mirror of
https://github.com/CloudCompare/PoissonRecon.git
synced 2026-08-29 16:40:28 +08:00
Daniel Girardeau-Montaut
156 lines
6.1 KiB
C++
156 lines
6.1 KiB
C++
//##########################################################################
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//# #
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//# CLOUDCOMPARE WRAPPER: PoissonReconLib #
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//# #
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//# This program is free software; you can redistribute it and/or modify #
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//# it under the terms of the GNU General Public License as published by #
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//# the Free Software Foundation; version 2 or later of the License. #
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//# #
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//# This program is distributed in the hope that it will be useful, #
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//# but WITHOUT ANY WARRANTY; without even the implied warranty of #
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//# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
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//# GNU General Public License for more details. #
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//# #
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//# COPYRIGHT: Daniel Girardeau-Montaut #
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//# #
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//##########################################################################
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#ifndef CC_POISSON_RECON_LIB_WRAPPER
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#define CC_POISSON_RECON_LIB_WRAPPER
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#include <cstddef>
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//! Wrapper to use PoissonRecon (Kazhdan et. al) as a library
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class PoissonReconLib
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{
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public:
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//! Algorithm parameters
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struct Parameters
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{
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//! Default initializer
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Parameters();
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//! Returns the maximum number of threads
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static int GetMaxThreadCount();
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//! Boundary types
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enum BoundaryType { FREE, DIRICHLET, NEUMANN };
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//! Boundary type for the finite elements
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BoundaryType boundary = NEUMANN;
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//! The maximum depth of the tree that will be used for surface reconstruction
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/** Running at depth d corresponds to solving on a 2^d x 2^d x 2^d.
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Note that since the reconstructor adapts the octree to the sampling density,
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the specified reconstruction depth is only an upper bound.
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**/
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int depth = 8;
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//! The target width of the finest level octree cells (ignored if depth is specified)
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float finestCellWidth = 0.0f;
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//! The ratio between the diameter of the cube used for reconstruction and the diameter of the samples' bounding cube.
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/** Specifies the factor of the bounding cube that the input samples should fit into.
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**/
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float scale = 1.1f;
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//! The minimum number of sample points that should fall within an octree node as the octree construction is adapted to sampling density.
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/** This parameter specifies the minimum number of points that should fall within an octree node.
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For noise-free samples, small values in the range [1.0 - 5.0] can be used. For more noisy samples, larger values
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in the range [15.0 - 20.0] may be needed to provide a smoother, noise-reduced, reconstruction.
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**/
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float samplesPerNode = 1.5f;
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//! The importance that interpolation of the point samples is given in the formulation of the screened Poisson equation.
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/** The results of the original (unscreened) Poisson Reconstruction can be obtained by setting this value to 0.
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**/
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float pointWeight = 2.0f;
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//! The number of solver iterations
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/** Number of Gauss-Seidel relaxations to be performed at each level of the octree hierarchy.
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**/
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int iters = 8;
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//! If this flag is enabled, the sampling density is written out with the vertices
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bool density = false;
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//! This flag tells the reconstructor to read in color values with the input points and extrapolate those to the vertices of the output.
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bool withColors = true;
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//! Data pull factor
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/** If withColors is rue, this floating point value specifies the relative importance of finer color estimates over lower ones.
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**/
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float colorPullFactor = 32.0f;
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//! Normal confidence exponent
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/** Exponent to be applied to a point's confidence to adjust its weight. (A point's confidence is defined by the magnitude of its normal.)
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**/
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float normalConfidence = 0.0;
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//! Normal confidence bias exponent
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/** Exponent to be applied to a point's confidence to bias the resolution at which the sample contributes to the linear system. (Points with lower confidence are biased to contribute at coarser resolutions.)
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**/
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float normalConfidenceBias = 0.0;
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//! Enabling this flag has the reconstructor use linear interpolation to estimate the positions of iso-vertices.
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bool linearFit = false;
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//! This parameter specifies the number of threads across which the solver should be parallelized
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int threads = 1;
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/** The parameters below are accessible via the command line but are not described in the official documentation **/
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//! The depth beyond which the octree will be adapted.
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/** At coarser depths, the octree will be complete, containing all 2^d x 2^d x 2^d nodes.
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**/
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int fullDepth = 5;
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//! Coarse MG solver depth
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int baseDepth = 0;
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//! Coarse MG solver v-cycles
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int baseVCycles = 1;
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//! This flag specifies the accuracy cut-off to be used for CG
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float cgAccuracy = 1.0e-3f;
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};
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//! Input cloud interface
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template <typename Real> class ICloud
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{
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public:
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virtual size_t size() const = 0;
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virtual bool hasNormals() const = 0;
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virtual bool hasColors() const = 0;
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virtual void getPoint(size_t index, Real* coords) const = 0;
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virtual void getNormal(size_t index, Real* coords) const = 0;
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virtual void getColor(size_t index, Real* rgb) const = 0;
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};
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//! Output mesh interface
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template <typename Real> class IMesh
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{
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public:
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virtual void addVertex(const Real* coords) = 0;
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virtual void addNormal(const Real* coords) = 0;
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virtual void addColor(const Real* rgb) = 0;
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virtual void addDensity(double d) = 0;
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virtual void addTriangle(size_t i1, size_t i2, size_t i3) = 0;
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};
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//! Reconstruct a mesh from a point cloud (float version)
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static bool Reconstruct(const Parameters& params,
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const PoissonReconLib::ICloud<float>& inCloud,
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PoissonReconLib::IMesh<float>& ouMesh);
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//! Reconstruct a mesh from a point cloud (double version)
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static bool Reconstruct(const Parameters& params,
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const PoissonReconLib::ICloud<double>& inCloud,
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PoissonReconLib::IMesh<double>& ouMesh);
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};
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#endif // CC_POISSON_RECON_LIB_12_0_WRAPPER
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