// Merge these input hulls.
virtual hacd::HaU32 mergeHulls(const MergeHullVector &inputHulls,
MergeHullVector &outputHulls,
hacd::HaU32 mergeHullCount,
hacd::HaF32 smallClusterThreshold,
hacd::HaU32 maxHullVertices)
{
mGuid = 0;
HaU32 count = (HaU32)inputHulls.size();
mHasBeenTested = HACD_NEW(TestedMap)(count*count);
mSmallClusterThreshold = smallClusterThreshold;
mMaxHullVertices = maxHullVertices;
mMergeNumHulls = mergeHullCount;
mTotalVolume = 0;
for (HaU32 i=0; i<inputHulls.size(); i++)
{
const MergeHull &h = inputHulls[i];
ChUll *ch = HACD_NEW(ChUll)(h.mVertexCount,h.mVertices,h.mTriangleCount,h.mIndices,mGuid++);
mChulls.push_back(ch);
mTotalVolume+=ch->mVolume;
}
for(;;)
{
bool combined = combineHulls(); // mege smallest hulls first, up to the max merge count.
if ( !combined ) break;
}
// return results..
for (HaU32 i=0; i<mChulls.size(); i++)
{
ChUll *ch = mChulls[i];
MergeHull mh;
mh.mVertexCount = ch->mVertexCount;
mh.mTriangleCount = ch->mTriangleCount;
mh.mIndices = ch->mIndices;
mh.mVertices = ch->mVertices;
outputHulls.push_back(mh);
}
delete mHasBeenTested;
return (HaU32)outputHulls.size();
}
unsigned int ConvexBuilder::process(const DecompDesc &desc)
{
unsigned int ret = 0;
MAXDEPTH = desc.mDepth;
CONCAVE_PERCENT = desc.mCpercent;
MERGE_PERCENT = desc.mPpercent;
calcConvexDecomposition(desc.mVcount, desc.mVertices, desc.mTcount, desc.mIndices,this,0,0);
while ( combineHulls() ); // keep combinging hulls until I can't combine any more...
int i;
for (i=0;i<mChulls.size();i++)
{
CHull *cr = mChulls[i];
// before we hand it back to the application, we need to regenerate the hull based on the
// limits given by the user.
const ConvexResult &c = *cr->mResult; // the high resolution hull...
HullResult result;
HullLibrary hl;
HullDesc hdesc;
hdesc.SetHullFlag(QF_TRIANGLES);
hdesc.mVcount = c.mHullVcount;
hdesc.mVertices = c.mHullVertices;
hdesc.mVertexStride = sizeof(float)*3;
hdesc.mMaxVertices = desc.mMaxVertices; // maximum number of vertices allowed in the output
if ( desc.mSkinWidth )
{
hdesc.mSkinWidth = desc.mSkinWidth;
hdesc.SetHullFlag(QF_SKIN_WIDTH); // do skin width computation.
}
HullError ret = hl.CreateConvexHull(hdesc,result);
if ( ret == QE_OK )
{
ConvexResult r(result.mNumOutputVertices, result.mOutputVertices, result.mNumFaces, result.mIndices);
r.mHullVolume = computeMeshVolume( result.mOutputVertices, result.mNumFaces, result.mIndices ); // the volume of the hull.
// compute the best fit OBB
computeBestFitOBB( result.mNumOutputVertices, result.mOutputVertices, sizeof(float)*3, r.mOBBSides, r.mOBBTransform );
r.mOBBVolume = r.mOBBSides[0] * r.mOBBSides[1] *r.mOBBSides[2]; // compute the OBB volume.
fm_getTranslation( r.mOBBTransform, r.mOBBCenter ); // get the translation component of the 4x4 matrix.
fm_matrixToQuat( r.mOBBTransform, r.mOBBOrientation ); // extract the orientation as a quaternion.
r.mSphereRadius = computeBoundingSphere( result.mNumOutputVertices, result.mOutputVertices, r.mSphereCenter );
r.mSphereVolume = fm_sphereVolume( r.mSphereRadius );
mCallback->ConvexDecompResult(r);
}
hl.ReleaseResult (result);
delete cr;
}
ret = mChulls.size();
mChulls.clear();
return ret;
}
// Merge these input hulls.
virtual hacd::HaU32 mergeHulls(const MergeHullVector &inputHulls,
MergeHullVector &outputHulls,
hacd::HaU32 mergeHullCount,
hacd::HaF32 smallClusterThreshold,
hacd::HaU32 maxHullVertices,
hacd::ICallback *callback,
JOB_SWARM_STANDALONE::JobSwarmContext *jobSwarmContext)
{
mGuid = 0;
HaU32 count = (HaU32)inputHulls.size();
mHasBeenTested = HACD_NEW(TestedMap)(count*count);
mSmallClusterThreshold = smallClusterThreshold;
mMaxHullVertices = maxHullVertices;
mMergeNumHulls = mergeHullCount;
mTotalVolume = 0;
for (HaU32 i=0; i<inputHulls.size(); i++)
{
const MergeHull &h = inputHulls[i];
CHull *ch = HACD_NEW(CHull)(h.mVertexCount,h.mVertices,h.mTriangleCount,h.mIndices,mGuid++);
mChulls.push_back(ch);
mTotalVolume+=ch->mVolume;
if ( callback )
{
HaF32 fraction = (HaF32)i / (HaF32)inputHulls.size();
callback->ReportProgress("Gathering Hulls To Merge", fraction );
}
}
//
hacd::HaU32 mergeCount = count - mergeHullCount;
hacd::HaU32 mergeIndex = 0;
for(;;)
{
if ( callback )
{
hacd::HaF32 fraction = (hacd::HaF32)mergeIndex / (hacd::HaF32)mergeCount;
callback->ReportProgress("Merging", fraction );
}
bool combined = combineHulls(jobSwarmContext); // mege smallest hulls first, up to the max merge count.
if ( !combined ) break;
mergeIndex++;
}
// return results..
for (HaU32 i=0; i<mChulls.size(); i++)
{
CHull *ch = mChulls[i];
MergeHull mh;
mh.mVertexCount = ch->mVertexCount;
mh.mTriangleCount = ch->mTriangleCount;
mh.mIndices = ch->mIndices;
mh.mVertices = ch->mVertices;
outputHulls.push_back(mh);
if ( callback )
{
HaF32 fraction = (HaF32)i / (HaF32)mChulls.size();
callback->ReportProgress("Gathering Merged Hulls Output", fraction );
}
}
delete mHasBeenTested;
return (HaU32)outputHulls.size();
}
