0 - ((i+0)*segmentLen+(j+1)*segmentLen) ) ;
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n_samples++;
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if(randomFlag) {
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CoordType rb=RandomBaricentric();
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ps.AddFace(*fp, V0*rb[0]+V1*rb[1]+V2*rb[2]);
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} else ps.AddFace(*fp,(V0+V1+V2)/3.0);
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/// Similar sampling. Each triangle is subdivided into similar triangles following a generalization of the classical 1-to-4 splitting rule of triangles.
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/// According to the level of subdivision <k> you get 1, 4 , 9, 16 , <k^2> triangles.
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/// Of these triangles we consider only internal vertices. (to avoid multiple sampling of edges and vertices).
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/// Therefore the number of internal points is ((k-3)*(k-2))/2. where k is the number of point on an edge (vertex included)
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// e.g. for a k=4 you get (1*2)/2 == 1 e.g. a single point, etc.
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/// So if you want N samples in a triangle i have to solve k^2 -5k +6 - 2N = 0
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if( j < n_samples_per_edge-i-2 )
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{
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CoordType V3((i+1)*segmentLen,(j+1)*segmentLen, 1.0 - ((i+1)*segmentLen+(j+1)*segmentLen) ) ;
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n_samples++;
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if(randomFlag) {
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CoordType rb=RandomBaricentric();
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ps.AddFace(*fp, V3*rb[0]+V1*rb[1]+V2*rb[2]);
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} else ps.AddFace(*fp,(V3+V1+V2)/3.0);
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}
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}
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return n_samples;
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}
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// Similar sampling
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// Each triangle is subdivided into similar triangles following a generalization of the classical 1-to-4 splitting rule of triangles.
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// According to the level of subdivision <k> you get 1, 4 , 9, 16 , <k^2> triangles.
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// Depending on the kind of the sampling strategies we can have two different approach to choosing the sample points.
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// 1) you have already sampled both edges and vertices
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// 2) you are not going to take samples on edges and vertices.
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//
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// In the first case you have to consider only internal vertices of the subdivided triangles (to avoid multiple sampling of edges and vertices).
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// Therefore the number of internal points is ((k-3)*(k-2))/2. where k is the number of points on an edge (vertex included)
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// E.g. for k=4 you get 3 segments on each edges and the original triangle is subdivided
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// into 9 smaller triangles and you get (1*2)/2 == 1 only a single internal point.
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// So if you want N samples in a triangle you have to solve k^2 -5k +6 - 2N = 0
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// from which you get:
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//
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// 5 + sqrt( 1 + 8N )
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// k = -------------------
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// 2
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//
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// In the second case if you are not interested to skip the sampling on edges and vertices you have to consider as sample number the number of triangles.
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// So if you want N samples in a triangle, the number <k> of points on an edge (vertex included) should be simply:
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// k = 1 + sqrt(N)
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// examples:
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// N = 4 -> k = 3
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// N = 9 -> k = 4
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//template <class MetroMesh>
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//void Sampling<MetroMesh>::SimilarFaceSampling()
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static void FaceSimilar(MetroMesh & m, VertexSampler &ps,int sampleNum)
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{
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static void FaceSimilar(MetroMesh & m, VertexSampler &ps,int sampleNum, bool dualFlag, bool randomFlag)
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{
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ScalarType area = Stat<MetroMesh>::ComputeMeshArea(m);
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ScalarType samplePerAreaUnit = sampleNum/area;
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//qDebug("samplePerAreaUnit %f",samplePerAreaUnit);
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// Similar Triangles sampling.
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int n_samples_per_edge;
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double n_samples_decimal = 0.0;
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FaceIterator fi;
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printf("Similar Triangles face sampling\n");
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for(fi=m.face.begin(); fi != m.face.end(); fi++)
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{
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// compute # samples in the current face.
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n_samples_decimal += 0.5*DoubleArea(*fi) * samplePerAreaUnit;
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int n_samples = (int) n_samples_decimal;
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if(n_samples)
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if(n_samples>0)
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{
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// face sampling.
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n_samples_per_edge = (int)((sqrt(1.0+8.0*(double)n_samples) +5.0)/2.0);
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//n_samples = 0;
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//SingleFaceSimilar((*fi).V(0)->cP(), (*fi).V(1)->cP(), (*fi).V(2)->cP(), n_samples_per_edge);
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n_samples = SingleFaceSimilar(&*fi,ps, n_samples_per_edge);
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if(dualFlag)
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{
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n_samples_per_edge = (int)((sqrt(1.0+8.0*(double)n_samples) +5.0)/2.0); // original for non dual case
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n_samples = SingleFaceSimilar(&*fi,ps, n_samples_per_edge);
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} else {
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n_samples_per_edge = (int)(sqrt(n_samples) +1.0);
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n_samples = SingleFaceSimilarDual(&*fi,ps, n_samples_per_edge,randomFlag);
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}
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}
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n_samples_decimal -= (double) n_samples;
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}
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@ -787,7 +834,7 @@ static void Poissondisk(MetroMesh &origMesh, VertexSampler &ps, MetroMesh &monte
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int sizeY = vcg::math::Max(1.0f,origMesh.bbox.DimY() / cellsize);
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int sizeZ = vcg::math::Max(1.0f,origMesh.bbox.DimZ() / cellsize);
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Point3i gridsize(sizeX, sizeY, sizeZ);
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#ifndef NO_QT
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#ifdef QT_VERSION
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qDebug("PDS: radius %f Grid:(%i %i %i) ",diskRadius,sizeX,sizeY,sizeZ);
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#endif
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// initialize spatial hash to index pre-generated samples
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@ -798,7 +845,7 @@ static void Poissondisk(MetroMesh &origMesh, VertexSampler &ps, MetroMesh &monte
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montecarloSHT.Add(&(*vi));
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verticescounter[0]++;
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}
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#ifndef NO_QT
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#ifdef QT_VERSION
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qDebug("PDS: Completed montercarloSHT, inserted %i vertex in %i cells", montecarloMesh.vn, montecarloSHT.AllocatedCells.size());
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#endif
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// initialize spatial hash table for check poisson-disk radius constrain
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@ -927,14 +974,14 @@ static void Poissondisk(MetroMesh &origMesh, VertexSampler &ps, MetroMesh &monte
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}
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nextPoints.clear();
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#ifndef NO_QT
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#ifdef QT_VERSION
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qDebug("PDS: Completed Level %i, added %i samples",level,samplesaccepted[level]);
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#endif
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level++;
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} while(level < pp.MAXLEVELS);
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#ifndef NO_QT
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#ifdef DEBUG_DUMP_STAT
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// write some statistics
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QFile outfile("C:/temp/poissondisk_statistics.txt");
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if (outfile.open(QFile::WriteOnly | QFile::Truncate))
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@ -987,3 +1034,4 @@ static void Texture(MetroMesh & m, VertexSampler &ps, int textureWidth, int text
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} // end namespace vcg
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#endif
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