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885 lines
30 KiB
C++
885 lines
30 KiB
C++
// This file is part of meshoptimizer library; see meshoptimizer.h for version/license details
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#include "meshoptimizer.h"
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#include <assert.h>
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#include <float.h>
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#include <math.h>
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#include <string.h>
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// This work is based on:
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// Graham Wihlidal. Optimizing the Graphics Pipeline with Compute. 2016
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// Matthaeus Chajdas. GeometryFX 1.2 - Cluster Culling. 2016
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// Jack Ritter. An Efficient Bounding Sphere. 1990
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namespace meshopt
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{
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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
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const size_t kMeshletMaxVertices = 255;
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// A reasonable limit is around 2*max_vertices or less
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const size_t kMeshletMaxTriangles = 512;
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struct TriangleAdjacency2
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{
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unsigned int* counts;
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unsigned int* offsets;
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unsigned int* data;
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};
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static void buildTriangleAdjacency(TriangleAdjacency2& adjacency, const unsigned int* indices, size_t index_count, size_t vertex_count, meshopt_Allocator& allocator)
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{
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size_t face_count = index_count / 3;
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// allocate arrays
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adjacency.counts = allocator.allocate<unsigned int>(vertex_count);
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adjacency.offsets = allocator.allocate<unsigned int>(vertex_count);
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adjacency.data = allocator.allocate<unsigned int>(index_count);
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// fill triangle counts
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memset(adjacency.counts, 0, vertex_count * sizeof(unsigned int));
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for (size_t i = 0; i < index_count; ++i)
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{
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assert(indices[i] < vertex_count);
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adjacency.counts[indices[i]]++;
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}
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// fill offset table
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unsigned int offset = 0;
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for (size_t i = 0; i < vertex_count; ++i)
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{
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adjacency.offsets[i] = offset;
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offset += adjacency.counts[i];
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}
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assert(offset == index_count);
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// fill triangle data
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for (size_t i = 0; i < face_count; ++i)
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{
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unsigned int a = indices[i * 3 + 0], b = indices[i * 3 + 1], c = indices[i * 3 + 2];
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adjacency.data[adjacency.offsets[a]++] = unsigned(i);
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adjacency.data[adjacency.offsets[b]++] = unsigned(i);
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adjacency.data[adjacency.offsets[c]++] = unsigned(i);
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}
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// fix offsets that have been disturbed by the previous pass
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for (size_t i = 0; i < vertex_count; ++i)
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{
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assert(adjacency.offsets[i] >= adjacency.counts[i]);
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adjacency.offsets[i] -= adjacency.counts[i];
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}
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}
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static void computeBoundingSphere(float result[4], const float points[][3], size_t count)
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{
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assert(count > 0);
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// find extremum points along all 3 axes; for each axis we get a pair of points with min/max coordinates
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size_t pmin[3] = {0, 0, 0};
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size_t pmax[3] = {0, 0, 0};
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for (size_t i = 0; i < count; ++i)
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{
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const float* p = points[i];
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for (int axis = 0; axis < 3; ++axis)
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{
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pmin[axis] = (p[axis] < points[pmin[axis]][axis]) ? i : pmin[axis];
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pmax[axis] = (p[axis] > points[pmax[axis]][axis]) ? i : pmax[axis];
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}
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}
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// find the pair of points with largest distance
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float paxisd2 = 0;
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int paxis = 0;
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for (int axis = 0; axis < 3; ++axis)
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{
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const float* p1 = points[pmin[axis]];
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const float* p2 = points[pmax[axis]];
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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]);
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if (d2 > paxisd2)
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{
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paxisd2 = d2;
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paxis = axis;
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}
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}
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// use the longest segment as the initial sphere diameter
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const float* p1 = points[pmin[paxis]];
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const float* p2 = points[pmax[paxis]];
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float center[3] = {(p1[0] + p2[0]) / 2, (p1[1] + p2[1]) / 2, (p1[2] + p2[2]) / 2};
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float radius = sqrtf(paxisd2) / 2;
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// iteratively adjust the sphere up until all points fit
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for (size_t i = 0; i < count; ++i)
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{
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const float* p = points[i];
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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]);
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if (d2 > radius * radius)
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{
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float d = sqrtf(d2);
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assert(d > 0);
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float k = 0.5f + (radius / d) / 2;
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center[0] = center[0] * k + p[0] * (1 - k);
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center[1] = center[1] * k + p[1] * (1 - k);
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center[2] = center[2] * k + p[2] * (1 - k);
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radius = (radius + d) / 2;
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}
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}
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result[0] = center[0];
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result[1] = center[1];
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result[2] = center[2];
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result[3] = radius;
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}
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struct Cone
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{
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float px, py, pz;
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float nx, ny, nz;
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};
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static float getMeshletScore(float distance2, float spread, float cone_weight, float expected_radius)
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{
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float cone = 1.f - spread * cone_weight;
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float cone_clamped = cone < 1e-3f ? 1e-3f : cone;
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return (1 + sqrtf(distance2) / expected_radius * (1 - cone_weight)) * cone_clamped;
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}
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static Cone getMeshletCone(const Cone& acc, unsigned int triangle_count)
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{
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Cone result = acc;
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float center_scale = triangle_count == 0 ? 0.f : 1.f / float(triangle_count);
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result.px *= center_scale;
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result.py *= center_scale;
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result.pz *= center_scale;
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float axis_length = result.nx * result.nx + result.ny * result.ny + result.nz * result.nz;
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float axis_scale = axis_length == 0.f ? 0.f : 1.f / sqrtf(axis_length);
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result.nx *= axis_scale;
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result.ny *= axis_scale;
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result.nz *= axis_scale;
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return result;
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}
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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)
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{
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(void)vertex_count;
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size_t vertex_stride_float = vertex_positions_stride / sizeof(float);
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size_t face_count = index_count / 3;
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float mesh_area = 0;
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for (size_t i = 0; i < face_count; ++i)
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{
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unsigned int a = indices[i * 3 + 0], b = indices[i * 3 + 1], c = indices[i * 3 + 2];
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assert(a < vertex_count && b < vertex_count && c < vertex_count);
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const float* p0 = vertex_positions + vertex_stride_float * a;
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const float* p1 = vertex_positions + vertex_stride_float * b;
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const float* p2 = vertex_positions + vertex_stride_float * c;
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float p10[3] = {p1[0] - p0[0], p1[1] - p0[1], p1[2] - p0[2]};
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float p20[3] = {p2[0] - p0[0], p2[1] - p0[1], p2[2] - p0[2]};
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float normalx = p10[1] * p20[2] - p10[2] * p20[1];
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float normaly = p10[2] * p20[0] - p10[0] * p20[2];
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float normalz = p10[0] * p20[1] - p10[1] * p20[0];
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float area = sqrtf(normalx * normalx + normaly * normaly + normalz * normalz);
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float invarea = (area == 0.f) ? 0.f : 1.f / area;
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triangles[i].px = (p0[0] + p1[0] + p2[0]) / 3.f;
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triangles[i].py = (p0[1] + p1[1] + p2[1]) / 3.f;
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triangles[i].pz = (p0[2] + p1[2] + p2[2]) / 3.f;
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triangles[i].nx = normalx * invarea;
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triangles[i].ny = normaly * invarea;
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triangles[i].nz = normalz * invarea;
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mesh_area += area;
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}
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return mesh_area;
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}
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static void finishMeshlet(meshopt_Meshlet& meshlet, unsigned char* meshlet_triangles)
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{
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size_t offset = meshlet.triangle_offset + meshlet.triangle_count * 3;
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// fill 4b padding with 0
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while (offset & 3)
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meshlet_triangles[offset++] = 0;
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}
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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)
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{
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unsigned char& av = used[a];
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unsigned char& bv = used[b];
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unsigned char& cv = used[c];
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bool result = false;
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unsigned int used_extra = (av == 0xff) + (bv == 0xff) + (cv == 0xff);
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if (meshlet.vertex_count + used_extra > max_vertices || meshlet.triangle_count >= max_triangles)
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{
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meshlets[meshlet_offset] = meshlet;
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for (size_t j = 0; j < meshlet.vertex_count; ++j)
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used[meshlet_vertices[meshlet.vertex_offset + j]] = 0xff;
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finishMeshlet(meshlet, meshlet_triangles);
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meshlet.vertex_offset += meshlet.vertex_count;
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meshlet.triangle_offset += (meshlet.triangle_count * 3 + 3) & ~3; // 4b padding
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meshlet.vertex_count = 0;
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meshlet.triangle_count = 0;
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result = true;
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}
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if (av == 0xff)
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{
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av = (unsigned char)meshlet.vertex_count;
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meshlet_vertices[meshlet.vertex_offset + meshlet.vertex_count++] = a;
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}
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if (bv == 0xff)
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{
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bv = (unsigned char)meshlet.vertex_count;
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meshlet_vertices[meshlet.vertex_offset + meshlet.vertex_count++] = b;
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}
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if (cv == 0xff)
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{
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cv = (unsigned char)meshlet.vertex_count;
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meshlet_vertices[meshlet.vertex_offset + meshlet.vertex_count++] = c;
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}
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meshlet_triangles[meshlet.triangle_offset + meshlet.triangle_count * 3 + 0] = av;
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meshlet_triangles[meshlet.triangle_offset + meshlet.triangle_count * 3 + 1] = bv;
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meshlet_triangles[meshlet.triangle_offset + meshlet.triangle_count * 3 + 2] = cv;
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meshlet.triangle_count++;
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return result;
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}
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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)
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{
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unsigned int best_triangle = ~0u;
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unsigned int best_extra = 5;
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float best_score = FLT_MAX;
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for (size_t i = 0; i < meshlet.vertex_count; ++i)
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{
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unsigned int index = meshlet_vertices[meshlet.vertex_offset + i];
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unsigned int* neighbors = &adjacency.data[0] + adjacency.offsets[index];
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size_t neighbors_size = adjacency.counts[index];
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for (size_t j = 0; j < neighbors_size; ++j)
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{
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unsigned int triangle = neighbors[j];
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unsigned int a = indices[triangle * 3 + 0], b = indices[triangle * 3 + 1], c = indices[triangle * 3 + 2];
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unsigned int extra = (used[a] == 0xff) + (used[b] == 0xff) + (used[c] == 0xff);
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// triangles that don't add new vertices to meshlets are max. priority
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if (extra != 0)
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{
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// artificially increase the priority of dangling triangles as they're expensive to add to new meshlets
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if (live_triangles[a] == 1 || live_triangles[b] == 1 || live_triangles[c] == 1)
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extra = 0;
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extra++;
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}
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// since topology-based priority is always more important than the score, we can skip scoring in some cases
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if (extra > best_extra)
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continue;
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float score = 0;
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// caller selects one of two scoring functions: geometrical (based on meshlet cone) or topological (based on remaining triangles)
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if (meshlet_cone)
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{
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const Cone& tri_cone = triangles[triangle];
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float distance2 =
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(tri_cone.px - meshlet_cone->px) * (tri_cone.px - meshlet_cone->px) +
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(tri_cone.py - meshlet_cone->py) * (tri_cone.py - meshlet_cone->py) +
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(tri_cone.pz - meshlet_cone->pz) * (tri_cone.pz - meshlet_cone->pz);
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float spread = tri_cone.nx * meshlet_cone->nx + tri_cone.ny * meshlet_cone->ny + tri_cone.nz * meshlet_cone->nz;
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score = getMeshletScore(distance2, spread, cone_weight, meshlet_expected_radius);
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}
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else
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{
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// each live_triangles entry is >= 1 since it includes the current triangle we're processing
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score = float(live_triangles[a] + live_triangles[b] + live_triangles[c] - 3);
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}
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// note that topology-based priority is always more important than the score
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// this helps maintain reasonable effectiveness of meshlet data and reduces scoring cost
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if (extra < best_extra || score < best_score)
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{
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best_triangle = triangle;
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best_extra = extra;
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best_score = score;
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}
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}
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}
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if (out_extra)
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*out_extra = best_extra;
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return best_triangle;
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}
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struct KDNode
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{
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union
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{
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float split;
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unsigned int index;
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};
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// leaves: axis = 3, children = number of extra points after this one (0 if 'index' is the only point)
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// branches: axis != 3, left subtree = skip 1, right subtree = skip 1+children
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unsigned int axis : 2;
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unsigned int children : 30;
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};
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static size_t kdtreePartition(unsigned int* indices, size_t count, const float* points, size_t stride, unsigned int axis, float pivot)
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{
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size_t m = 0;
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// invariant: elements in range [0, m) are < pivot, elements in range [m, i) are >= pivot
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for (size_t i = 0; i < count; ++i)
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{
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float v = points[indices[i] * stride + axis];
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// swap(m, i) unconditionally
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unsigned int t = indices[m];
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indices[m] = indices[i];
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indices[i] = t;
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// when v >= pivot, we swap i with m without advancing it, preserving invariants
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m += v < pivot;
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}
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return m;
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}
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static size_t kdtreeBuildLeaf(size_t offset, KDNode* nodes, size_t node_count, unsigned int* indices, size_t count)
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{
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assert(offset + count <= node_count);
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(void)node_count;
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KDNode& result = nodes[offset];
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result.index = indices[0];
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result.axis = 3;
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result.children = unsigned(count - 1);
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// all remaining points are stored in nodes immediately following the leaf
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for (size_t i = 1; i < count; ++i)
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{
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KDNode& tail = nodes[offset + i];
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tail.index = indices[i];
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tail.axis = 3;
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tail.children = ~0u >> 2; // bogus value to prevent misuse
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}
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return offset + count;
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}
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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)
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{
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assert(count > 0);
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assert(offset < node_count);
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if (count <= leaf_size)
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return kdtreeBuildLeaf(offset, nodes, node_count, indices, count);
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float mean[3] = {};
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float vars[3] = {};
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float runc = 1, runs = 1;
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// gather statistics on the points in the subtree using Welford's algorithm
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for (size_t i = 0; i < count; ++i, runc += 1.f, runs = 1.f / runc)
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{
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const float* point = points + indices[i] * stride;
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for (int k = 0; k < 3; ++k)
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{
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float delta = point[k] - mean[k];
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mean[k] += delta * runs;
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vars[k] += delta * (point[k] - mean[k]);
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}
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}
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// 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];
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size_t middle = kdtreePartition(indices, count, points, stride, axis, split);
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// when the partition is degenerate simply consolidate the points into a single node
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if (middle <= leaf_size / 2 || middle >= count - leaf_size / 2)
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return kdtreeBuildLeaf(offset, nodes, node_count, indices, count);
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KDNode& result = nodes[offset];
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result.split = split;
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result.axis = axis;
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// left subtree is right after our node
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size_t next_offset = kdtreeBuild(offset + 1, nodes, node_count, points, stride, indices, middle, leaf_size);
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// distance to the right subtree is represented explicitly
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result.children = unsigned(next_offset - offset - 1);
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return kdtreeBuild(next_offset, nodes, node_count, points, stride, indices + middle, count - middle, leaf_size);
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}
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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)
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{
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const KDNode& node = nodes[root];
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if (node.axis == 3)
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{
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// leaf
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for (unsigned int i = 0; i <= node.children; ++i)
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|
{
|
|
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);
|
|
}
|
|
}
|
|
|
|
} // namespace meshopt
|
|
|
|
size_t meshopt_buildMeshletsBound(size_t index_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
|
|
|
|
(void)kMeshletMaxVertices;
|
|
(void)kMeshletMaxTriangles;
|
|
|
|
// 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;
|
|
}
|
|
|
|
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)
|
|
{
|
|
using namespace meshopt;
|
|
|
|
assert(index_count % 3 == 0);
|
|
assert(vertex_positions_stride >= 12 && vertex_positions_stride <= 256);
|
|
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
|
|
|
|
assert(cone_weight >= 0 && cone_weight <= 1);
|
|
|
|
meshopt_Allocator allocator;
|
|
|
|
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);
|
|
|
|
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);
|
|
|
|
// 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;
|
|
|
|
Cone meshlet_cone_acc = {};
|
|
|
|
for (;;)
|
|
{
|
|
Cone meshlet_cone = getMeshletCone(meshlet_cone_acc, meshlet.triangle_count);
|
|
|
|
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);
|
|
|
|
// 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);
|
|
}
|
|
|
|
// when we run out of neighboring triangles we need to switch to spatial search; we currently just pick the closest triangle irrespective of connectivity
|
|
if (best_triangle == ~0u)
|
|
{
|
|
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;
|
|
}
|
|
|
|
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))
|
|
{
|
|
meshlet_offset++;
|
|
memset(&meshlet_cone_acc, 0, sizeof(meshlet_cone_acc));
|
|
}
|
|
|
|
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)
|
|
{
|
|
unsigned int index = indices[best_triangle * 3 + k];
|
|
|
|
unsigned int* neighbors = &adjacency.data[0] + adjacency.offsets[index];
|
|
size_t neighbors_size = adjacency.counts[index];
|
|
|
|
for (size_t i = 0; i < neighbors_size; ++i)
|
|
{
|
|
unsigned int tri = neighbors[i];
|
|
|
|
if (tri == best_triangle)
|
|
{
|
|
neighbors[i] = neighbors[neighbors_size - 1];
|
|
adjacency.counts[index]--;
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
// 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);
|
|
}
|
|
|
|
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;
|
|
}
|
|
|
|
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);
|
|
assert(index_count / 3 <= kMeshletMaxTriangles);
|
|
assert(vertex_positions_stride >= 12 && vertex_positions_stride <= 256);
|
|
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
|
|
float normals[kMeshletMaxTriangles][3];
|
|
float corners[kMeshletMaxTriangles][3][3];
|
|
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;
|
|
}
|
|
|
|
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)
|
|
{
|
|
using namespace meshopt;
|
|
|
|
assert(triangle_count <= kMeshletMaxTriangles);
|
|
assert(vertex_positions_stride >= 12 && vertex_positions_stride <= 256);
|
|
assert(vertex_positions_stride % sizeof(float) == 0);
|
|
|
|
unsigned int indices[kMeshletMaxTriangles * 3];
|
|
|
|
for (size_t i = 0; i < triangle_count * 3; ++i)
|
|
{
|
|
unsigned int index = meshlet_vertices[meshlet_triangles[i]];
|
|
assert(index < vertex_count);
|
|
|
|
indices[i] = index;
|
|
}
|
|
|
|
return meshopt_computeClusterBounds(indices, triangle_count * 3, vertex_positions, vertex_count, vertex_positions_stride);
|
|
}
|