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// This file is part of meshoptimizer library; see meshoptimizer.h for version/license details
# include "meshoptimizer.h"
# include <assert.h>
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# include <float.h>
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# include <math.h>
# include <string.h>
// This work is based on:
// Graham Wihlidal. Optimizing the Graphics Pipeline with Compute. 2016
// Matthaeus Chajdas. GeometryFX 1.2 - Cluster Culling. 2016
// Jack Ritter. An Efficient Bounding Sphere. 1990
namespace meshopt
{
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// This must be <= 255 since index 0xff is used internally to indice a vertex that doesn't belong to a meshlet
const size_t kMeshletMaxVertices = 255 ;
// A reasonable limit is around 2*max_vertices or less
const size_t kMeshletMaxTriangles = 512 ;
struct TriangleAdjacency2
{
unsigned int * counts ;
unsigned int * offsets ;
unsigned int * data ;
} ;
static void buildTriangleAdjacency ( TriangleAdjacency2 & adjacency , const unsigned int * indices , size_t index_count , size_t vertex_count , meshopt_Allocator & allocator )
{
size_t face_count = index_count / 3 ;
// allocate arrays
adjacency . counts = allocator . allocate < unsigned int > ( vertex_count ) ;
adjacency . offsets = allocator . allocate < unsigned int > ( vertex_count ) ;
adjacency . data = allocator . allocate < unsigned int > ( index_count ) ;
// fill triangle counts
memset ( adjacency . counts , 0 , vertex_count * sizeof ( unsigned int ) ) ;
for ( size_t i = 0 ; i < index_count ; + + i )
{
assert ( indices [ i ] < vertex_count ) ;
adjacency . counts [ indices [ i ] ] + + ;
}
// fill offset table
unsigned int offset = 0 ;
for ( size_t i = 0 ; i < vertex_count ; + + i )
{
adjacency . offsets [ i ] = offset ;
offset + = adjacency . counts [ i ] ;
}
assert ( offset = = index_count ) ;
// fill triangle data
for ( size_t i = 0 ; i < face_count ; + + i )
{
unsigned int a = indices [ i * 3 + 0 ] , b = indices [ i * 3 + 1 ] , c = indices [ i * 3 + 2 ] ;
adjacency . data [ adjacency . offsets [ a ] + + ] = unsigned ( i ) ;
adjacency . data [ adjacency . offsets [ b ] + + ] = unsigned ( i ) ;
adjacency . data [ adjacency . offsets [ c ] + + ] = unsigned ( i ) ;
}
// fix offsets that have been disturbed by the previous pass
for ( size_t i = 0 ; i < vertex_count ; + + i )
{
assert ( adjacency . offsets [ i ] > = adjacency . counts [ i ] ) ;
adjacency . offsets [ i ] - = adjacency . counts [ i ] ;
}
}
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static void computeBoundingSphere ( float result [ 4 ] , const float points [ ] [ 3 ] , size_t count )
{
assert ( count > 0 ) ;
// find extremum points along all 3 axes; for each axis we get a pair of points with min/max coordinates
size_t pmin [ 3 ] = { 0 , 0 , 0 } ;
size_t pmax [ 3 ] = { 0 , 0 , 0 } ;
for ( size_t i = 0 ; i < count ; + + i )
{
const float * p = points [ i ] ;
for ( int axis = 0 ; axis < 3 ; + + axis )
{
pmin [ axis ] = ( p [ axis ] < points [ pmin [ axis ] ] [ axis ] ) ? i : pmin [ axis ] ;
pmax [ axis ] = ( p [ axis ] > points [ pmax [ axis ] ] [ axis ] ) ? i : pmax [ axis ] ;
}
}
// find the pair of points with largest distance
float paxisd2 = 0 ;
int paxis = 0 ;
for ( int axis = 0 ; axis < 3 ; + + axis )
{
const float * p1 = points [ pmin [ axis ] ] ;
const float * p2 = points [ pmax [ axis ] ] ;
float d2 = ( p2 [ 0 ] - p1 [ 0 ] ) * ( p2 [ 0 ] - p1 [ 0 ] ) + ( p2 [ 1 ] - p1 [ 1 ] ) * ( p2 [ 1 ] - p1 [ 1 ] ) + ( p2 [ 2 ] - p1 [ 2 ] ) * ( p2 [ 2 ] - p1 [ 2 ] ) ;
if ( d2 > paxisd2 )
{
paxisd2 = d2 ;
paxis = axis ;
}
}
// use the longest segment as the initial sphere diameter
const float * p1 = points [ pmin [ paxis ] ] ;
const float * p2 = points [ pmax [ paxis ] ] ;
float center [ 3 ] = { ( p1 [ 0 ] + p2 [ 0 ] ) / 2 , ( p1 [ 1 ] + p2 [ 1 ] ) / 2 , ( p1 [ 2 ] + p2 [ 2 ] ) / 2 } ;
float radius = sqrtf ( paxisd2 ) / 2 ;
// iteratively adjust the sphere up until all points fit
for ( size_t i = 0 ; i < count ; + + i )
{
const float * p = points [ i ] ;
float d2 = ( p [ 0 ] - center [ 0 ] ) * ( p [ 0 ] - center [ 0 ] ) + ( p [ 1 ] - center [ 1 ] ) * ( p [ 1 ] - center [ 1 ] ) + ( p [ 2 ] - center [ 2 ] ) * ( p [ 2 ] - center [ 2 ] ) ;
if ( d2 > radius * radius )
{
float d = sqrtf ( d2 ) ;
assert ( d > 0 ) ;
float k = 0.5f + ( radius / d ) / 2 ;
center [ 0 ] = center [ 0 ] * k + p [ 0 ] * ( 1 - k ) ;
center [ 1 ] = center [ 1 ] * k + p [ 1 ] * ( 1 - k ) ;
center [ 2 ] = center [ 2 ] * k + p [ 2 ] * ( 1 - k ) ;
radius = ( radius + d ) / 2 ;
}
}
result [ 0 ] = center [ 0 ] ;
result [ 1 ] = center [ 1 ] ;
result [ 2 ] = center [ 2 ] ;
result [ 3 ] = radius ;
}
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struct Cone
{
float px , py , pz ;
float nx , ny , nz ;
} ;
static float getMeshletScore ( float distance2 , float spread , float cone_weight , float expected_radius )
{
float cone = 1.f - spread * cone_weight ;
float cone_clamped = cone < 1e-3 f ? 1e-3 f : cone ;
return ( 1 + sqrtf ( distance2 ) / expected_radius * ( 1 - cone_weight ) ) * cone_clamped ;
}
static Cone getMeshletCone ( const Cone & acc , unsigned int triangle_count )
{
Cone result = acc ;
float center_scale = triangle_count = = 0 ? 0.f : 1.f / float ( triangle_count ) ;
result . px * = center_scale ;
result . py * = center_scale ;
result . pz * = center_scale ;
float axis_length = result . nx * result . nx + result . ny * result . ny + result . nz * result . nz ;
float axis_scale = axis_length = = 0.f ? 0.f : 1.f / sqrtf ( axis_length ) ;
result . nx * = axis_scale ;
result . ny * = axis_scale ;
result . nz * = axis_scale ;
return result ;
}
static float computeTriangleCones ( Cone * triangles , const unsigned int * indices , size_t index_count , const float * vertex_positions , size_t vertex_count , size_t vertex_positions_stride )
{
( void ) vertex_count ;
size_t vertex_stride_float = vertex_positions_stride / sizeof ( float ) ;
size_t face_count = index_count / 3 ;
float mesh_area = 0 ;
for ( size_t i = 0 ; i < face_count ; + + i )
{
unsigned int a = indices [ i * 3 + 0 ] , b = indices [ i * 3 + 1 ] , c = indices [ i * 3 + 2 ] ;
assert ( a < vertex_count & & b < vertex_count & & c < vertex_count ) ;
const float * p0 = vertex_positions + vertex_stride_float * a ;
const float * p1 = vertex_positions + vertex_stride_float * b ;
const float * p2 = vertex_positions + vertex_stride_float * c ;
float p10 [ 3 ] = { p1 [ 0 ] - p0 [ 0 ] , p1 [ 1 ] - p0 [ 1 ] , p1 [ 2 ] - p0 [ 2 ] } ;
float p20 [ 3 ] = { p2 [ 0 ] - p0 [ 0 ] , p2 [ 1 ] - p0 [ 1 ] , p2 [ 2 ] - p0 [ 2 ] } ;
float normalx = p10 [ 1 ] * p20 [ 2 ] - p10 [ 2 ] * p20 [ 1 ] ;
float normaly = p10 [ 2 ] * p20 [ 0 ] - p10 [ 0 ] * p20 [ 2 ] ;
float normalz = p10 [ 0 ] * p20 [ 1 ] - p10 [ 1 ] * p20 [ 0 ] ;
float area = sqrtf ( normalx * normalx + normaly * normaly + normalz * normalz ) ;
float invarea = ( area = = 0.f ) ? 0.f : 1.f / area ;
triangles [ i ] . px = ( p0 [ 0 ] + p1 [ 0 ] + p2 [ 0 ] ) / 3.f ;
triangles [ i ] . py = ( p0 [ 1 ] + p1 [ 1 ] + p2 [ 1 ] ) / 3.f ;
triangles [ i ] . pz = ( p0 [ 2 ] + p1 [ 2 ] + p2 [ 2 ] ) / 3.f ;
triangles [ i ] . nx = normalx * invarea ;
triangles [ i ] . ny = normaly * invarea ;
triangles [ i ] . nz = normalz * invarea ;
mesh_area + = area ;
}
return mesh_area ;
}
static void finishMeshlet ( meshopt_Meshlet & meshlet , unsigned char * meshlet_triangles )
{
size_t offset = meshlet . triangle_offset + meshlet . triangle_count * 3 ;
// fill 4b padding with 0
while ( offset & 3 )
meshlet_triangles [ offset + + ] = 0 ;
}
static bool appendMeshlet ( meshopt_Meshlet & meshlet , unsigned int a , unsigned int b , unsigned int c , unsigned char * used , meshopt_Meshlet * meshlets , unsigned int * meshlet_vertices , unsigned char * meshlet_triangles , size_t meshlet_offset , size_t max_vertices , size_t max_triangles )
{
unsigned char & av = used [ a ] ;
unsigned char & bv = used [ b ] ;
unsigned char & cv = used [ c ] ;
bool result = false ;
unsigned int used_extra = ( av = = 0xff ) + ( bv = = 0xff ) + ( cv = = 0xff ) ;
if ( meshlet . vertex_count + used_extra > max_vertices | | meshlet . triangle_count > = max_triangles )
{
meshlets [ meshlet_offset ] = meshlet ;
for ( size_t j = 0 ; j < meshlet . vertex_count ; + + j )
used [ meshlet_vertices [ meshlet . vertex_offset + j ] ] = 0xff ;
finishMeshlet ( meshlet , meshlet_triangles ) ;
meshlet . vertex_offset + = meshlet . vertex_count ;
meshlet . triangle_offset + = ( meshlet . triangle_count * 3 + 3 ) & ~ 3 ; // 4b padding
meshlet . vertex_count = 0 ;
meshlet . triangle_count = 0 ;
result = true ;
}
if ( av = = 0xff )
{
av = ( unsigned char ) meshlet . vertex_count ;
meshlet_vertices [ meshlet . vertex_offset + meshlet . vertex_count + + ] = a ;
}
if ( bv = = 0xff )
{
bv = ( unsigned char ) meshlet . vertex_count ;
meshlet_vertices [ meshlet . vertex_offset + meshlet . vertex_count + + ] = b ;
}
if ( cv = = 0xff )
{
cv = ( unsigned char ) meshlet . vertex_count ;
meshlet_vertices [ meshlet . vertex_offset + meshlet . vertex_count + + ] = c ;
}
meshlet_triangles [ meshlet . triangle_offset + meshlet . triangle_count * 3 + 0 ] = av ;
meshlet_triangles [ meshlet . triangle_offset + meshlet . triangle_count * 3 + 1 ] = bv ;
meshlet_triangles [ meshlet . triangle_offset + meshlet . triangle_count * 3 + 2 ] = cv ;
meshlet . triangle_count + + ;
return result ;
}
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static unsigned int getNeighborTriangle ( const meshopt_Meshlet & meshlet , const Cone * meshlet_cone , unsigned int * meshlet_vertices , const unsigned int * indices , const TriangleAdjacency2 & adjacency , const Cone * triangles , const unsigned int * live_triangles , const unsigned char * used , float meshlet_expected_radius , float cone_weight , unsigned int * out_extra )
{
unsigned int best_triangle = ~ 0u ;
unsigned int best_extra = 5 ;
float best_score = FLT_MAX ;
for ( size_t i = 0 ; i < meshlet . vertex_count ; + + i )
{
unsigned int index = meshlet_vertices [ meshlet . vertex_offset + i ] ;
unsigned int * neighbors = & adjacency . data [ 0 ] + adjacency . offsets [ index ] ;
size_t neighbors_size = adjacency . counts [ index ] ;
for ( size_t j = 0 ; j < neighbors_size ; + + j )
{
unsigned int triangle = neighbors [ j ] ;
unsigned int a = indices [ triangle * 3 + 0 ] , b = indices [ triangle * 3 + 1 ] , c = indices [ triangle * 3 + 2 ] ;
unsigned int extra = ( used [ a ] = = 0xff ) + ( used [ b ] = = 0xff ) + ( used [ c ] = = 0xff ) ;
// triangles that don't add new vertices to meshlets are max. priority
if ( extra ! = 0 )
{
// artificially increase the priority of dangling triangles as they're expensive to add to new meshlets
if ( live_triangles [ a ] = = 1 | | live_triangles [ b ] = = 1 | | live_triangles [ c ] = = 1 )
extra = 0 ;
extra + + ;
}
// since topology-based priority is always more important than the score, we can skip scoring in some cases
if ( extra > best_extra )
continue ;
float score = 0 ;
// caller selects one of two scoring functions: geometrical (based on meshlet cone) or topological (based on remaining triangles)
if ( meshlet_cone )
{
const Cone & tri_cone = triangles [ triangle ] ;
float distance2 =
( tri_cone . px - meshlet_cone - > px ) * ( tri_cone . px - meshlet_cone - > px ) +
( tri_cone . py - meshlet_cone - > py ) * ( tri_cone . py - meshlet_cone - > py ) +
( tri_cone . pz - meshlet_cone - > pz ) * ( tri_cone . pz - meshlet_cone - > pz ) ;
float spread = tri_cone . nx * meshlet_cone - > nx + tri_cone . ny * meshlet_cone - > ny + tri_cone . nz * meshlet_cone - > nz ;
score = getMeshletScore ( distance2 , spread , cone_weight , meshlet_expected_radius ) ;
}
else
{
// each live_triangles entry is >= 1 since it includes the current triangle we're processing
score = float ( live_triangles [ a ] + live_triangles [ b ] + live_triangles [ c ] - 3 ) ;
}
// note that topology-based priority is always more important than the score
// this helps maintain reasonable effectiveness of meshlet data and reduces scoring cost
if ( extra < best_extra | | score < best_score )
{
best_triangle = triangle ;
best_extra = extra ;
best_score = score ;
}
}
}
if ( out_extra )
* out_extra = best_extra ;
return best_triangle ;
}
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struct KDNode
{
union
{
float split ;
unsigned int index ;
} ;
// leaves: axis = 3, children = number of extra points after this one (0 if 'index' is the only point)
// branches: axis != 3, left subtree = skip 1, right subtree = skip 1+children
unsigned int axis : 2 ;
unsigned int children : 30 ;
} ;
static size_t kdtreePartition ( unsigned int * indices , size_t count , const float * points , size_t stride , unsigned int axis , float pivot )
{
size_t m = 0 ;
// invariant: elements in range [0, m) are < pivot, elements in range [m, i) are >= pivot
for ( size_t i = 0 ; i < count ; + + i )
{
float v = points [ indices [ i ] * stride + axis ] ;
// swap(m, i) unconditionally
unsigned int t = indices [ m ] ;
indices [ m ] = indices [ i ] ;
indices [ i ] = t ;
// when v >= pivot, we swap i with m without advancing it, preserving invariants
m + = v < pivot ;
}
return m ;
}
static size_t kdtreeBuildLeaf ( size_t offset , KDNode * nodes , size_t node_count , unsigned int * indices , size_t count )
{
assert ( offset + count < = node_count ) ;
( void ) node_count ;
KDNode & result = nodes [ offset ] ;
result . index = indices [ 0 ] ;
result . axis = 3 ;
result . children = unsigned ( count - 1 ) ;
// all remaining points are stored in nodes immediately following the leaf
for ( size_t i = 1 ; i < count ; + + i )
{
KDNode & tail = nodes [ offset + i ] ;
tail . index = indices [ i ] ;
tail . axis = 3 ;
tail . children = ~ 0u > > 2 ; // bogus value to prevent misuse
}
return offset + count ;
}
static size_t kdtreeBuild ( size_t offset , KDNode * nodes , size_t node_count , const float * points , size_t stride , unsigned int * indices , size_t count , size_t leaf_size )
{
assert ( count > 0 ) ;
assert ( offset < node_count ) ;
if ( count < = leaf_size )
return kdtreeBuildLeaf ( offset , nodes , node_count , indices , count ) ;
float mean [ 3 ] = { } ;
float vars [ 3 ] = { } ;
float runc = 1 , runs = 1 ;
// gather statistics on the points in the subtree using Welford's algorithm
for ( size_t i = 0 ; i < count ; + + i , runc + = 1.f , runs = 1.f / runc )
{
const float * point = points + indices [ i ] * stride ;
for ( int k = 0 ; k < 3 ; + + k )
{
float delta = point [ k ] - mean [ k ] ;
mean [ k ] + = delta * runs ;
vars [ k ] + = delta * ( point [ k ] - mean [ k ] ) ;
}
}
// split axis is one where the variance is largest
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unsigned int axis = vars [ 0 ] > = vars [ 1 ] & & vars [ 0 ] > = vars [ 2 ] ? 0 : vars [ 1 ] > = vars [ 2 ] ? 1 : 2 ;
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float split = mean [ axis ] ;
size_t middle = kdtreePartition ( indices , count , points , stride , axis , split ) ;
// when the partition is degenerate simply consolidate the points into a single node
if ( middle < = leaf_size / 2 | | middle > = count - leaf_size / 2 )
return kdtreeBuildLeaf ( offset , nodes , node_count , indices , count ) ;
KDNode & result = nodes [ offset ] ;
result . split = split ;
result . axis = axis ;
// left subtree is right after our node
size_t next_offset = kdtreeBuild ( offset + 1 , nodes , node_count , points , stride , indices , middle , leaf_size ) ;
// distance to the right subtree is represented explicitly
result . children = unsigned ( next_offset - offset - 1 ) ;
return kdtreeBuild ( next_offset , nodes , node_count , points , stride , indices + middle , count - middle , leaf_size ) ;
}
static void kdtreeNearest ( KDNode * nodes , unsigned int root , const float * points , size_t stride , const unsigned char * emitted_flags , const float * position , unsigned int & result , float & limit )
{
const KDNode & node = nodes [ root ] ;
if ( node . axis = = 3 )
{
// leaf
for ( unsigned int i = 0 ; i < = node . children ; + + i )
{
unsigned int index = nodes [ root + i ] . index ;
if ( emitted_flags [ index ] )
continue ;
const float * point = points + index * stride ;
float distance2 =
( point [ 0 ] - position [ 0 ] ) * ( point [ 0 ] - position [ 0 ] ) +
( point [ 1 ] - position [ 1 ] ) * ( point [ 1 ] - position [ 1 ] ) +
( point [ 2 ] - position [ 2 ] ) * ( point [ 2 ] - position [ 2 ] ) ;
float distance = sqrtf ( distance2 ) ;
if ( distance < limit )
{
result = index ;
limit = distance ;
}
}
}
else
{
// branch; we order recursion to process the node that search position is in first
float delta = position [ node . axis ] - node . split ;
unsigned int first = ( delta < = 0 ) ? 0 : node . children ;
unsigned int second = first ^ node . children ;
kdtreeNearest ( nodes , root + 1 + first , points , stride , emitted_flags , position , result , limit ) ;
// only process the other node if it can have a match based on closest distance so far
if ( fabsf ( delta ) < = limit )
kdtreeNearest ( nodes , root + 1 + second , points , stride , emitted_flags , position , result , limit ) ;
}
}
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} // namespace meshopt
size_t meshopt_buildMeshletsBound ( size_t index_count , size_t max_vertices , size_t max_triangles )
{
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using namespace meshopt ;
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assert ( index_count % 3 = = 0 ) ;
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assert ( max_vertices > = 3 & & max_vertices < = kMeshletMaxVertices ) ;
assert ( max_triangles > = 1 & & max_triangles < = kMeshletMaxTriangles ) ;
assert ( max_triangles % 4 = = 0 ) ; // ensures the caller will compute output space properly as index data is 4b aligned
( void ) kMeshletMaxVertices ;
( void ) kMeshletMaxTriangles ;
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// meshlet construction is limited by max vertices and max triangles per meshlet
// the worst case is that the input is an unindexed stream since this equally stresses both limits
// note that we assume that in the worst case, we leave 2 vertices unpacked in each meshlet - if we have space for 3 we can pack any triangle
size_t max_vertices_conservative = max_vertices - 2 ;
size_t meshlet_limit_vertices = ( index_count + max_vertices_conservative - 1 ) / max_vertices_conservative ;
size_t meshlet_limit_triangles = ( index_count / 3 + max_triangles - 1 ) / max_triangles ;
return meshlet_limit_vertices > meshlet_limit_triangles ? meshlet_limit_vertices : meshlet_limit_triangles ;
}
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size_t meshopt_buildMeshlets ( meshopt_Meshlet * meshlets , unsigned int * meshlet_vertices , unsigned char * meshlet_triangles , const unsigned int * indices , size_t index_count , const float * vertex_positions , size_t vertex_count , size_t vertex_positions_stride , size_t max_vertices , size_t max_triangles , float cone_weight )
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{
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using namespace meshopt ;
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assert ( index_count % 3 = = 0 ) ;
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assert ( vertex_positions_stride > = 12 & & vertex_positions_stride < = 256 ) ;
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assert ( vertex_positions_stride % sizeof ( float ) = = 0 ) ;
assert ( max_vertices > = 3 & & max_vertices < = kMeshletMaxVertices ) ;
assert ( max_triangles > = 1 & & max_triangles < = kMeshletMaxTriangles ) ;
assert ( max_triangles % 4 = = 0 ) ; // ensures the caller will compute output space properly as index data is 4b aligned
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assert ( cone_weight > = 0 & & cone_weight < = 1 ) ;
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meshopt_Allocator allocator ;
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TriangleAdjacency2 adjacency = { } ;
buildTriangleAdjacency ( adjacency , indices , index_count , vertex_count , allocator ) ;
unsigned int * live_triangles = allocator . allocate < unsigned int > ( vertex_count ) ;
memcpy ( live_triangles , adjacency . counts , vertex_count * sizeof ( unsigned int ) ) ;
size_t face_count = index_count / 3 ;
unsigned char * emitted_flags = allocator . allocate < unsigned char > ( face_count ) ;
memset ( emitted_flags , 0 , face_count ) ;
// for each triangle, precompute centroid & normal to use for scoring
Cone * triangles = allocator . allocate < Cone > ( face_count ) ;
float mesh_area = computeTriangleCones ( triangles , indices , index_count , vertex_positions , vertex_count , vertex_positions_stride ) ;
// assuming each meshlet is a square patch, expected radius is sqrt(expected area)
float triangle_area_avg = face_count = = 0 ? 0.f : mesh_area / float ( face_count ) * 0.5f ;
float meshlet_expected_radius = sqrtf ( triangle_area_avg * max_triangles ) * 0.5f ;
// build a kd-tree for nearest neighbor lookup
unsigned int * kdindices = allocator . allocate < unsigned int > ( face_count ) ;
for ( size_t i = 0 ; i < face_count ; + + i )
kdindices [ i ] = unsigned ( i ) ;
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KDNode * nodes = allocator . allocate < KDNode > ( face_count * 2 ) ;
kdtreeBuild ( 0 , nodes , face_count * 2 , & triangles [ 0 ] . px , sizeof ( Cone ) / sizeof ( float ) , kdindices , face_count , /* leaf_size= */ 8 ) ;
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// index of the vertex in the meshlet, 0xff if the vertex isn't used
unsigned char * used = allocator . allocate < unsigned char > ( vertex_count ) ;
memset ( used , - 1 , vertex_count ) ;
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meshopt_Meshlet meshlet = { } ;
size_t meshlet_offset = 0 ;
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Cone meshlet_cone_acc = { } ;
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for ( ; ; )
{
Cone meshlet_cone = getMeshletCone ( meshlet_cone_acc , meshlet . triangle_count ) ;
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unsigned int best_extra = 0 ;
unsigned int best_triangle = getNeighborTriangle ( meshlet , & meshlet_cone , meshlet_vertices , indices , adjacency , triangles , live_triangles , used , meshlet_expected_radius , cone_weight , & best_extra ) ;
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// if the best triangle doesn't fit into current meshlet, the spatial scoring we've used is not very meaningful, so we re-select using topological scoring
if ( best_triangle ! = ~ 0u & & ( meshlet . vertex_count + best_extra > max_vertices | | meshlet . triangle_count > = max_triangles ) )
{
best_triangle = getNeighborTriangle ( meshlet , NULL , meshlet_vertices , indices , adjacency , triangles , live_triangles , used , meshlet_expected_radius , 0.f , NULL ) ;
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}
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// when we run out of neighboring triangles we need to switch to spatial search; we currently just pick the closest triangle irrespective of connectivity
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if ( best_triangle = = ~ 0u )
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{
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float position [ 3 ] = { meshlet_cone . px , meshlet_cone . py , meshlet_cone . pz } ;
unsigned int index = ~ 0u ;
float limit = FLT_MAX ;
kdtreeNearest ( nodes , 0 , & triangles [ 0 ] . px , sizeof ( Cone ) / sizeof ( float ) , emitted_flags , position , index , limit ) ;
best_triangle = index ;
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}
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if ( best_triangle = = ~ 0u )
break ;
unsigned int a = indices [ best_triangle * 3 + 0 ] , b = indices [ best_triangle * 3 + 1 ] , c = indices [ best_triangle * 3 + 2 ] ;
assert ( a < vertex_count & & b < vertex_count & & c < vertex_count ) ;
// add meshlet to the output; when the current meshlet is full we reset the accumulated bounds
if ( appendMeshlet ( meshlet , a , b , c , used , meshlets , meshlet_vertices , meshlet_triangles , meshlet_offset , max_vertices , max_triangles ) )
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{
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meshlet_offset + + ;
memset ( & meshlet_cone_acc , 0 , sizeof ( meshlet_cone_acc ) ) ;
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}
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live_triangles [ a ] - - ;
live_triangles [ b ] - - ;
live_triangles [ c ] - - ;
// remove emitted triangle from adjacency data
// this makes sure that we spend less time traversing these lists on subsequent iterations
for ( size_t k = 0 ; k < 3 ; + + k )
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{
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unsigned int index = indices [ best_triangle * 3 + k ] ;
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unsigned int * neighbors = & adjacency . data [ 0 ] + adjacency . offsets [ index ] ;
size_t neighbors_size = adjacency . counts [ index ] ;
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for ( size_t i = 0 ; i < neighbors_size ; + + i )
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{
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unsigned int tri = neighbors [ i ] ;
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if ( tri = = best_triangle )
{
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neighbors [ i ] = neighbors [ neighbors_size - 1 ] ;
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adjacency . counts [ index ] - - ;
break ;
}
}
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}
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// update aggregated meshlet cone data for scoring subsequent triangles
meshlet_cone_acc . px + = triangles [ best_triangle ] . px ;
meshlet_cone_acc . py + = triangles [ best_triangle ] . py ;
meshlet_cone_acc . pz + = triangles [ best_triangle ] . pz ;
meshlet_cone_acc . nx + = triangles [ best_triangle ] . nx ;
meshlet_cone_acc . ny + = triangles [ best_triangle ] . ny ;
meshlet_cone_acc . nz + = triangles [ best_triangle ] . nz ;
emitted_flags [ best_triangle ] = 1 ;
}
if ( meshlet . triangle_count )
{
finishMeshlet ( meshlet , meshlet_triangles ) ;
meshlets [ meshlet_offset + + ] = meshlet ;
}
assert ( meshlet_offset < = meshopt_buildMeshletsBound ( index_count , max_vertices , max_triangles ) ) ;
return meshlet_offset ;
}
size_t meshopt_buildMeshletsScan ( meshopt_Meshlet * meshlets , unsigned int * meshlet_vertices , unsigned char * meshlet_triangles , const unsigned int * indices , size_t index_count , size_t vertex_count , size_t max_vertices , size_t max_triangles )
{
using namespace meshopt ;
assert ( index_count % 3 = = 0 ) ;
assert ( max_vertices > = 3 & & max_vertices < = kMeshletMaxVertices ) ;
assert ( max_triangles > = 1 & & max_triangles < = kMeshletMaxTriangles ) ;
assert ( max_triangles % 4 = = 0 ) ; // ensures the caller will compute output space properly as index data is 4b aligned
meshopt_Allocator allocator ;
// index of the vertex in the meshlet, 0xff if the vertex isn't used
unsigned char * used = allocator . allocate < unsigned char > ( vertex_count ) ;
memset ( used , - 1 , vertex_count ) ;
meshopt_Meshlet meshlet = { } ;
size_t meshlet_offset = 0 ;
for ( size_t i = 0 ; i < index_count ; i + = 3 )
{
unsigned int a = indices [ i + 0 ] , b = indices [ i + 1 ] , c = indices [ i + 2 ] ;
assert ( a < vertex_count & & b < vertex_count & & c < vertex_count ) ;
// appends triangle to the meshlet and writes previous meshlet to the output if full
meshlet_offset + = appendMeshlet ( meshlet , a , b , c , used , meshlets , meshlet_vertices , meshlet_triangles , meshlet_offset , max_vertices , max_triangles ) ;
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}
if ( meshlet . triangle_count )
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{
finishMeshlet ( meshlet , meshlet_triangles ) ;
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meshlets [ meshlet_offset + + ] = meshlet ;
}
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assert ( meshlet_offset < = meshopt_buildMeshletsBound ( index_count , max_vertices , max_triangles ) ) ;
return meshlet_offset ;
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}
meshopt_Bounds meshopt_computeClusterBounds ( const unsigned int * indices , size_t index_count , const float * vertex_positions , size_t vertex_count , size_t vertex_positions_stride )
{
using namespace meshopt ;
assert ( index_count % 3 = = 0 ) ;
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assert ( index_count / 3 < = kMeshletMaxTriangles ) ;
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assert ( vertex_positions_stride > = 12 & & vertex_positions_stride < = 256 ) ;
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assert ( vertex_positions_stride % sizeof ( float ) = = 0 ) ;
( void ) vertex_count ;
size_t vertex_stride_float = vertex_positions_stride / sizeof ( float ) ;
// compute triangle normals and gather triangle corners
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float normals [ kMeshletMaxTriangles ] [ 3 ] ;
float corners [ kMeshletMaxTriangles ] [ 3 ] [ 3 ] ;
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size_t triangles = 0 ;
for ( size_t i = 0 ; i < index_count ; i + = 3 )
{
unsigned int a = indices [ i + 0 ] , b = indices [ i + 1 ] , c = indices [ i + 2 ] ;
assert ( a < vertex_count & & b < vertex_count & & c < vertex_count ) ;
const float * p0 = vertex_positions + vertex_stride_float * a ;
const float * p1 = vertex_positions + vertex_stride_float * b ;
const float * p2 = vertex_positions + vertex_stride_float * c ;
float p10 [ 3 ] = { p1 [ 0 ] - p0 [ 0 ] , p1 [ 1 ] - p0 [ 1 ] , p1 [ 2 ] - p0 [ 2 ] } ;
float p20 [ 3 ] = { p2 [ 0 ] - p0 [ 0 ] , p2 [ 1 ] - p0 [ 1 ] , p2 [ 2 ] - p0 [ 2 ] } ;
float normalx = p10 [ 1 ] * p20 [ 2 ] - p10 [ 2 ] * p20 [ 1 ] ;
float normaly = p10 [ 2 ] * p20 [ 0 ] - p10 [ 0 ] * p20 [ 2 ] ;
float normalz = p10 [ 0 ] * p20 [ 1 ] - p10 [ 1 ] * p20 [ 0 ] ;
float area = sqrtf ( normalx * normalx + normaly * normaly + normalz * normalz ) ;
// no need to include degenerate triangles - they will be invisible anyway
if ( area = = 0.f )
continue ;
// record triangle normals & corners for future use; normal and corner 0 define a plane equation
normals [ triangles ] [ 0 ] = normalx / area ;
normals [ triangles ] [ 1 ] = normaly / area ;
normals [ triangles ] [ 2 ] = normalz / area ;
memcpy ( corners [ triangles ] [ 0 ] , p0 , 3 * sizeof ( float ) ) ;
memcpy ( corners [ triangles ] [ 1 ] , p1 , 3 * sizeof ( float ) ) ;
memcpy ( corners [ triangles ] [ 2 ] , p2 , 3 * sizeof ( float ) ) ;
triangles + + ;
}
meshopt_Bounds bounds = { } ;
// degenerate cluster, no valid triangles => trivial reject (cone data is 0)
if ( triangles = = 0 )
return bounds ;
// compute cluster bounding sphere; we'll use the center to determine normal cone apex as well
float psphere [ 4 ] = { } ;
computeBoundingSphere ( psphere , corners [ 0 ] , triangles * 3 ) ;
float center [ 3 ] = { psphere [ 0 ] , psphere [ 1 ] , psphere [ 2 ] } ;
// treating triangle normals as points, find the bounding sphere - the sphere center determines the optimal cone axis
float nsphere [ 4 ] = { } ;
computeBoundingSphere ( nsphere , normals , triangles ) ;
float axis [ 3 ] = { nsphere [ 0 ] , nsphere [ 1 ] , nsphere [ 2 ] } ;
float axislength = sqrtf ( axis [ 0 ] * axis [ 0 ] + axis [ 1 ] * axis [ 1 ] + axis [ 2 ] * axis [ 2 ] ) ;
float invaxislength = axislength = = 0.f ? 0.f : 1.f / axislength ;
axis [ 0 ] * = invaxislength ;
axis [ 1 ] * = invaxislength ;
axis [ 2 ] * = invaxislength ;
// compute a tight cone around all normals, mindp = cos(angle/2)
float mindp = 1.f ;
for ( size_t i = 0 ; i < triangles ; + + i )
{
float dp = normals [ i ] [ 0 ] * axis [ 0 ] + normals [ i ] [ 1 ] * axis [ 1 ] + normals [ i ] [ 2 ] * axis [ 2 ] ;
mindp = ( dp < mindp ) ? dp : mindp ;
}
// fill bounding sphere info; note that below we can return bounds without cone information for degenerate cones
bounds . center [ 0 ] = center [ 0 ] ;
bounds . center [ 1 ] = center [ 1 ] ;
bounds . center [ 2 ] = center [ 2 ] ;
bounds . radius = psphere [ 3 ] ;
// degenerate cluster, normal cone is larger than a hemisphere => trivial accept
// note that if mindp is positive but close to 0, the triangle intersection code below gets less stable
// we arbitrarily decide that if a normal cone is ~168 degrees wide or more, the cone isn't useful
if ( mindp < = 0.1f )
{
bounds . cone_cutoff = 1 ;
bounds . cone_cutoff_s8 = 127 ;
return bounds ;
}
float maxt = 0 ;
// we need to find the point on center-t*axis ray that lies in negative half-space of all triangles
for ( size_t i = 0 ; i < triangles ; + + i )
{
// dot(center-t*axis-corner, trinormal) = 0
// dot(center-corner, trinormal) - t * dot(axis, trinormal) = 0
float cx = center [ 0 ] - corners [ i ] [ 0 ] [ 0 ] ;
float cy = center [ 1 ] - corners [ i ] [ 0 ] [ 1 ] ;
float cz = center [ 2 ] - corners [ i ] [ 0 ] [ 2 ] ;
float dc = cx * normals [ i ] [ 0 ] + cy * normals [ i ] [ 1 ] + cz * normals [ i ] [ 2 ] ;
float dn = axis [ 0 ] * normals [ i ] [ 0 ] + axis [ 1 ] * normals [ i ] [ 1 ] + axis [ 2 ] * normals [ i ] [ 2 ] ;
// dn should be larger than mindp cutoff above
assert ( dn > 0.f ) ;
float t = dc / dn ;
maxt = ( t > maxt ) ? t : maxt ;
}
// cone apex should be in the negative half-space of all cluster triangles by construction
bounds . cone_apex [ 0 ] = center [ 0 ] - axis [ 0 ] * maxt ;
bounds . cone_apex [ 1 ] = center [ 1 ] - axis [ 1 ] * maxt ;
bounds . cone_apex [ 2 ] = center [ 2 ] - axis [ 2 ] * maxt ;
// note: this axis is the axis of the normal cone, but our test for perspective camera effectively negates the axis
bounds . cone_axis [ 0 ] = axis [ 0 ] ;
bounds . cone_axis [ 1 ] = axis [ 1 ] ;
bounds . cone_axis [ 2 ] = axis [ 2 ] ;
// cos(a) for normal cone is mindp; we need to add 90 degrees on both sides and invert the cone
// which gives us -cos(a+90) = -(-sin(a)) = sin(a) = sqrt(1 - cos^2(a))
bounds . cone_cutoff = sqrtf ( 1 - mindp * mindp ) ;
// quantize axis & cutoff to 8-bit SNORM format
bounds . cone_axis_s8 [ 0 ] = ( signed char ) ( meshopt_quantizeSnorm ( bounds . cone_axis [ 0 ] , 8 ) ) ;
bounds . cone_axis_s8 [ 1 ] = ( signed char ) ( meshopt_quantizeSnorm ( bounds . cone_axis [ 1 ] , 8 ) ) ;
bounds . cone_axis_s8 [ 2 ] = ( signed char ) ( meshopt_quantizeSnorm ( bounds . cone_axis [ 2 ] , 8 ) ) ;
// for the 8-bit test to be conservative, we need to adjust the cutoff by measuring the max. error
float cone_axis_s8_e0 = fabsf ( bounds . cone_axis_s8 [ 0 ] / 127.f - bounds . cone_axis [ 0 ] ) ;
float cone_axis_s8_e1 = fabsf ( bounds . cone_axis_s8 [ 1 ] / 127.f - bounds . cone_axis [ 1 ] ) ;
float cone_axis_s8_e2 = fabsf ( bounds . cone_axis_s8 [ 2 ] / 127.f - bounds . cone_axis [ 2 ] ) ;
// note that we need to round this up instead of rounding to nearest, hence +1
int cone_cutoff_s8 = int ( 127 * ( bounds . cone_cutoff + cone_axis_s8_e0 + cone_axis_s8_e1 + cone_axis_s8_e2 ) + 1 ) ;
bounds . cone_cutoff_s8 = ( cone_cutoff_s8 > 127 ) ? 127 : ( signed char ) ( cone_cutoff_s8 ) ;
return bounds ;
}
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meshopt_Bounds meshopt_computeMeshletBounds ( const unsigned int * meshlet_vertices , const unsigned char * meshlet_triangles , size_t triangle_count , const float * vertex_positions , size_t vertex_count , size_t vertex_positions_stride )
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{
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using namespace meshopt ;
assert ( triangle_count < = kMeshletMaxTriangles ) ;
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assert ( vertex_positions_stride > = 12 & & vertex_positions_stride < = 256 ) ;
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assert ( vertex_positions_stride % sizeof ( float ) = = 0 ) ;
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unsigned int indices [ kMeshletMaxTriangles * 3 ] ;
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for ( size_t i = 0 ; i < triangle_count * 3 ; + + i )
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{
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unsigned int index = meshlet_vertices [ meshlet_triangles [ i ] ] ;
assert ( index < vertex_count ) ;
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indices [ i ] = index ;
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}
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return meshopt_computeClusterBounds ( indices , triangle_count * 3 , vertex_positions , vertex_count , vertex_positions_stride ) ;
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}