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Ponca : API change relating WeightFunc #19

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Ponca : API change relating WeightFunc #19

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7 changes: 3 additions & 4 deletions src/dataManager.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -77,17 +77,16 @@ DataManager::loadPointCloud(const std::string& path){

void
DataManager::computeNormals(int k){
using WeightFunc = Ponca::DistWeightFunc<DataPoint,Ponca::ConstantWeightKernel<typename DataPoint::Scalar> >;
using PlaneFit = Ponca::Basket<DataPoint ,WeightFunc, Ponca::CovariancePlaneFit>;
using NeighborFilter = Ponca::DistWeightFunc<DataPoint,Ponca::ConstantWeightKernel<typename DataPoint::Scalar> >;
using PlaneFit = Ponca::Basket<DataPoint, NeighborFilter, Ponca::CovariancePlaneFit>;

std::cout << "Recompute normals" << std::endl;

for (auto& pp : m_points){
VectorType p {pp.x(),pp.y()};
PlaneFit fit;
fit.setWeightFunc(WeightFunc());
// Set the evaluation position
fit.init(p);
fit.setNeighborFilter(NeighborFilter(p));
// Fit plane (method compute handles multipass fitting
if (fit.computeWithIds(m_tree.k_nearest_neighbors(p, k), m_tree.points()) == Ponca::STABLE) {
pp.z() = std::acos(fit.primitiveGradient().normalized().x());
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14 changes: 6 additions & 8 deletions src/drawingPasses/bestFieldFit.h
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Expand Up @@ -10,7 +10,7 @@ struct SingleFitField : public _Base {

using Base = _Base;
using FitType = _FitType;
using WeightFunc = typename FitType::WeightFunction;
using NeighborFilter = typename FitType::NeighborFilter;

virtual float configureAndFit(const KdTree& points, FitType& fit, RenderingContext ctx) = 0;

Expand Down Expand Up @@ -71,16 +71,15 @@ struct BestFitField : public SingleFitField<_FitType, DrawingPass> {
~BestFitField() override = default;

using FitType = _FitType;
using WeightFunc = typename FitType::WeightFunction;
using NeighborFilter = typename FitType::NeighborFilter;

/// Method called at the end of the fitting process, only for stable fits
virtual void postProcess(FitType& /*fit*/){};

inline float configureAndFit(const KdTree& points, FitType& fit, RenderingContext ctx) override {
// Configure computation to be centered on the point cloud coordinates
float scale = points.nodes()[0].getAabb()->diagonal().norm();
fit.setWeightFunc(WeightFunc(scale));
fit.init(points.nodes()[0].getAabb()->center());
fit.setNeighborFilter(NeighborFilter(points.nodes()[0].getAabb()->center(), scale));
// Compute fit
fit.compute(points.points());
postProcess(fit);
Expand All @@ -106,19 +105,18 @@ struct OnePointFitField : public SingleFitField<_FitType, BaseFitField>, public
~OnePointFitField() override = default;

using FitType = _FitType;
using WeightFunc = typename FitType::WeightFunction;
using NeighborFilter = typename FitType::NeighborFilter;
using Scalar = typename FitType::Scalar;

/// Method called at the end of the fitting process, only for stable fits
virtual void postProcess(FitType& /*fit*/){};

inline float configureAndFit(const KdTree& points, FitType& fit, RenderingContext ctx) override {
// Configure computation to be centered on the point cloud coordinates
fit.setWeightFunc(WeightFunc(BaseFitField::params.m_scale));
auto query = points.points()[pointId].pos();
// Compute fit
for (int iter = 0; iter != BaseFitField::params.m_iter; ++iter) {
fit.init(query);
// Configure computation to be centered on the point cloud coordinates
fit.setNeighborFilter(NeighborFilter(query, BaseFitField::params.m_scale));
if (fit.computeWithIds(points.range_neighbors(query, BaseFitField::params.m_scale), points.points()) ==
Ponca::STABLE) {
postProcess(fit);
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15 changes: 6 additions & 9 deletions src/drawingPasses/poncaFitField.h
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Expand Up @@ -10,7 +10,7 @@ struct FitField : public BaseFitField {
~FitField() override = default;

using FitType = _FitType;
using WeightFunc = typename FitType::WeightFunction;
using NeighborFilter = typename FitType::NeighborFilter;

/// Method called at the end of the fitting process, only for stable fits
virtual void postProcess(FitType& /*fit*/){};
Expand All @@ -36,11 +36,10 @@ struct FitField : public BaseFitField {
DataPoint::VectorType query (coord.first, coord.second);

FitType fit;
// Set a weighting function instance
fit.setWeightFunc(WeightFunc(params.m_scale));
// Set the evaluation position
for (int iter = 0; iter != params.m_iter; ++iter) {
fit.init(query);
// Set a weighting function instance
fit.setNeighborFilter(NeighborFilter(query, params.m_scale));
// Fit plane (method compute handles multipass fitting
if (fit.computeWithIds(points.range_neighbors(query, params.m_scale), points.points()) ==
Ponca::STABLE) {
Expand Down Expand Up @@ -81,23 +80,21 @@ struct FitField : public BaseFitField {
float potential {0.f};
do {
FitType fit;
// Set a weighting function instance
fit.setWeightFunc(WeightFunc(params.m_scale));

// Set the evaluation position
for (int iter = 0; iter != params.m_iter; ++iter) {
x = nextx;

// project to next location and draw
fit.init(x);
// Set a weighting function instance
fit.setNeighborFilter(NeighborFilter(x, params.m_scale));
if (fit.computeWithIds(points.range_neighbors(x, params.m_scale), points.points()) ==
Ponca::STABLE) {
postProcess(fit);
nextx = fit.project(x);
potential = fit.potential(nextx);

// ask to stop the projection procedure if motion is below one pixel
int nbPix = bresenham(ctx.pointToPix( x ) , ctx.pointToPix( nextx ),
int nbPix = bresenham(ctx.pointToPix( x ), ctx.pointToPix( nextx ),
{ctx.w, ctx.h},
[buffer, ctx](int x, int y){
auto *b = buffer + (x + y * ctx.w) * 4;
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18 changes: 9 additions & 9 deletions src/poncaTypes.h
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Original file line number Diff line number Diff line change
Expand Up @@ -20,16 +20,16 @@ class DataPoint
VectorType m_pos, m_normal;
};

using WeightFunc = Ponca::DistWeightFunc<DataPoint,Ponca::SmoothWeightKernel<typename DataPoint::Scalar> >;
using ConstWeightFunc = Ponca::DistWeightFunc<DataPoint,Ponca::ConstantWeightKernel<typename DataPoint::Scalar> >;
using WeightFunc = Ponca::DistWeightFunc<DataPoint,Ponca::SmoothWeightKernel<DataPoint::Scalar> >;
using ConstWeightFunc = Ponca::DistWeightFunc<DataPoint,Ponca::ConstantWeightKernel<DataPoint::Scalar> >;

using PlaneFit = Ponca::Basket<DataPoint ,WeightFunc, Ponca::CovariancePlaneFit>;
using ConstPlaneFit = Ponca::Basket<DataPoint ,ConstWeightFunc, Ponca::CovariancePlaneFit>;
using SphereFit = Ponca::Basket<DataPoint ,WeightFunc, Ponca::SphereFit>;
using ConstSphereFit = Ponca::Basket<DataPoint ,ConstWeightFunc, Ponca::SphereFit>;
using OrientedSphereFit= Ponca::Basket<DataPoint ,WeightFunc, Ponca::OrientedSphereFit>;
using ConstOrientedSphereFit= Ponca::Basket<DataPoint ,ConstWeightFunc, Ponca::OrientedSphereFit>;
using UnorientedSphereFit = Ponca::Basket<DataPoint ,WeightFunc, Ponca::UnorientedSphereFit>;
using PlaneFit = Ponca::Basket<DataPoint, WeightFunc, Ponca::CovariancePlaneFit>;
using ConstPlaneFit = Ponca::Basket<DataPoint, ConstWeightFunc, Ponca::CovariancePlaneFit>;
using SphereFit = Ponca::Basket<DataPoint, WeightFunc, Ponca::SphereFit>;
using ConstSphereFit = Ponca::Basket<DataPoint, ConstWeightFunc, Ponca::SphereFit>;
using OrientedSphereFit= Ponca::Basket<DataPoint, WeightFunc, Ponca::OrientedSphereFit>;
using ConstOrientedSphereFit= Ponca::Basket<DataPoint, ConstWeightFunc, Ponca::OrientedSphereFit>;
using UnorientedSphereFit = Ponca::Basket<DataPoint, WeightFunc, Ponca::UnorientedSphereFit>;



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