godot/thirdparty/vhacd/src/VHACD.cpp
Juan Linietsky 5823b5d77d Bundled VHACD library for convex decomposition.
Modified both MeshInstance tools as well as importer to use it instead of QuickHull.
2019-04-10 17:47:28 -03:00

1590 lines
60 KiB
C++

/* Copyright (c) 2011 Khaled Mamou (kmamou at gmail dot com)
All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
3. The names of the contributors may not be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef _CRT_SECURE_NO_WARNINGS
#define _CRT_SECURE_NO_WARNINGS
#endif
#include <algorithm>
#include <fstream>
#include <iomanip>
#include <limits>
#include <sstream>
#if _OPENMP
#include <omp.h>
#endif // _OPENMP
#include "../public/VHACD.h"
#include "btConvexHullComputer.h"
#include "vhacdICHull.h"
#include "vhacdMesh.h"
#include "vhacdSArray.h"
#include "vhacdTimer.h"
#include "vhacdVHACD.h"
#include "vhacdVector.h"
#include "vhacdVolume.h"
#include "FloatMath.h"
#define MAX(a, b) (((a) > (b)) ? (a) : (b))
#define MIN(a, b) (((a) < (b)) ? (a) : (b))
#define ABS(a) (((a) < 0) ? -(a) : (a))
#define ZSGN(a) (((a) < 0) ? -1 : (a) > 0 ? 1 : 0)
#define MAX_DOUBLE (1.79769e+308)
#ifdef _MSC_VER
#pragma warning(disable:4267 4100 4244 4456)
#endif
#ifdef USE_SSE
#include <immintrin.h>
const int32_t SIMD_WIDTH = 4;
inline int32_t FindMinimumElement(const float* const d, float* const _, const int32_t n)
{
// Min within vectors
__m128 min_i = _mm_set1_ps(-1.0f);
__m128 min_v = _mm_set1_ps(std::numeric_limits<float>::max());
for (int32_t i = 0; i <= n - SIMD_WIDTH; i += SIMD_WIDTH) {
const __m128 data = _mm_load_ps(&d[i]);
const __m128 pred = _mm_cmplt_ps(data, min_v);
min_i = _mm_blendv_ps(min_i, _mm_set1_ps(i), pred);
min_v = _mm_min_ps(data, min_v);
}
/* Min within vector */
const __m128 min1 = _mm_shuffle_ps(min_v, min_v, _MM_SHUFFLE(1, 0, 3, 2));
const __m128 min2 = _mm_min_ps(min_v, min1);
const __m128 min3 = _mm_shuffle_ps(min2, min2, _MM_SHUFFLE(0, 1, 0, 1));
const __m128 min4 = _mm_min_ps(min2, min3);
float min_d = _mm_cvtss_f32(min4);
// Min index
const int32_t min_idx = __builtin_ctz(_mm_movemask_ps(_mm_cmpeq_ps(min_v, min4)));
int32_t ret = min_i[min_idx] + min_idx;
// Trailing elements
for (int32_t i = (n & ~(SIMD_WIDTH - 1)); i < n; ++i) {
if (d[i] < min_d) {
min_d = d[i];
ret = i;
}
}
*m = min_d;
return ret;
}
inline int32_t FindMinimumElement(const float* const d, float* const m, const int32_t begin, const int32_t end)
{
// Leading elements
int32_t min_i = -1;
float min_d = std::numeric_limits<float>::max();
const int32_t aligned = (begin & ~(SIMD_WIDTH - 1)) + ((begin & (SIMD_WIDTH - 1)) ? SIMD_WIDTH : 0);
for (int32_t i = begin; i < std::min(end, aligned); ++i) {
if (d[i] < min_d) {
min_d = d[i];
min_i = i;
}
}
// Middle and trailing elements
float r_m = std::numeric_limits<float>::max();
const int32_t n = end - aligned;
const int32_t r_i = (n > 0) ? FindMinimumElement(&d[aligned], &r_m, n) : 0;
// Pick the lowest
if (r_m < min_d) {
*m = r_m;
return r_i + aligned;
}
else {
*m = min_d;
return min_i;
}
}
#else
inline int32_t FindMinimumElement(const float* const d, float* const m, const int32_t begin, const int32_t end)
{
int32_t idx = -1;
float min = (std::numeric_limits<float>::max)();
for (size_t i = begin; i < size_t(end); ++i) {
if (d[i] < min) {
idx = i;
min = d[i];
}
}
*m = min;
return idx;
}
#endif
//#define OCL_SOURCE_FROM_FILE
#ifndef OCL_SOURCE_FROM_FILE
const char* oclProgramSource = "\
__kernel void ComputePartialVolumes(__global short4 * voxels, \
const int numVoxels, \
const float4 plane, \
const float4 minBB, \
const float4 scale, \
__local uint4 * localPartialVolumes, \
__global uint4 * partialVolumes) \
{ \
int localId = get_local_id(0); \
int groupSize = get_local_size(0); \
int i0 = get_global_id(0) << 2; \
float4 voxel; \
uint4 v; \
voxel = convert_float4(voxels[i0]); \
v.s0 = (dot(plane, mad(scale, voxel, minBB)) >= 0.0f) * (i0 < numVoxels);\
voxel = convert_float4(voxels[i0 + 1]); \
v.s1 = (dot(plane, mad(scale, voxel, minBB)) >= 0.0f) * (i0 + 1 < numVoxels);\
voxel = convert_float4(voxels[i0 + 2]); \
v.s2 = (dot(plane, mad(scale, voxel, minBB)) >= 0.0f) * (i0 + 2 < numVoxels);\
voxel = convert_float4(voxels[i0 + 3]); \
v.s3 = (dot(plane, mad(scale, voxel, minBB)) >= 0.0f) * (i0 + 3 < numVoxels);\
localPartialVolumes[localId] = v; \
barrier(CLK_LOCAL_MEM_FENCE); \
for (int i = groupSize >> 1; i > 0; i >>= 1) \
{ \
if (localId < i) \
{ \
localPartialVolumes[localId] += localPartialVolumes[localId + i]; \
} \
barrier(CLK_LOCAL_MEM_FENCE); \
} \
if (localId == 0) \
{ \
partialVolumes[get_group_id(0)] = localPartialVolumes[0]; \
} \
} \
__kernel void ComputePartialSums(__global uint4 * data, \
const int dataSize, \
__local uint4 * partialSums) \
{ \
int globalId = get_global_id(0); \
int localId = get_local_id(0); \
int groupSize = get_local_size(0); \
int i; \
if (globalId < dataSize) \
{ \
partialSums[localId] = data[globalId]; \
} \
else \
{ \
partialSums[localId] = (0, 0, 0, 0); \
} \
barrier(CLK_LOCAL_MEM_FENCE); \
for (i = groupSize >> 1; i > 0; i >>= 1) \
{ \
if (localId < i) \
{ \
partialSums[localId] += partialSums[localId + i]; \
} \
barrier(CLK_LOCAL_MEM_FENCE); \
} \
if (localId == 0) \
{ \
data[get_group_id(0)] = partialSums[0]; \
} \
}";
#endif //OCL_SOURCE_FROM_FILE
namespace VHACD {
IVHACD* CreateVHACD(void)
{
return new VHACD();
}
bool VHACD::OCLInit(void* const oclDevice, IUserLogger* const logger)
{
#ifdef CL_VERSION_1_1
m_oclDevice = (cl_device_id*)oclDevice;
cl_int error;
m_oclContext = clCreateContext(NULL, 1, m_oclDevice, NULL, NULL, &error);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't create context\n");
}
return false;
}
#ifdef OCL_SOURCE_FROM_FILE
std::string cl_files = OPENCL_CL_FILES;
// read kernal from file
#ifdef _WIN32
std::replace(cl_files.begin(), cl_files.end(), '/', '\\');
#endif // _WIN32
FILE* program_handle = fopen(cl_files.c_str(), "rb");
fseek(program_handle, 0, SEEK_END);
size_t program_size = ftell(program_handle);
rewind(program_handle);
char* program_buffer = new char[program_size + 1];
program_buffer[program_size] = '\0';
fread(program_buffer, sizeof(char), program_size, program_handle);
fclose(program_handle);
// create program
m_oclProgram = clCreateProgramWithSource(m_oclContext, 1, (const char**)&program_buffer, &program_size, &error);
delete[] program_buffer;
#else
size_t program_size = strlen(oclProgramSource);
m_oclProgram = clCreateProgramWithSource(m_oclContext, 1, (const char**)&oclProgramSource, &program_size, &error);
#endif
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't create program\n");
}
return false;
}
/* Build program */
error = clBuildProgram(m_oclProgram, 1, m_oclDevice, "-cl-denorms-are-zero", NULL, NULL);
if (error != CL_SUCCESS) {
size_t log_size;
/* Find Size of log and print to std output */
clGetProgramBuildInfo(m_oclProgram, *m_oclDevice, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);
char* program_log = new char[log_size + 2];
program_log[log_size] = '\n';
program_log[log_size + 1] = '\0';
clGetProgramBuildInfo(m_oclProgram, *m_oclDevice, CL_PROGRAM_BUILD_LOG, log_size + 1, program_log, NULL);
if (logger) {
logger->Log("Couldn't build program\n");
logger->Log(program_log);
}
delete[] program_log;
return false;
}
delete[] m_oclQueue;
delete[] m_oclKernelComputePartialVolumes;
delete[] m_oclKernelComputeSum;
m_oclQueue = new cl_command_queue[m_ompNumProcessors];
m_oclKernelComputePartialVolumes = new cl_kernel[m_ompNumProcessors];
m_oclKernelComputeSum = new cl_kernel[m_ompNumProcessors];
const char nameKernelComputePartialVolumes[] = "ComputePartialVolumes";
const char nameKernelComputeSum[] = "ComputePartialSums";
for (int32_t k = 0; k < m_ompNumProcessors; ++k) {
m_oclKernelComputePartialVolumes[k] = clCreateKernel(m_oclProgram, nameKernelComputePartialVolumes, &error);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't create kernel\n");
}
return false;
}
m_oclKernelComputeSum[k] = clCreateKernel(m_oclProgram, nameKernelComputeSum, &error);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't create kernel\n");
}
return false;
}
}
error = clGetKernelWorkGroupInfo(m_oclKernelComputePartialVolumes[0],
*m_oclDevice,
CL_KERNEL_WORK_GROUP_SIZE,
sizeof(size_t),
&m_oclWorkGroupSize,
NULL);
size_t workGroupSize = 0;
error = clGetKernelWorkGroupInfo(m_oclKernelComputeSum[0],
*m_oclDevice,
CL_KERNEL_WORK_GROUP_SIZE,
sizeof(size_t),
&workGroupSize,
NULL);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't query work group info\n");
}
return false;
}
if (workGroupSize < m_oclWorkGroupSize) {
m_oclWorkGroupSize = workGroupSize;
}
for (int32_t k = 0; k < m_ompNumProcessors; ++k) {
m_oclQueue[k] = clCreateCommandQueue(m_oclContext, *m_oclDevice, 0 /*CL_QUEUE_PROFILING_ENABLE*/, &error);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't create queue\n");
}
return false;
}
}
return true;
#else //CL_VERSION_1_1
return false;
#endif //CL_VERSION_1_1
}
bool VHACD::OCLRelease(IUserLogger* const logger)
{
#ifdef CL_VERSION_1_1
cl_int error;
if (m_oclKernelComputePartialVolumes) {
for (int32_t k = 0; k < m_ompNumProcessors; ++k) {
error = clReleaseKernel(m_oclKernelComputePartialVolumes[k]);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't release kernal\n");
}
return false;
}
}
delete[] m_oclKernelComputePartialVolumes;
}
if (m_oclKernelComputeSum) {
for (int32_t k = 0; k < m_ompNumProcessors; ++k) {
error = clReleaseKernel(m_oclKernelComputeSum[k]);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't release kernal\n");
}
return false;
}
}
delete[] m_oclKernelComputeSum;
}
if (m_oclQueue) {
for (int32_t k = 0; k < m_ompNumProcessors; ++k) {
error = clReleaseCommandQueue(m_oclQueue[k]);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't release queue\n");
}
return false;
}
}
delete[] m_oclQueue;
}
error = clReleaseProgram(m_oclProgram);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't release program\n");
}
return false;
}
error = clReleaseContext(m_oclContext);
if (error != CL_SUCCESS) {
if (logger) {
logger->Log("Couldn't release context\n");
}
return false;
}
return true;
#else //CL_VERSION_1_1
return false;
#endif //CL_VERSION_1_1
}
void VHACD::ComputePrimitiveSet(const Parameters& params)
{
if (GetCancel()) {
return;
}
m_timer.Tic();
m_stage = "Compute primitive set";
m_operation = "Convert volume to pset";
std::ostringstream msg;
if (params.m_logger) {
msg << "+ " << m_stage << std::endl;
params.m_logger->Log(msg.str().c_str());
}
Update(0.0, 0.0, params);
if (params.m_mode == 0) {
VoxelSet* vset = new VoxelSet;
m_volume->Convert(*vset);
m_pset = vset;
}
else {
TetrahedronSet* tset = new TetrahedronSet;
m_volume->Convert(*tset);
m_pset = tset;
}
delete m_volume;
m_volume = 0;
if (params.m_logger) {
msg.str("");
msg << "\t # primitives " << m_pset->GetNPrimitives() << std::endl;
msg << "\t # inside surface " << m_pset->GetNPrimitivesInsideSurf() << std::endl;
msg << "\t # on surface " << m_pset->GetNPrimitivesOnSurf() << std::endl;
params.m_logger->Log(msg.str().c_str());
}
m_overallProgress = 15.0;
Update(100.0, 100.0, params);
m_timer.Toc();
if (params.m_logger) {
msg.str("");
msg << "\t time " << m_timer.GetElapsedTime() / 1000.0 << "s" << std::endl;
params.m_logger->Log(msg.str().c_str());
}
}
bool VHACD::Compute(const double* const points, const uint32_t nPoints,
const uint32_t* const triangles,const uint32_t nTriangles, const Parameters& params)
{
return ComputeACD(points, nPoints, triangles, nTriangles, params);
}
bool VHACD::Compute(const float* const points,const uint32_t nPoints,
const uint32_t* const triangles,const uint32_t nTriangles, const Parameters& params)
{
return ComputeACD(points, nPoints, triangles, nTriangles, params);
}
double ComputePreferredCuttingDirection(const PrimitiveSet* const tset, Vec3<double>& dir)
{
double ex = tset->GetEigenValue(AXIS_X);
double ey = tset->GetEigenValue(AXIS_Y);
double ez = tset->GetEigenValue(AXIS_Z);
double vx = (ey - ez) * (ey - ez);
double vy = (ex - ez) * (ex - ez);
double vz = (ex - ey) * (ex - ey);
if (vx < vy && vx < vz) {
double e = ey * ey + ez * ez;
dir[0] = 1.0;
dir[1] = 0.0;
dir[2] = 0.0;
return (e == 0.0) ? 0.0 : 1.0 - vx / e;
}
else if (vy < vx && vy < vz) {
double e = ex * ex + ez * ez;
dir[0] = 0.0;
dir[1] = 1.0;
dir[2] = 0.0;
return (e == 0.0) ? 0.0 : 1.0 - vy / e;
}
else {
double e = ex * ex + ey * ey;
dir[0] = 0.0;
dir[1] = 0.0;
dir[2] = 1.0;
return (e == 0.0) ? 0.0 : 1.0 - vz / e;
}
}
void ComputeAxesAlignedClippingPlanes(const VoxelSet& vset, const short downsampling, SArray<Plane>& planes)
{
const Vec3<short> minV = vset.GetMinBBVoxels();
const Vec3<short> maxV = vset.GetMaxBBVoxels();
Vec3<double> pt;
Plane plane;
const short i0 = minV[0];
const short i1 = maxV[0];
plane.m_a = 1.0;
plane.m_b = 0.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_X;
for (short i = i0; i <= i1; i += downsampling) {
pt = vset.GetPoint(Vec3<double>(i + 0.5, 0.0, 0.0));
plane.m_d = -pt[0];
plane.m_index = i;
planes.PushBack(plane);
}
const short j0 = minV[1];
const short j1 = maxV[1];
plane.m_a = 0.0;
plane.m_b = 1.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_Y;
for (short j = j0; j <= j1; j += downsampling) {
pt = vset.GetPoint(Vec3<double>(0.0, j + 0.5, 0.0));
plane.m_d = -pt[1];
plane.m_index = j;
planes.PushBack(plane);
}
const short k0 = minV[2];
const short k1 = maxV[2];
plane.m_a = 0.0;
plane.m_b = 0.0;
plane.m_c = 1.0;
plane.m_axis = AXIS_Z;
for (short k = k0; k <= k1; k += downsampling) {
pt = vset.GetPoint(Vec3<double>(0.0, 0.0, k + 0.5));
plane.m_d = -pt[2];
plane.m_index = k;
planes.PushBack(plane);
}
}
void ComputeAxesAlignedClippingPlanes(const TetrahedronSet& tset, const short downsampling, SArray<Plane>& planes)
{
const Vec3<double> minV = tset.GetMinBB();
const Vec3<double> maxV = tset.GetMaxBB();
const double scale = tset.GetSacle();
const short i0 = 0;
const short j0 = 0;
const short k0 = 0;
const short i1 = static_cast<short>((maxV[0] - minV[0]) / scale + 0.5);
const short j1 = static_cast<short>((maxV[1] - minV[1]) / scale + 0.5);
const short k1 = static_cast<short>((maxV[2] - minV[2]) / scale + 0.5);
Plane plane;
plane.m_a = 1.0;
plane.m_b = 0.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_X;
for (short i = i0; i <= i1; i += downsampling) {
double x = minV[0] + scale * i;
plane.m_d = -x;
plane.m_index = i;
planes.PushBack(plane);
}
plane.m_a = 0.0;
plane.m_b = 1.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_Y;
for (short j = j0; j <= j1; j += downsampling) {
double y = minV[1] + scale * j;
plane.m_d = -y;
plane.m_index = j;
planes.PushBack(plane);
}
plane.m_a = 0.0;
plane.m_b = 0.0;
plane.m_c = 1.0;
plane.m_axis = AXIS_Z;
for (short k = k0; k <= k1; k += downsampling) {
double z = minV[2] + scale * k;
plane.m_d = -z;
plane.m_index = k;
planes.PushBack(plane);
}
}
void RefineAxesAlignedClippingPlanes(const VoxelSet& vset, const Plane& bestPlane, const short downsampling,
SArray<Plane>& planes)
{
const Vec3<short> minV = vset.GetMinBBVoxels();
const Vec3<short> maxV = vset.GetMaxBBVoxels();
Vec3<double> pt;
Plane plane;
if (bestPlane.m_axis == AXIS_X) {
const short i0 = MAX(minV[0], bestPlane.m_index - downsampling);
const short i1 = MIN(maxV[0], bestPlane.m_index + downsampling);
plane.m_a = 1.0;
plane.m_b = 0.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_X;
for (short i = i0; i <= i1; ++i) {
pt = vset.GetPoint(Vec3<double>(i + 0.5, 0.0, 0.0));
plane.m_d = -pt[0];
plane.m_index = i;
planes.PushBack(plane);
}
}
else if (bestPlane.m_axis == AXIS_Y) {
const short j0 = MAX(minV[1], bestPlane.m_index - downsampling);
const short j1 = MIN(maxV[1], bestPlane.m_index + downsampling);
plane.m_a = 0.0;
plane.m_b = 1.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_Y;
for (short j = j0; j <= j1; ++j) {
pt = vset.GetPoint(Vec3<double>(0.0, j + 0.5, 0.0));
plane.m_d = -pt[1];
plane.m_index = j;
planes.PushBack(plane);
}
}
else {
const short k0 = MAX(minV[2], bestPlane.m_index - downsampling);
const short k1 = MIN(maxV[2], bestPlane.m_index + downsampling);
plane.m_a = 0.0;
plane.m_b = 0.0;
plane.m_c = 1.0;
plane.m_axis = AXIS_Z;
for (short k = k0; k <= k1; ++k) {
pt = vset.GetPoint(Vec3<double>(0.0, 0.0, k + 0.5));
plane.m_d = -pt[2];
plane.m_index = k;
planes.PushBack(plane);
}
}
}
void RefineAxesAlignedClippingPlanes(const TetrahedronSet& tset, const Plane& bestPlane, const short downsampling,
SArray<Plane>& planes)
{
const Vec3<double> minV = tset.GetMinBB();
const Vec3<double> maxV = tset.GetMaxBB();
const double scale = tset.GetSacle();
Plane plane;
if (bestPlane.m_axis == AXIS_X) {
const short i0 = MAX(0, bestPlane.m_index - downsampling);
const short i1 = static_cast<short>(MIN((maxV[0] - minV[0]) / scale + 0.5, bestPlane.m_index + downsampling));
plane.m_a = 1.0;
plane.m_b = 0.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_X;
for (short i = i0; i <= i1; ++i) {
double x = minV[0] + scale * i;
plane.m_d = -x;
plane.m_index = i;
planes.PushBack(plane);
}
}
else if (bestPlane.m_axis == AXIS_Y) {
const short j0 = MAX(0, bestPlane.m_index - downsampling);
const short j1 = static_cast<short>(MIN((maxV[1] - minV[1]) / scale + 0.5, bestPlane.m_index + downsampling));
plane.m_a = 0.0;
plane.m_b = 1.0;
plane.m_c = 0.0;
plane.m_axis = AXIS_Y;
for (short j = j0; j <= j1; ++j) {
double y = minV[1] + scale * j;
plane.m_d = -y;
plane.m_index = j;
planes.PushBack(plane);
}
}
else {
const short k0 = MAX(0, bestPlane.m_index - downsampling);
const short k1 = static_cast<short>(MIN((maxV[2] - minV[2]) / scale + 0.5, bestPlane.m_index + downsampling));
plane.m_a = 0.0;
plane.m_b = 0.0;
plane.m_c = 1.0;
plane.m_axis = AXIS_Z;
for (short k = k0; k <= k1; ++k) {
double z = minV[2] + scale * k;
plane.m_d = -z;
plane.m_index = k;
planes.PushBack(plane);
}
}
}
inline double ComputeLocalConcavity(const double volume, const double volumeCH)
{
return fabs(volumeCH - volume) / volumeCH;
}
inline double ComputeConcavity(const double volume, const double volumeCH, const double volume0)
{
return fabs(volumeCH - volume) / volume0;
}
//#define DEBUG_TEMP
void VHACD::ComputeBestClippingPlane(const PrimitiveSet* inputPSet, const double volume, const SArray<Plane>& planes,
const Vec3<double>& preferredCuttingDirection, const double w, const double alpha, const double beta,
const int32_t convexhullDownsampling, const double progress0, const double progress1, Plane& bestPlane,
double& minConcavity, const Parameters& params)
{
if (GetCancel()) {
return;
}
char msg[256];
size_t nPrimitives = inputPSet->GetNPrimitives();
bool oclAcceleration = (nPrimitives > OCL_MIN_NUM_PRIMITIVES && params.m_oclAcceleration && params.m_mode == 0) ? true : false;
int32_t iBest = -1;
int32_t nPlanes = static_cast<int32_t>(planes.Size());
bool cancel = false;
int32_t done = 0;
double minTotal = MAX_DOUBLE;
double minBalance = MAX_DOUBLE;
double minSymmetry = MAX_DOUBLE;
minConcavity = MAX_DOUBLE;
SArray<Vec3<double> >* chPts = new SArray<Vec3<double> >[2 * m_ompNumProcessors];
Mesh* chs = new Mesh[2 * m_ompNumProcessors];
PrimitiveSet* onSurfacePSet = inputPSet->Create();
inputPSet->SelectOnSurface(onSurfacePSet);
PrimitiveSet** psets = 0;
if (!params.m_convexhullApproximation) {
psets = new PrimitiveSet*[2 * m_ompNumProcessors];
for (int32_t i = 0; i < 2 * m_ompNumProcessors; ++i) {
psets[i] = inputPSet->Create();
}
}
#ifdef CL_VERSION_1_1
// allocate OpenCL data structures
cl_mem voxels;
cl_mem* partialVolumes = 0;
size_t globalSize = 0;
size_t nWorkGroups = 0;
double unitVolume = 0.0;
if (oclAcceleration) {
VoxelSet* vset = (VoxelSet*)inputPSet;
const Vec3<double> minBB = vset->GetMinBB();
const float fMinBB[4] = { (float)minBB[0], (float)minBB[1], (float)minBB[2], 1.0f };
const float fSclae[4] = { (float)vset->GetScale(), (float)vset->GetScale(), (float)vset->GetScale(), 0.0f };
const int32_t nVoxels = (int32_t)nPrimitives;
unitVolume = vset->GetUnitVolume();
nWorkGroups = (nPrimitives + 4 * m_oclWorkGroupSize - 1) / (4 * m_oclWorkGroupSize);
globalSize = nWorkGroups * m_oclWorkGroupSize;
cl_int error;
voxels = clCreateBuffer(m_oclContext,
CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR,
sizeof(Voxel) * nPrimitives,
vset->GetVoxels(),
&error);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't create buffer\n");
}
SetCancel(true);
}
partialVolumes = new cl_mem[m_ompNumProcessors];
for (int32_t i = 0; i < m_ompNumProcessors; ++i) {
partialVolumes[i] = clCreateBuffer(m_oclContext,
CL_MEM_WRITE_ONLY,
sizeof(uint32_t) * 4 * nWorkGroups,
NULL,
&error);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't create buffer\n");
}
SetCancel(true);
break;
}
error = clSetKernelArg(m_oclKernelComputePartialVolumes[i], 0, sizeof(cl_mem), &voxels);
error |= clSetKernelArg(m_oclKernelComputePartialVolumes[i], 1, sizeof(uint32_t), &nVoxels);
error |= clSetKernelArg(m_oclKernelComputePartialVolumes[i], 3, sizeof(float) * 4, fMinBB);
error |= clSetKernelArg(m_oclKernelComputePartialVolumes[i], 4, sizeof(float) * 4, &fSclae);
error |= clSetKernelArg(m_oclKernelComputePartialVolumes[i], 5, sizeof(uint32_t) * 4 * m_oclWorkGroupSize, NULL);
error |= clSetKernelArg(m_oclKernelComputePartialVolumes[i], 6, sizeof(cl_mem), &(partialVolumes[i]));
error |= clSetKernelArg(m_oclKernelComputeSum[i], 0, sizeof(cl_mem), &(partialVolumes[i]));
error |= clSetKernelArg(m_oclKernelComputeSum[i], 2, sizeof(uint32_t) * 4 * m_oclWorkGroupSize, NULL);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't kernel arguments \n");
}
SetCancel(true);
}
}
}
#else // CL_VERSION_1_1
oclAcceleration = false;
#endif // CL_VERSION_1_1
#ifdef DEBUG_TEMP
Timer timerComputeCost;
timerComputeCost.Tic();
#endif // DEBUG_TEMP
#if USE_THREAD == 1 && _OPENMP
#pragma omp parallel for
#endif
for (int32_t x = 0; x < nPlanes; ++x) {
int32_t threadID = 0;
#if USE_THREAD == 1 && _OPENMP
threadID = omp_get_thread_num();
#pragma omp flush(cancel)
#endif
if (!cancel) {
//Update progress
if (GetCancel()) {
cancel = true;
#if USE_THREAD == 1 && _OPENMP
#pragma omp flush(cancel)
#endif
}
Plane plane = planes[x];
if (oclAcceleration) {
#ifdef CL_VERSION_1_1
const float fPlane[4] = { (float)plane.m_a, (float)plane.m_b, (float)plane.m_c, (float)plane.m_d };
cl_int error = clSetKernelArg(m_oclKernelComputePartialVolumes[threadID], 2, sizeof(float) * 4, fPlane);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't kernel atguments \n");
}
SetCancel(true);
}
error = clEnqueueNDRangeKernel(m_oclQueue[threadID], m_oclKernelComputePartialVolumes[threadID],
1, NULL, &globalSize, &m_oclWorkGroupSize, 0, NULL, NULL);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't run kernel \n");
}
SetCancel(true);
}
int32_t nValues = (int32_t)nWorkGroups;
while (nValues > 1) {
error = clSetKernelArg(m_oclKernelComputeSum[threadID], 1, sizeof(int32_t), &nValues);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't kernel atguments \n");
}
SetCancel(true);
}
size_t nWorkGroups = (nValues + m_oclWorkGroupSize - 1) / m_oclWorkGroupSize;
size_t globalSize = nWorkGroups * m_oclWorkGroupSize;
error = clEnqueueNDRangeKernel(m_oclQueue[threadID], m_oclKernelComputeSum[threadID],
1, NULL, &globalSize, &m_oclWorkGroupSize, 0, NULL, NULL);
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't run kernel \n");
}
SetCancel(true);
}
nValues = (int32_t)nWorkGroups;
}
#endif // CL_VERSION_1_1
}
Mesh& leftCH = chs[threadID];
Mesh& rightCH = chs[threadID + m_ompNumProcessors];
rightCH.ResizePoints(0);
leftCH.ResizePoints(0);
rightCH.ResizeTriangles(0);
leftCH.ResizeTriangles(0);
// compute convex-hulls
#ifdef TEST_APPROX_CH
double volumeLeftCH1;
double volumeRightCH1;
#endif //TEST_APPROX_CH
if (params.m_convexhullApproximation) {
SArray<Vec3<double> >& leftCHPts = chPts[threadID];
SArray<Vec3<double> >& rightCHPts = chPts[threadID + m_ompNumProcessors];
rightCHPts.Resize(0);
leftCHPts.Resize(0);
onSurfacePSet->Intersect(plane, &rightCHPts, &leftCHPts, convexhullDownsampling * 32);
inputPSet->GetConvexHull().Clip(plane, rightCHPts, leftCHPts);
rightCH.ComputeConvexHull((double*)rightCHPts.Data(), rightCHPts.Size());
leftCH.ComputeConvexHull((double*)leftCHPts.Data(), leftCHPts.Size());
#ifdef TEST_APPROX_CH
Mesh leftCH1;
Mesh rightCH1;
VoxelSet right;
VoxelSet left;
onSurfacePSet->Clip(plane, &right, &left);
right.ComputeConvexHull(rightCH1, convexhullDownsampling);
left.ComputeConvexHull(leftCH1, convexhullDownsampling);
volumeLeftCH1 = leftCH1.ComputeVolume();
volumeRightCH1 = rightCH1.ComputeVolume();
#endif //TEST_APPROX_CH
}
else {
PrimitiveSet* const right = psets[threadID];
PrimitiveSet* const left = psets[threadID + m_ompNumProcessors];
onSurfacePSet->Clip(plane, right, left);
right->ComputeConvexHull(rightCH, convexhullDownsampling);
left->ComputeConvexHull(leftCH, convexhullDownsampling);
}
double volumeLeftCH = leftCH.ComputeVolume();
double volumeRightCH = rightCH.ComputeVolume();
// compute clipped volumes
double volumeLeft = 0.0;
double volumeRight = 0.0;
if (oclAcceleration) {
#ifdef CL_VERSION_1_1
uint32_t volumes[4];
cl_int error = clEnqueueReadBuffer(m_oclQueue[threadID], partialVolumes[threadID], CL_TRUE,
0, sizeof(uint32_t) * 4, volumes, 0, NULL, NULL);
size_t nPrimitivesRight = volumes[0] + volumes[1] + volumes[2] + volumes[3];
size_t nPrimitivesLeft = nPrimitives - nPrimitivesRight;
volumeRight = nPrimitivesRight * unitVolume;
volumeLeft = nPrimitivesLeft * unitVolume;
if (error != CL_SUCCESS) {
if (params.m_logger) {
params.m_logger->Log("Couldn't read buffer \n");
}
SetCancel(true);
}
#endif // CL_VERSION_1_1
}
else {
inputPSet->ComputeClippedVolumes(plane, volumeRight, volumeLeft);
}
double concavityLeft = ComputeConcavity(volumeLeft, volumeLeftCH, m_volumeCH0);
double concavityRight = ComputeConcavity(volumeRight, volumeRightCH, m_volumeCH0);
double concavity = (concavityLeft + concavityRight);
// compute cost
double balance = alpha * fabs(volumeLeft - volumeRight) / m_volumeCH0;
double d = w * (preferredCuttingDirection[0] * plane.m_a + preferredCuttingDirection[1] * plane.m_b + preferredCuttingDirection[2] * plane.m_c);
double symmetry = beta * d;
double total = concavity + balance + symmetry;
#if USE_THREAD == 1 && _OPENMP
#pragma omp critical
#endif
{
if (total < minTotal || (total == minTotal && x < iBest)) {
minConcavity = concavity;
minBalance = balance;
minSymmetry = symmetry;
bestPlane = plane;
minTotal = total;
iBest = x;
}
++done;
if (!(done & 127)) // reduce update frequency
{
double progress = done * (progress1 - progress0) / nPlanes + progress0;
Update(m_stageProgress, progress, params);
}
}
}
}
#ifdef DEBUG_TEMP
timerComputeCost.Toc();
printf_s("Cost[%i] = %f\n", nPlanes, timerComputeCost.GetElapsedTime());
#endif // DEBUG_TEMP
#ifdef CL_VERSION_1_1
if (oclAcceleration) {
clReleaseMemObject(voxels);
for (int32_t i = 0; i < m_ompNumProcessors; ++i) {
clReleaseMemObject(partialVolumes[i]);
}
delete[] partialVolumes;
}
#endif // CL_VERSION_1_1
if (psets) {
for (int32_t i = 0; i < 2 * m_ompNumProcessors; ++i) {
delete psets[i];
}
delete[] psets;
}
delete onSurfacePSet;
delete[] chPts;
delete[] chs;
if (params.m_logger) {
sprintf(msg, "\n\t\t\t Best %04i T=%2.6f C=%2.6f B=%2.6f S=%2.6f (%1.1f, %1.1f, %1.1f, %3.3f)\n\n", iBest, minTotal, minConcavity, minBalance, minSymmetry, bestPlane.m_a, bestPlane.m_b, bestPlane.m_c, bestPlane.m_d);
params.m_logger->Log(msg);
}
}
void VHACD::ComputeACD(const Parameters& params)
{
if (GetCancel()) {
return;
}
m_timer.Tic();
m_stage = "Approximate Convex Decomposition";
m_stageProgress = 0.0;
std::ostringstream msg;
if (params.m_logger) {
msg << "+ " << m_stage << std::endl;
params.m_logger->Log(msg.str().c_str());
}
SArray<PrimitiveSet*> parts;
SArray<PrimitiveSet*> inputParts;
SArray<PrimitiveSet*> temp;
inputParts.PushBack(m_pset);
m_pset = 0;
SArray<Plane> planes;
SArray<Plane> planesRef;
uint32_t sub = 0;
bool firstIteration = true;
m_volumeCH0 = 1.0;
// Compute the decomposition depth based on the number of convex hulls being requested..
uint32_t hullCount = 2;
uint32_t depth = 1;
while (params.m_maxConvexHulls > hullCount)
{
depth++;
hullCount *= 2;
}
// We must always increment the decomposition depth one higher than the maximum number of hulls requested.
// The reason for this is as follows.
// Say, for example, the user requests 32 convex hulls exactly. This would be a decomposition depth of 5.
// However, when we do that, we do *not* necessarily get 32 hulls as a result. This is because, during
// the recursive descent of the binary tree, one or more of the leaf nodes may have no concavity and
// will not be split. So, in this way, even with a decomposition depth of 5, you can produce fewer than
// 32 hulls. So, in this case, we would set the decomposition depth to 6 (producing up to as high as 64 convex hulls).
// Then, the merge step which combines over-described hulls down to the user requested amount, we will end up
// getting exactly 32 convex hulls as a result.
// We could just allow the artist to directly control the decomposition depth directly, but this would be a bit
// too complex and the preference is simply to let them specify how many hulls they want and derive the solution
// from that.
depth++;
while (sub++ < depth && inputParts.Size() > 0 && !m_cancel) {
msg.str("");
msg << "Subdivision level " << sub;
m_operation = msg.str();
if (params.m_logger) {
msg.str("");
msg << "\t Subdivision level " << sub << std::endl;
params.m_logger->Log(msg.str().c_str());
}
double maxConcavity = 0.0;
const size_t nInputParts = inputParts.Size();
Update(m_stageProgress, 0.0, params);
for (size_t p = 0; p < nInputParts && !m_cancel; ++p) {
const double progress0 = p * 100.0 / nInputParts;
const double progress1 = (p + 0.75) * 100.0 / nInputParts;
const double progress2 = (p + 1.00) * 100.0 / nInputParts;
Update(m_stageProgress, progress0, params);
PrimitiveSet* pset = inputParts[p];
inputParts[p] = 0;
double volume = pset->ComputeVolume();
pset->ComputeBB();
pset->ComputePrincipalAxes();
if (params.m_pca) {
pset->AlignToPrincipalAxes();
}
pset->ComputeConvexHull(pset->GetConvexHull());
double volumeCH = fabs(pset->GetConvexHull().ComputeVolume());
if (firstIteration) {
m_volumeCH0 = volumeCH;
}
double concavity = ComputeConcavity(volume, volumeCH, m_volumeCH0);
double error = 1.01 * pset->ComputeMaxVolumeError() / m_volumeCH0;
if (firstIteration) {
firstIteration = false;
}
if (params.m_logger) {
msg.str("");
msg << "\t -> Part[" << p
<< "] C = " << concavity
<< ", E = " << error
<< ", VS = " << pset->GetNPrimitivesOnSurf()
<< ", VI = " << pset->GetNPrimitivesInsideSurf()
<< std::endl;
params.m_logger->Log(msg.str().c_str());
}
if (concavity > params.m_concavity && concavity > error) {
Vec3<double> preferredCuttingDirection;
double w = ComputePreferredCuttingDirection(pset, preferredCuttingDirection);
planes.Resize(0);
if (params.m_mode == 0) {
VoxelSet* vset = (VoxelSet*)pset;
ComputeAxesAlignedClippingPlanes(*vset, params.m_planeDownsampling, planes);
}
else {
TetrahedronSet* tset = (TetrahedronSet*)pset;
ComputeAxesAlignedClippingPlanes(*tset, params.m_planeDownsampling, planes);
}
if (params.m_logger) {
msg.str("");
msg << "\t\t [Regular sampling] Number of clipping planes " << planes.Size() << std::endl;
params.m_logger->Log(msg.str().c_str());
}
Plane bestPlane;
double minConcavity = MAX_DOUBLE;
ComputeBestClippingPlane(pset,
volume,
planes,
preferredCuttingDirection,
w,
concavity * params.m_alpha,
concavity * params.m_beta,
params.m_convexhullDownsampling,
progress0,
progress1,
bestPlane,
minConcavity,
params);
if (!m_cancel && (params.m_planeDownsampling > 1 || params.m_convexhullDownsampling > 1)) {
planesRef.Resize(0);
if (params.m_mode == 0) {
VoxelSet* vset = (VoxelSet*)pset;
RefineAxesAlignedClippingPlanes(*vset, bestPlane, params.m_planeDownsampling, planesRef);
}
else {
TetrahedronSet* tset = (TetrahedronSet*)pset;
RefineAxesAlignedClippingPlanes(*tset, bestPlane, params.m_planeDownsampling, planesRef);
}
if (params.m_logger) {
msg.str("");
msg << "\t\t [Refining] Number of clipping planes " << planesRef.Size() << std::endl;
params.m_logger->Log(msg.str().c_str());
}
ComputeBestClippingPlane(pset,
volume,
planesRef,
preferredCuttingDirection,
w,
concavity * params.m_alpha,
concavity * params.m_beta,
1, // convexhullDownsampling = 1
progress1,
progress2,
bestPlane,
minConcavity,
params);
}
if (GetCancel()) {
delete pset; // clean up
break;
}
else {
if (maxConcavity < minConcavity) {
maxConcavity = minConcavity;
}
PrimitiveSet* bestLeft = pset->Create();
PrimitiveSet* bestRight = pset->Create();
temp.PushBack(bestLeft);
temp.PushBack(bestRight);
pset->Clip(bestPlane, bestRight, bestLeft);
if (params.m_pca) {
bestRight->RevertAlignToPrincipalAxes();
bestLeft->RevertAlignToPrincipalAxes();
}
delete pset;
}
}
else {
if (params.m_pca) {
pset->RevertAlignToPrincipalAxes();
}
parts.PushBack(pset);
}
}
Update(95.0 * (1.0 - maxConcavity) / (1.0 - params.m_concavity), 100.0, params);
if (GetCancel()) {
const size_t nTempParts = temp.Size();
for (size_t p = 0; p < nTempParts; ++p) {
delete temp[p];
}
temp.Resize(0);
}
else {
inputParts = temp;
temp.Resize(0);
}
}
const size_t nInputParts = inputParts.Size();
for (size_t p = 0; p < nInputParts; ++p) {
parts.PushBack(inputParts[p]);
}
if (GetCancel()) {
const size_t nParts = parts.Size();
for (size_t p = 0; p < nParts; ++p) {
delete parts[p];
}
return;
}
m_overallProgress = 90.0;
Update(m_stageProgress, 100.0, params);
msg.str("");
msg << "Generate convex-hulls";
m_operation = msg.str();
size_t nConvexHulls = parts.Size();
if (params.m_logger) {
msg.str("");
msg << "+ Generate " << nConvexHulls << " convex-hulls " << std::endl;
params.m_logger->Log(msg.str().c_str());
}
Update(m_stageProgress, 0.0, params);
m_convexHulls.Resize(0);
for (size_t p = 0; p < nConvexHulls && !m_cancel; ++p) {
Update(m_stageProgress, p * 100.0 / nConvexHulls, params);
m_convexHulls.PushBack(new Mesh);
parts[p]->ComputeConvexHull(*m_convexHulls[p]);
size_t nv = m_convexHulls[p]->GetNPoints();
double x, y, z;
for (size_t i = 0; i < nv; ++i) {
Vec3<double>& pt = m_convexHulls[p]->GetPoint(i);
x = pt[0];
y = pt[1];
z = pt[2];
pt[0] = m_rot[0][0] * x + m_rot[0][1] * y + m_rot[0][2] * z + m_barycenter[0];
pt[1] = m_rot[1][0] * x + m_rot[1][1] * y + m_rot[1][2] * z + m_barycenter[1];
pt[2] = m_rot[2][0] * x + m_rot[2][1] * y + m_rot[2][2] * z + m_barycenter[2];
}
}
const size_t nParts = parts.Size();
for (size_t p = 0; p < nParts; ++p) {
delete parts[p];
parts[p] = 0;
}
parts.Resize(0);
if (GetCancel()) {
const size_t nConvexHulls = m_convexHulls.Size();
for (size_t p = 0; p < nConvexHulls; ++p) {
delete m_convexHulls[p];
}
m_convexHulls.Clear();
return;
}
m_overallProgress = 95.0;
Update(100.0, 100.0, params);
m_timer.Toc();
if (params.m_logger) {
msg.str("");
msg << "\t time " << m_timer.GetElapsedTime() / 1000.0 << "s" << std::endl;
params.m_logger->Log(msg.str().c_str());
}
}
void AddPoints(const Mesh* const mesh, SArray<Vec3<double> >& pts)
{
const int32_t n = (int32_t)mesh->GetNPoints();
for (int32_t i = 0; i < n; ++i) {
pts.PushBack(mesh->GetPoint(i));
}
}
void ComputeConvexHull(const Mesh* const ch1, const Mesh* const ch2, SArray<Vec3<double> >& pts, Mesh* const combinedCH)
{
pts.Resize(0);
AddPoints(ch1, pts);
AddPoints(ch2, pts);
btConvexHullComputer ch;
ch.compute((double*)pts.Data(), 3 * sizeof(double), (int32_t)pts.Size(), -1.0, -1.0);
combinedCH->ResizePoints(0);
combinedCH->ResizeTriangles(0);
for (int32_t v = 0; v < ch.vertices.size(); v++) {
combinedCH->AddPoint(Vec3<double>(ch.vertices[v].getX(), ch.vertices[v].getY(), ch.vertices[v].getZ()));
}
const int32_t nt = ch.faces.size();
for (int32_t t = 0; t < nt; ++t) {
const btConvexHullComputer::Edge* sourceEdge = &(ch.edges[ch.faces[t]]);
int32_t a = sourceEdge->getSourceVertex();
int32_t b = sourceEdge->getTargetVertex();
const btConvexHullComputer::Edge* edge = sourceEdge->getNextEdgeOfFace();
int32_t c = edge->getTargetVertex();
while (c != a) {
combinedCH->AddTriangle(Vec3<int32_t>(a, b, c));
edge = edge->getNextEdgeOfFace();
b = c;
c = edge->getTargetVertex();
}
}
}
void VHACD::MergeConvexHulls(const Parameters& params)
{
if (GetCancel()) {
return;
}
m_timer.Tic();
m_stage = "Merge Convex Hulls";
std::ostringstream msg;
if (params.m_logger) {
msg << "+ " << m_stage << std::endl;
params.m_logger->Log(msg.str().c_str());
}
// Get the current number of convex hulls
size_t nConvexHulls = m_convexHulls.Size();
// Iteration counter
int32_t iteration = 0;
// While we have more than at least one convex hull and the user has not asked us to cancel the operation
if (nConvexHulls > 1 && !m_cancel)
{
// Get the gamma error threshold for when to exit
SArray<Vec3<double> > pts;
Mesh combinedCH;
// Populate the cost matrix
size_t idx = 0;
SArray<float> costMatrix;
costMatrix.Resize(((nConvexHulls * nConvexHulls) - nConvexHulls) >> 1);
for (size_t p1 = 1; p1 < nConvexHulls; ++p1)
{
const float volume1 = m_convexHulls[p1]->ComputeVolume();
for (size_t p2 = 0; p2 < p1; ++p2)
{
ComputeConvexHull(m_convexHulls[p1], m_convexHulls[p2], pts, &combinedCH);
costMatrix[idx++] = ComputeConcavity(volume1 + m_convexHulls[p2]->ComputeVolume(), combinedCH.ComputeVolume(), m_volumeCH0);
}
}
// Until we cant merge below the maximum cost
size_t costSize = m_convexHulls.Size();
while (!m_cancel)
{
msg.str("");
msg << "Iteration " << iteration++;
m_operation = msg.str();
// Search for lowest cost
float bestCost = (std::numeric_limits<float>::max)();
const size_t addr = FindMinimumElement(costMatrix.Data(), &bestCost, 0, costMatrix.Size());
if ( (costSize-1) < params.m_maxConvexHulls)
{
break;
}
const size_t addrI = (static_cast<int32_t>(sqrt(1 + (8 * addr))) - 1) >> 1;
const size_t p1 = addrI + 1;
const size_t p2 = addr - ((addrI * (addrI + 1)) >> 1);
assert(p1 >= 0);
assert(p2 >= 0);
assert(p1 < costSize);
assert(p2 < costSize);
if (params.m_logger)
{
msg.str("");
msg << "\t\t Merging (" << p1 << ", " << p2 << ") " << bestCost << std::endl
<< std::endl;
params.m_logger->Log(msg.str().c_str());
}
// Make the lowest cost row and column into a new hull
Mesh* cch = new Mesh;
ComputeConvexHull(m_convexHulls[p1], m_convexHulls[p2], pts, cch);
delete m_convexHulls[p2];
m_convexHulls[p2] = cch;
delete m_convexHulls[p1];
std::swap(m_convexHulls[p1], m_convexHulls[m_convexHulls.Size() - 1]);
m_convexHulls.PopBack();
costSize = costSize - 1;
// Calculate costs versus the new hull
size_t rowIdx = ((p2 - 1) * p2) >> 1;
const float volume1 = m_convexHulls[p2]->ComputeVolume();
for (size_t i = 0; (i < p2) && (!m_cancel); ++i)
{
ComputeConvexHull(m_convexHulls[p2], m_convexHulls[i], pts, &combinedCH);
costMatrix[rowIdx++] = ComputeConcavity(volume1 + m_convexHulls[i]->ComputeVolume(), combinedCH.ComputeVolume(), m_volumeCH0);
}
rowIdx += p2;
for (size_t i = p2 + 1; (i < costSize) && (!m_cancel); ++i)
{
ComputeConvexHull(m_convexHulls[p2], m_convexHulls[i], pts, &combinedCH);
costMatrix[rowIdx] = ComputeConcavity(volume1 + m_convexHulls[i]->ComputeVolume(), combinedCH.ComputeVolume(), m_volumeCH0);
rowIdx += i;
assert(rowIdx >= 0);
}
// Move the top column in to replace its space
const size_t erase_idx = ((costSize - 1) * costSize) >> 1;
if (p1 < costSize) {
rowIdx = (addrI * p1) >> 1;
size_t top_row = erase_idx;
for (size_t i = 0; i < p1; ++i) {
if (i != p2) {
costMatrix[rowIdx] = costMatrix[top_row];
}
++rowIdx;
++top_row;
}
++top_row;
rowIdx += p1;
for (size_t i = p1 + 1; i < (costSize + 1); ++i) {
costMatrix[rowIdx] = costMatrix[top_row++];
rowIdx += i;
assert(rowIdx >= 0);
}
}
costMatrix.Resize(erase_idx);
}
}
m_overallProgress = 99.0;
Update(100.0, 100.0, params);
m_timer.Toc();
if (params.m_logger) {
msg.str("");
msg << "\t time " << m_timer.GetElapsedTime() / 1000.0 << "s" << std::endl;
params.m_logger->Log(msg.str().c_str());
}
}
void VHACD::SimplifyConvexHull(Mesh* const ch, const size_t nvertices, const double minVolume)
{
if (nvertices <= 4) {
return;
}
ICHull icHull;
if (mRaycastMesh)
{
// We project these points onto the original source mesh to increase precision
// The voxelization process drops floating point precision so returned data points are not exactly lying on the
// surface of the original source mesh.
// The first step is we need to compute the bounding box of the mesh we are trying to build a convex hull for.
// From this bounding box, we compute the length of the diagonal to get a relative size and center for point projection
uint32_t nPoints = ch->GetNPoints();
Vec3<double> *inputPoints = ch->GetPointsBuffer();
Vec3<double> bmin(inputPoints[0]);
Vec3<double> bmax(inputPoints[1]);
for (uint32_t i = 1; i < nPoints; i++)
{
const Vec3<double> &p = inputPoints[i];
p.UpdateMinMax(bmin, bmax);
}
Vec3<double> center;
double diagonalLength = center.GetCenter(bmin, bmax); // Get the center of the bounding box
// This is the error threshold for determining if we should use the raycast result data point vs. the voxelized result.
double pointDistanceThreshold = diagonalLength * 0.05;
// If a new point is within 1/100th the diagonal length of the bounding volume we do not add it. To do so would create a
// thin sliver in the resulting convex hull
double snapDistanceThreshold = diagonalLength * 0.01;
double snapDistanceThresholdSquared = snapDistanceThreshold*snapDistanceThreshold;
// Allocate buffer for projected vertices
Vec3<double> *outputPoints = new Vec3<double>[nPoints];
uint32_t outCount = 0;
for (uint32_t i = 0; i < nPoints; i++)
{
Vec3<double> &inputPoint = inputPoints[i];
Vec3<double> &outputPoint = outputPoints[outCount];
// Compute the direction vector from the center of this mesh to the vertex
Vec3<double> dir = inputPoint - center;
// Normalize the direction vector.
dir.Normalize();
// Multiply times the diagonal length of the mesh
dir *= diagonalLength;
// Add the center back in again to get the destination point
dir += center;
// By default the output point is equal to the input point
outputPoint = inputPoint;
double pointDistance;
if (mRaycastMesh->raycast(center.GetData(), dir.GetData(), inputPoint.GetData(), outputPoint.GetData(),&pointDistance) )
{
// If the nearest intersection point is too far away, we keep the original source data point.
// Not all points lie directly on the original mesh surface
if (pointDistance > pointDistanceThreshold)
{
outputPoint = inputPoint;
}
}
// Ok, before we add this point, we do not want to create points which are extremely close to each other.
// This will result in tiny sliver triangles which are really bad for collision detection.
bool foundNearbyPoint = false;
for (uint32_t j = 0; j < outCount; j++)
{
// If this new point is extremely close to an existing point, we do not add it!
double squaredDistance = outputPoints[j].GetDistanceSquared(outputPoint);
if (squaredDistance < snapDistanceThresholdSquared )
{
foundNearbyPoint = true;
break;
}
}
if (!foundNearbyPoint)
{
outCount++;
}
}
icHull.AddPoints(outputPoints, outCount);
delete[]outputPoints;
}
else
{
icHull.AddPoints(ch->GetPointsBuffer(), ch->GetNPoints());
}
icHull.Process((uint32_t)nvertices, minVolume);
TMMesh& mesh = icHull.GetMesh();
const size_t nT = mesh.GetNTriangles();
const size_t nV = mesh.GetNVertices();
ch->ResizePoints(nV);
ch->ResizeTriangles(nT);
mesh.GetIFS(ch->GetPointsBuffer(), ch->GetTrianglesBuffer());
}
void VHACD::SimplifyConvexHulls(const Parameters& params)
{
if (m_cancel || params.m_maxNumVerticesPerCH < 4) {
return;
}
m_timer.Tic();
m_stage = "Simplify convex-hulls";
m_operation = "Simplify convex-hulls";
std::ostringstream msg;
const size_t nConvexHulls = m_convexHulls.Size();
if (params.m_logger) {
msg << "+ Simplify " << nConvexHulls << " convex-hulls " << std::endl;
params.m_logger->Log(msg.str().c_str());
}
Update(0.0, 0.0, params);
for (size_t i = 0; i < nConvexHulls && !m_cancel; ++i) {
if (params.m_logger) {
msg.str("");
msg << "\t\t Simplify CH[" << std::setfill('0') << std::setw(5) << i << "] " << m_convexHulls[i]->GetNPoints() << " V, " << m_convexHulls[i]->GetNTriangles() << " T" << std::endl;
params.m_logger->Log(msg.str().c_str());
}
SimplifyConvexHull(m_convexHulls[i], params.m_maxNumVerticesPerCH, m_volumeCH0 * params.m_minVolumePerCH);
}
m_overallProgress = 100.0;
Update(100.0, 100.0, params);
m_timer.Toc();
if (params.m_logger) {
msg.str("");
msg << "\t time " << m_timer.GetElapsedTime() / 1000.0 << "s" << std::endl;
params.m_logger->Log(msg.str().c_str());
}
}
bool VHACD::ComputeCenterOfMass(double centerOfMass[3]) const
{
bool ret = false;
centerOfMass[0] = 0;
centerOfMass[1] = 0;
centerOfMass[2] = 0;
// Get number of convex hulls in the result
uint32_t hullCount = GetNConvexHulls();
if (hullCount) // if we have results
{
ret = true;
double totalVolume = 0;
// Initialize the center of mass to zero
centerOfMass[0] = 0;
centerOfMass[1] = 0;
centerOfMass[2] = 0;
// Compute the total volume of all convex hulls
for (uint32_t i = 0; i < hullCount; i++)
{
ConvexHull ch;
GetConvexHull(i, ch);
totalVolume += ch.m_volume;
}
// compute the reciprocal of the total volume
double recipVolume = 1.0 / totalVolume;
// Add in the weighted by volume average of the center point of each convex hull
for (uint32_t i = 0; i < hullCount; i++)
{
ConvexHull ch;
GetConvexHull(i, ch);
double ratio = ch.m_volume*recipVolume;
centerOfMass[0] += ch.m_center[0] * ratio;
centerOfMass[1] += ch.m_center[1] * ratio;
centerOfMass[2] += ch.m_center[2] * ratio;
}
}
return ret;
}
} // end of VHACD namespace