| 1 | // This file is part of meshoptimizer library; see meshoptimizer.h for version/license details |
| 2 | #include "meshoptimizer.h" |
| 3 | |
| 4 | #include <assert.h> |
| 5 | #include <float.h> |
| 6 | #include <math.h> |
| 7 | #include <string.h> |
| 8 | |
| 9 | // This work is based on: |
| 10 | // Graham Wihlidal. Optimizing the Graphics Pipeline with Compute. 2016 |
| 11 | // Matthaeus Chajdas. GeometryFX 1.2 - Cluster Culling. 2016 |
| 12 | // Jack Ritter. An Efficient Bounding Sphere. 1990 |
| 13 | namespace meshopt |
| 14 | { |
| 15 | |
| 16 | // This must be <= 255 since index 0xff is used internally to indice a vertex that doesn't belong to a meshlet |
| 17 | const size_t kMeshletMaxVertices = 255; |
| 18 | |
| 19 | // A reasonable limit is around 2*max_vertices or less |
| 20 | const size_t kMeshletMaxTriangles = 512; |
| 21 | |
| 22 | struct TriangleAdjacency2 |
| 23 | { |
| 24 | unsigned int* counts; |
| 25 | unsigned int* offsets; |
| 26 | unsigned int* data; |
| 27 | }; |
| 28 | |
| 29 | static void buildTriangleAdjacency(TriangleAdjacency2& adjacency, const unsigned int* indices, size_t index_count, size_t vertex_count, meshopt_Allocator& allocator) |
| 30 | { |
| 31 | size_t face_count = index_count / 3; |
| 32 | |
| 33 | // allocate arrays |
| 34 | adjacency.counts = allocator.allocate<unsigned int>(vertex_count); |
| 35 | adjacency.offsets = allocator.allocate<unsigned int>(vertex_count); |
| 36 | adjacency.data = allocator.allocate<unsigned int>(index_count); |
| 37 | |
| 38 | // fill triangle counts |
| 39 | memset(adjacency.counts, 0, vertex_count * sizeof(unsigned int)); |
| 40 | |
| 41 | for (size_t i = 0; i < index_count; ++i) |
| 42 | { |
| 43 | assert(indices[i] < vertex_count); |
| 44 | |
| 45 | adjacency.counts[indices[i]]++; |
| 46 | } |
| 47 | |
| 48 | // fill offset table |
| 49 | unsigned int offset = 0; |
| 50 | |
| 51 | for (size_t i = 0; i < vertex_count; ++i) |
| 52 | { |
| 53 | adjacency.offsets[i] = offset; |
| 54 | offset += adjacency.counts[i]; |
| 55 | } |
| 56 | |
| 57 | assert(offset == index_count); |
| 58 | |
| 59 | // fill triangle data |
| 60 | for (size_t i = 0; i < face_count; ++i) |
| 61 | { |
| 62 | unsigned int a = indices[i * 3 + 0], b = indices[i * 3 + 1], c = indices[i * 3 + 2]; |
| 63 | |
| 64 | adjacency.data[adjacency.offsets[a]++] = unsigned(i); |
| 65 | adjacency.data[adjacency.offsets[b]++] = unsigned(i); |
| 66 | adjacency.data[adjacency.offsets[c]++] = unsigned(i); |
| 67 | } |
| 68 | |
| 69 | // fix offsets that have been disturbed by the previous pass |
| 70 | for (size_t i = 0; i < vertex_count; ++i) |
| 71 | { |
| 72 | assert(adjacency.offsets[i] >= adjacency.counts[i]); |
| 73 | |
| 74 | adjacency.offsets[i] -= adjacency.counts[i]; |
| 75 | } |
| 76 | } |
| 77 | |
| 78 | static void computeBoundingSphere(float result[4], const float points[][3], size_t count) |
| 79 | { |
| 80 | assert(count > 0); |
| 81 | |
| 82 | // find extremum points along all 3 axes; for each axis we get a pair of points with min/max coordinates |
| 83 | size_t pmin[3] = {0, 0, 0}; |
| 84 | size_t pmax[3] = {0, 0, 0}; |
| 85 | |
| 86 | for (size_t i = 0; i < count; ++i) |
| 87 | { |
| 88 | const float* p = points[i]; |
| 89 | |
| 90 | for (int axis = 0; axis < 3; ++axis) |
| 91 | { |
| 92 | pmin[axis] = (p[axis] < points[pmin[axis]][axis]) ? i : pmin[axis]; |
| 93 | pmax[axis] = (p[axis] > points[pmax[axis]][axis]) ? i : pmax[axis]; |
| 94 | } |
| 95 | } |
| 96 | |
| 97 | // find the pair of points with largest distance |
| 98 | float paxisd2 = 0; |
| 99 | int paxis = 0; |
| 100 | |
| 101 | for (int axis = 0; axis < 3; ++axis) |
| 102 | { |
| 103 | const float* p1 = points[pmin[axis]]; |
| 104 | const float* p2 = points[pmax[axis]]; |
| 105 | |
| 106 | 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]); |
| 107 | |
| 108 | if (d2 > paxisd2) |
| 109 | { |
| 110 | paxisd2 = d2; |
| 111 | paxis = axis; |
| 112 | } |
| 113 | } |
| 114 | |
| 115 | // use the longest segment as the initial sphere diameter |
| 116 | const float* p1 = points[pmin[paxis]]; |
| 117 | const float* p2 = points[pmax[paxis]]; |
| 118 | |
| 119 | float center[3] = {(p1[0] + p2[0]) / 2, (p1[1] + p2[1]) / 2, (p1[2] + p2[2]) / 2}; |
| 120 | float radius = sqrtf(paxisd2) / 2; |
| 121 | |
| 122 | // iteratively adjust the sphere up until all points fit |
| 123 | for (size_t i = 0; i < count; ++i) |
| 124 | { |
| 125 | const float* p = points[i]; |
| 126 | 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]); |
| 127 | |
| 128 | if (d2 > radius * radius) |
| 129 | { |
| 130 | float d = sqrtf(d2); |
| 131 | assert(d > 0); |
| 132 | |
| 133 | float k = 0.5f + (radius / d) / 2; |
| 134 | |
| 135 | center[0] = center[0] * k + p[0] * (1 - k); |
| 136 | center[1] = center[1] * k + p[1] * (1 - k); |
| 137 | center[2] = center[2] * k + p[2] * (1 - k); |
| 138 | radius = (radius + d) / 2; |
| 139 | } |
| 140 | } |
| 141 | |
| 142 | result[0] = center[0]; |
| 143 | result[1] = center[1]; |
| 144 | result[2] = center[2]; |
| 145 | result[3] = radius; |
| 146 | } |
| 147 | |
| 148 | struct Cone |
| 149 | { |
| 150 | float px, py, pz; |
| 151 | float nx, ny, nz; |
| 152 | }; |
| 153 | |
| 154 | static float getMeshletScore(float distance2, float spread, float cone_weight, float expected_radius) |
| 155 | { |
| 156 | float cone = 1.f - spread * cone_weight; |
| 157 | float cone_clamped = cone < 1e-3f ? 1e-3f : cone; |
| 158 | |
| 159 | return (1 + sqrtf(distance2) / expected_radius * (1 - cone_weight)) * cone_clamped; |
| 160 | } |
| 161 | |
| 162 | static Cone getMeshletCone(const Cone& acc, unsigned int triangle_count) |
| 163 | { |
| 164 | Cone result = acc; |
| 165 | |
| 166 | float center_scale = triangle_count == 0 ? 0.f : 1.f / float(triangle_count); |
| 167 | |
| 168 | result.px *= center_scale; |
| 169 | result.py *= center_scale; |
| 170 | result.pz *= center_scale; |
| 171 | |
| 172 | float axis_length = result.nx * result.nx + result.ny * result.ny + result.nz * result.nz; |
| 173 | float axis_scale = axis_length == 0.f ? 0.f : 1.f / sqrtf(axis_length); |
| 174 | |
| 175 | result.nx *= axis_scale; |
| 176 | result.ny *= axis_scale; |
| 177 | result.nz *= axis_scale; |
| 178 | |
| 179 | return result; |
| 180 | } |
| 181 | |
| 182 | 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) |
| 183 | { |
| 184 | (void)vertex_count; |
| 185 | |
| 186 | size_t vertex_stride_float = vertex_positions_stride / sizeof(float); |
| 187 | size_t face_count = index_count / 3; |
| 188 | |
| 189 | float mesh_area = 0; |
| 190 | |
| 191 | for (size_t i = 0; i < face_count; ++i) |
| 192 | { |
| 193 | unsigned int a = indices[i * 3 + 0], b = indices[i * 3 + 1], c = indices[i * 3 + 2]; |
| 194 | assert(a < vertex_count && b < vertex_count && c < vertex_count); |
| 195 | |
| 196 | const float* p0 = vertex_positions + vertex_stride_float * a; |
| 197 | const float* p1 = vertex_positions + vertex_stride_float * b; |
| 198 | const float* p2 = vertex_positions + vertex_stride_float * c; |
| 199 | |
| 200 | float p10[3] = {p1[0] - p0[0], p1[1] - p0[1], p1[2] - p0[2]}; |
| 201 | float p20[3] = {p2[0] - p0[0], p2[1] - p0[1], p2[2] - p0[2]}; |
| 202 | |
| 203 | float normalx = p10[1] * p20[2] - p10[2] * p20[1]; |
| 204 | float normaly = p10[2] * p20[0] - p10[0] * p20[2]; |
| 205 | float normalz = p10[0] * p20[1] - p10[1] * p20[0]; |
| 206 | |
| 207 | float area = sqrtf(normalx * normalx + normaly * normaly + normalz * normalz); |
| 208 | float invarea = (area == 0.f) ? 0.f : 1.f / area; |
| 209 | |
| 210 | triangles[i].px = (p0[0] + p1[0] + p2[0]) / 3.f; |
| 211 | triangles[i].py = (p0[1] + p1[1] + p2[1]) / 3.f; |
| 212 | triangles[i].pz = (p0[2] + p1[2] + p2[2]) / 3.f; |
| 213 | |
| 214 | triangles[i].nx = normalx * invarea; |
| 215 | triangles[i].ny = normaly * invarea; |
| 216 | triangles[i].nz = normalz * invarea; |
| 217 | |
| 218 | mesh_area += area; |
| 219 | } |
| 220 | |
| 221 | return mesh_area; |
| 222 | } |
| 223 | |
| 224 | static void finishMeshlet(meshopt_Meshlet& meshlet, unsigned char* meshlet_triangles) |
| 225 | { |
| 226 | size_t offset = meshlet.triangle_offset + meshlet.triangle_count * 3; |
| 227 | |
| 228 | // fill 4b padding with 0 |
| 229 | while (offset & 3) |
| 230 | meshlet_triangles[offset++] = 0; |
| 231 | } |
| 232 | |
| 233 | 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) |
| 234 | { |
| 235 | unsigned char& av = used[a]; |
| 236 | unsigned char& bv = used[b]; |
| 237 | unsigned char& cv = used[c]; |
| 238 | |
| 239 | bool result = false; |
| 240 | |
| 241 | unsigned int = (av == 0xff) + (bv == 0xff) + (cv == 0xff); |
| 242 | |
| 243 | if (meshlet.vertex_count + used_extra > max_vertices || meshlet.triangle_count >= max_triangles) |
| 244 | { |
| 245 | meshlets[meshlet_offset] = meshlet; |
| 246 | |
| 247 | for (size_t j = 0; j < meshlet.vertex_count; ++j) |
| 248 | used[meshlet_vertices[meshlet.vertex_offset + j]] = 0xff; |
| 249 | |
| 250 | finishMeshlet(meshlet, meshlet_triangles); |
| 251 | |
| 252 | meshlet.vertex_offset += meshlet.vertex_count; |
| 253 | meshlet.triangle_offset += (meshlet.triangle_count * 3 + 3) & ~3; // 4b padding |
| 254 | meshlet.vertex_count = 0; |
| 255 | meshlet.triangle_count = 0; |
| 256 | |
| 257 | result = true; |
| 258 | } |
| 259 | |
| 260 | if (av == 0xff) |
| 261 | { |
| 262 | av = (unsigned char)meshlet.vertex_count; |
| 263 | meshlet_vertices[meshlet.vertex_offset + meshlet.vertex_count++] = a; |
| 264 | } |
| 265 | |
| 266 | if (bv == 0xff) |
| 267 | { |
| 268 | bv = (unsigned char)meshlet.vertex_count; |
| 269 | meshlet_vertices[meshlet.vertex_offset + meshlet.vertex_count++] = b; |
| 270 | } |
| 271 | |
| 272 | if (cv == 0xff) |
| 273 | { |
| 274 | cv = (unsigned char)meshlet.vertex_count; |
| 275 | meshlet_vertices[meshlet.vertex_offset + meshlet.vertex_count++] = c; |
| 276 | } |
| 277 | |
| 278 | meshlet_triangles[meshlet.triangle_offset + meshlet.triangle_count * 3 + 0] = av; |
| 279 | meshlet_triangles[meshlet.triangle_offset + meshlet.triangle_count * 3 + 1] = bv; |
| 280 | meshlet_triangles[meshlet.triangle_offset + meshlet.triangle_count * 3 + 2] = cv; |
| 281 | meshlet.triangle_count++; |
| 282 | |
| 283 | return result; |
| 284 | } |
| 285 | |
| 286 | 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* ) |
| 287 | { |
| 288 | unsigned int best_triangle = ~0u; |
| 289 | unsigned int = 5; |
| 290 | float best_score = FLT_MAX; |
| 291 | |
| 292 | for (size_t i = 0; i < meshlet.vertex_count; ++i) |
| 293 | { |
| 294 | unsigned int index = meshlet_vertices[meshlet.vertex_offset + i]; |
| 295 | |
| 296 | unsigned int* neighbors = &adjacency.data[0] + adjacency.offsets[index]; |
| 297 | size_t neighbors_size = adjacency.counts[index]; |
| 298 | |
| 299 | for (size_t j = 0; j < neighbors_size; ++j) |
| 300 | { |
| 301 | unsigned int triangle = neighbors[j]; |
| 302 | unsigned int a = indices[triangle * 3 + 0], b = indices[triangle * 3 + 1], c = indices[triangle * 3 + 2]; |
| 303 | |
| 304 | unsigned int = (used[a] == 0xff) + (used[b] == 0xff) + (used[c] == 0xff); |
| 305 | |
| 306 | // triangles that don't add new vertices to meshlets are max. priority |
| 307 | if (extra != 0) |
| 308 | { |
| 309 | // artificially increase the priority of dangling triangles as they're expensive to add to new meshlets |
| 310 | if (live_triangles[a] == 1 || live_triangles[b] == 1 || live_triangles[c] == 1) |
| 311 | extra = 0; |
| 312 | |
| 313 | extra++; |
| 314 | } |
| 315 | |
| 316 | // since topology-based priority is always more important than the score, we can skip scoring in some cases |
| 317 | if (extra > best_extra) |
| 318 | continue; |
| 319 | |
| 320 | float score = 0; |
| 321 | |
| 322 | // caller selects one of two scoring functions: geometrical (based on meshlet cone) or topological (based on remaining triangles) |
| 323 | if (meshlet_cone) |
| 324 | { |
| 325 | const Cone& tri_cone = triangles[triangle]; |
| 326 | |
| 327 | float distance2 = |
| 328 | (tri_cone.px - meshlet_cone->px) * (tri_cone.px - meshlet_cone->px) + |
| 329 | (tri_cone.py - meshlet_cone->py) * (tri_cone.py - meshlet_cone->py) + |
| 330 | (tri_cone.pz - meshlet_cone->pz) * (tri_cone.pz - meshlet_cone->pz); |
| 331 | |
| 332 | float spread = tri_cone.nx * meshlet_cone->nx + tri_cone.ny * meshlet_cone->ny + tri_cone.nz * meshlet_cone->nz; |
| 333 | |
| 334 | score = getMeshletScore(distance2, spread, cone_weight, meshlet_expected_radius); |
| 335 | } |
| 336 | else |
| 337 | { |
| 338 | // each live_triangles entry is >= 1 since it includes the current triangle we're processing |
| 339 | score = float(live_triangles[a] + live_triangles[b] + live_triangles[c] - 3); |
| 340 | } |
| 341 | |
| 342 | // note that topology-based priority is always more important than the score |
| 343 | // this helps maintain reasonable effectiveness of meshlet data and reduces scoring cost |
| 344 | if (extra < best_extra || score < best_score) |
| 345 | { |
| 346 | best_triangle = triangle; |
| 347 | best_extra = extra; |
| 348 | best_score = score; |
| 349 | } |
| 350 | } |
| 351 | } |
| 352 | |
| 353 | if (out_extra) |
| 354 | *out_extra = best_extra; |
| 355 | |
| 356 | return best_triangle; |
| 357 | } |
| 358 | |
| 359 | struct KDNode |
| 360 | { |
| 361 | union |
| 362 | { |
| 363 | float split; |
| 364 | unsigned int index; |
| 365 | }; |
| 366 | |
| 367 | // leaves: axis = 3, children = number of extra points after this one (0 if 'index' is the only point) |
| 368 | // branches: axis != 3, left subtree = skip 1, right subtree = skip 1+children |
| 369 | unsigned int axis : 2; |
| 370 | unsigned int children : 30; |
| 371 | }; |
| 372 | |
| 373 | static size_t kdtreePartition(unsigned int* indices, size_t count, const float* points, size_t stride, unsigned int axis, float pivot) |
| 374 | { |
| 375 | size_t m = 0; |
| 376 | |
| 377 | // invariant: elements in range [0, m) are < pivot, elements in range [m, i) are >= pivot |
| 378 | for (size_t i = 0; i < count; ++i) |
| 379 | { |
| 380 | float v = points[indices[i] * stride + axis]; |
| 381 | |
| 382 | // swap(m, i) unconditionally |
| 383 | unsigned int t = indices[m]; |
| 384 | indices[m] = indices[i]; |
| 385 | indices[i] = t; |
| 386 | |
| 387 | // when v >= pivot, we swap i with m without advancing it, preserving invariants |
| 388 | m += v < pivot; |
| 389 | } |
| 390 | |
| 391 | return m; |
| 392 | } |
| 393 | |
| 394 | static size_t kdtreeBuildLeaf(size_t offset, KDNode* nodes, size_t node_count, unsigned int* indices, size_t count) |
| 395 | { |
| 396 | assert(offset + count <= node_count); |
| 397 | (void)node_count; |
| 398 | |
| 399 | KDNode& result = nodes[offset]; |
| 400 | |
| 401 | result.index = indices[0]; |
| 402 | result.axis = 3; |
| 403 | result.children = unsigned(count - 1); |
| 404 | |
| 405 | // all remaining points are stored in nodes immediately following the leaf |
| 406 | for (size_t i = 1; i < count; ++i) |
| 407 | { |
| 408 | KDNode& tail = nodes[offset + i]; |
| 409 | |
| 410 | tail.index = indices[i]; |
| 411 | tail.axis = 3; |
| 412 | tail.children = ~0u >> 2; // bogus value to prevent misuse |
| 413 | } |
| 414 | |
| 415 | return offset + count; |
| 416 | } |
| 417 | |
| 418 | 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) |
| 419 | { |
| 420 | assert(count > 0); |
| 421 | assert(offset < node_count); |
| 422 | |
| 423 | if (count <= leaf_size) |
| 424 | return kdtreeBuildLeaf(offset, nodes, node_count, indices, count); |
| 425 | |
| 426 | float mean[3] = {}; |
| 427 | float vars[3] = {}; |
| 428 | float runc = 1, runs = 1; |
| 429 | |
| 430 | // gather statistics on the points in the subtree using Welford's algorithm |
| 431 | for (size_t i = 0; i < count; ++i, runc += 1.f, runs = 1.f / runc) |
| 432 | { |
| 433 | const float* point = points + indices[i] * stride; |
| 434 | |
| 435 | for (int k = 0; k < 3; ++k) |
| 436 | { |
| 437 | float delta = point[k] - mean[k]; |
| 438 | mean[k] += delta * runs; |
| 439 | vars[k] += delta * (point[k] - mean[k]); |
| 440 | } |
| 441 | } |
| 442 | |
| 443 | // split axis is one where the variance is largest |
| 444 | unsigned int axis = vars[0] >= vars[1] && vars[0] >= vars[2] ? 0 : vars[1] >= vars[2] ? 1 : 2; |
| 445 | |
| 446 | float split = mean[axis]; |
| 447 | size_t middle = kdtreePartition(indices, count, points, stride, axis, split); |
| 448 | |
| 449 | // when the partition is degenerate simply consolidate the points into a single node |
| 450 | if (middle <= leaf_size / 2 || middle >= count - leaf_size / 2) |
| 451 | return kdtreeBuildLeaf(offset, nodes, node_count, indices, count); |
| 452 | |
| 453 | KDNode& result = nodes[offset]; |
| 454 | |
| 455 | result.split = split; |
| 456 | result.axis = axis; |
| 457 | |
| 458 | // left subtree is right after our node |
| 459 | size_t next_offset = kdtreeBuild(offset + 1, nodes, node_count, points, stride, indices, middle, leaf_size); |
| 460 | |
| 461 | // distance to the right subtree is represented explicitly |
| 462 | result.children = unsigned(next_offset - offset - 1); |
| 463 | |
| 464 | return kdtreeBuild(next_offset, nodes, node_count, points, stride, indices + middle, count - middle, leaf_size); |
| 465 | } |
| 466 | |
| 467 | 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) |
| 468 | { |
| 469 | const KDNode& node = nodes[root]; |
| 470 | |
| 471 | if (node.axis == 3) |
| 472 | { |
| 473 | // leaf |
| 474 | for (unsigned int i = 0; i <= node.children; ++i) |
| 475 | { |
| 476 | unsigned int index = nodes[root + i].index; |
| 477 | |
| 478 | if (emitted_flags[index]) |
| 479 | continue; |
| 480 | |
| 481 | const float* point = points + index * stride; |
| 482 | |
| 483 | float distance2 = |
| 484 | (point[0] - position[0]) * (point[0] - position[0]) + |
| 485 | (point[1] - position[1]) * (point[1] - position[1]) + |
| 486 | (point[2] - position[2]) * (point[2] - position[2]); |
| 487 | float distance = sqrtf(distance2); |
| 488 | |
| 489 | if (distance < limit) |
| 490 | { |
| 491 | result = index; |
| 492 | limit = distance; |
| 493 | } |
| 494 | } |
| 495 | } |
| 496 | else |
| 497 | { |
| 498 | // branch; we order recursion to process the node that search position is in first |
| 499 | float delta = position[node.axis] - node.split; |
| 500 | unsigned int first = (delta <= 0) ? 0 : node.children; |
| 501 | unsigned int second = first ^ node.children; |
| 502 | |
| 503 | kdtreeNearest(nodes, root + 1 + first, points, stride, emitted_flags, position, result, limit); |
| 504 | |
| 505 | // only process the other node if it can have a match based on closest distance so far |
| 506 | if (fabsf(delta) <= limit) |
| 507 | kdtreeNearest(nodes, root + 1 + second, points, stride, emitted_flags, position, result, limit); |
| 508 | } |
| 509 | } |
| 510 | |
| 511 | } // namespace meshopt |
| 512 | |
| 513 | size_t meshopt_buildMeshletsBound(size_t index_count, size_t max_vertices, size_t max_triangles) |
| 514 | { |
| 515 | using namespace meshopt; |
| 516 | |
| 517 | assert(index_count % 3 == 0); |
| 518 | assert(max_vertices >= 3 && max_vertices <= kMeshletMaxVertices); |
| 519 | assert(max_triangles >= 1 && max_triangles <= kMeshletMaxTriangles); |
| 520 | assert(max_triangles % 4 == 0); // ensures the caller will compute output space properly as index data is 4b aligned |
| 521 | |
| 522 | (void)kMeshletMaxVertices; |
| 523 | (void)kMeshletMaxTriangles; |
| 524 | |
| 525 | // meshlet construction is limited by max vertices and max triangles per meshlet |
| 526 | // the worst case is that the input is an unindexed stream since this equally stresses both limits |
| 527 | // 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 |
| 528 | size_t max_vertices_conservative = max_vertices - 2; |
| 529 | size_t meshlet_limit_vertices = (index_count + max_vertices_conservative - 1) / max_vertices_conservative; |
| 530 | size_t meshlet_limit_triangles = (index_count / 3 + max_triangles - 1) / max_triangles; |
| 531 | |
| 532 | return meshlet_limit_vertices > meshlet_limit_triangles ? meshlet_limit_vertices : meshlet_limit_triangles; |
| 533 | } |
| 534 | |
| 535 | 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) |
| 536 | { |
| 537 | using namespace meshopt; |
| 538 | |
| 539 | assert(index_count % 3 == 0); |
| 540 | assert(vertex_positions_stride >= 12 && vertex_positions_stride <= 256); |
| 541 | assert(vertex_positions_stride % sizeof(float) == 0); |
| 542 | |
| 543 | assert(max_vertices >= 3 && max_vertices <= kMeshletMaxVertices); |
| 544 | assert(max_triangles >= 1 && max_triangles <= kMeshletMaxTriangles); |
| 545 | assert(max_triangles % 4 == 0); // ensures the caller will compute output space properly as index data is 4b aligned |
| 546 | |
| 547 | assert(cone_weight >= 0 && cone_weight <= 1); |
| 548 | |
| 549 | meshopt_Allocator allocator; |
| 550 | |
| 551 | TriangleAdjacency2 adjacency = {}; |
| 552 | buildTriangleAdjacency(adjacency, indices, index_count, vertex_count, allocator); |
| 553 | |
| 554 | unsigned int* live_triangles = allocator.allocate<unsigned int>(vertex_count); |
| 555 | memcpy(live_triangles, adjacency.counts, vertex_count * sizeof(unsigned int)); |
| 556 | |
| 557 | size_t face_count = index_count / 3; |
| 558 | |
| 559 | unsigned char* emitted_flags = allocator.allocate<unsigned char>(face_count); |
| 560 | memset(emitted_flags, 0, face_count); |
| 561 | |
| 562 | // for each triangle, precompute centroid & normal to use for scoring |
| 563 | Cone* triangles = allocator.allocate<Cone>(face_count); |
| 564 | float mesh_area = computeTriangleCones(triangles, indices, index_count, vertex_positions, vertex_count, vertex_positions_stride); |
| 565 | |
| 566 | // assuming each meshlet is a square patch, expected radius is sqrt(expected area) |
| 567 | float triangle_area_avg = face_count == 0 ? 0.f : mesh_area / float(face_count) * 0.5f; |
| 568 | float meshlet_expected_radius = sqrtf(triangle_area_avg * max_triangles) * 0.5f; |
| 569 | |
| 570 | // build a kd-tree for nearest neighbor lookup |
| 571 | unsigned int* kdindices = allocator.allocate<unsigned int>(face_count); |
| 572 | for (size_t i = 0; i < face_count; ++i) |
| 573 | kdindices[i] = unsigned(i); |
| 574 | |
| 575 | KDNode* nodes = allocator.allocate<KDNode>(face_count * 2); |
| 576 | kdtreeBuild(0, nodes, face_count * 2, &triangles[0].px, sizeof(Cone) / sizeof(float), kdindices, face_count, /* leaf_size= */ 8); |
| 577 | |
| 578 | // index of the vertex in the meshlet, 0xff if the vertex isn't used |
| 579 | unsigned char* used = allocator.allocate<unsigned char>(vertex_count); |
| 580 | memset(used, -1, vertex_count); |
| 581 | |
| 582 | meshopt_Meshlet meshlet = {}; |
| 583 | size_t meshlet_offset = 0; |
| 584 | |
| 585 | Cone meshlet_cone_acc = {}; |
| 586 | |
| 587 | for (;;) |
| 588 | { |
| 589 | Cone meshlet_cone = getMeshletCone(meshlet_cone_acc, meshlet.triangle_count); |
| 590 | |
| 591 | unsigned int = 0; |
| 592 | unsigned int best_triangle = getNeighborTriangle(meshlet, &meshlet_cone, meshlet_vertices, indices, adjacency, triangles, live_triangles, used, meshlet_expected_radius, cone_weight, &best_extra); |
| 593 | |
| 594 | // 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 |
| 595 | if (best_triangle != ~0u && (meshlet.vertex_count + best_extra > max_vertices || meshlet.triangle_count >= max_triangles)) |
| 596 | { |
| 597 | best_triangle = getNeighborTriangle(meshlet, NULL, meshlet_vertices, indices, adjacency, triangles, live_triangles, used, meshlet_expected_radius, 0.f, NULL); |
| 598 | } |
| 599 | |
| 600 | // when we run out of neighboring triangles we need to switch to spatial search; we currently just pick the closest triangle irrespective of connectivity |
| 601 | if (best_triangle == ~0u) |
| 602 | { |
| 603 | float position[3] = {meshlet_cone.px, meshlet_cone.py, meshlet_cone.pz}; |
| 604 | unsigned int index = ~0u; |
| 605 | float limit = FLT_MAX; |
| 606 | |
| 607 | kdtreeNearest(nodes, 0, &triangles[0].px, sizeof(Cone) / sizeof(float), emitted_flags, position, index, limit); |
| 608 | |
| 609 | best_triangle = index; |
| 610 | } |
| 611 | |
| 612 | if (best_triangle == ~0u) |
| 613 | break; |
| 614 | |
| 615 | unsigned int a = indices[best_triangle * 3 + 0], b = indices[best_triangle * 3 + 1], c = indices[best_triangle * 3 + 2]; |
| 616 | assert(a < vertex_count && b < vertex_count && c < vertex_count); |
| 617 | |
| 618 | // add meshlet to the output; when the current meshlet is full we reset the accumulated bounds |
| 619 | if (appendMeshlet(meshlet, a, b, c, used, meshlets, meshlet_vertices, meshlet_triangles, meshlet_offset, max_vertices, max_triangles)) |
| 620 | { |
| 621 | meshlet_offset++; |
| 622 | memset(&meshlet_cone_acc, 0, sizeof(meshlet_cone_acc)); |
| 623 | } |
| 624 | |
| 625 | live_triangles[a]--; |
| 626 | live_triangles[b]--; |
| 627 | live_triangles[c]--; |
| 628 | |
| 629 | // remove emitted triangle from adjacency data |
| 630 | // this makes sure that we spend less time traversing these lists on subsequent iterations |
| 631 | for (size_t k = 0; k < 3; ++k) |
| 632 | { |
| 633 | unsigned int index = indices[best_triangle * 3 + k]; |
| 634 | |
| 635 | unsigned int* neighbors = &adjacency.data[0] + adjacency.offsets[index]; |
| 636 | size_t neighbors_size = adjacency.counts[index]; |
| 637 | |
| 638 | for (size_t i = 0; i < neighbors_size; ++i) |
| 639 | { |
| 640 | unsigned int tri = neighbors[i]; |
| 641 | |
| 642 | if (tri == best_triangle) |
| 643 | { |
| 644 | neighbors[i] = neighbors[neighbors_size - 1]; |
| 645 | adjacency.counts[index]--; |
| 646 | break; |
| 647 | } |
| 648 | } |
| 649 | } |
| 650 | |
| 651 | // update aggregated meshlet cone data for scoring subsequent triangles |
| 652 | meshlet_cone_acc.px += triangles[best_triangle].px; |
| 653 | meshlet_cone_acc.py += triangles[best_triangle].py; |
| 654 | meshlet_cone_acc.pz += triangles[best_triangle].pz; |
| 655 | meshlet_cone_acc.nx += triangles[best_triangle].nx; |
| 656 | meshlet_cone_acc.ny += triangles[best_triangle].ny; |
| 657 | meshlet_cone_acc.nz += triangles[best_triangle].nz; |
| 658 | |
| 659 | emitted_flags[best_triangle] = 1; |
| 660 | } |
| 661 | |
| 662 | if (meshlet.triangle_count) |
| 663 | { |
| 664 | finishMeshlet(meshlet, meshlet_triangles); |
| 665 | |
| 666 | meshlets[meshlet_offset++] = meshlet; |
| 667 | } |
| 668 | |
| 669 | assert(meshlet_offset <= meshopt_buildMeshletsBound(index_count, max_vertices, max_triangles)); |
| 670 | return meshlet_offset; |
| 671 | } |
| 672 | |
| 673 | 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) |
| 674 | { |
| 675 | using namespace meshopt; |
| 676 | |
| 677 | assert(index_count % 3 == 0); |
| 678 | |
| 679 | assert(max_vertices >= 3 && max_vertices <= kMeshletMaxVertices); |
| 680 | assert(max_triangles >= 1 && max_triangles <= kMeshletMaxTriangles); |
| 681 | assert(max_triangles % 4 == 0); // ensures the caller will compute output space properly as index data is 4b aligned |
| 682 | |
| 683 | meshopt_Allocator allocator; |
| 684 | |
| 685 | // index of the vertex in the meshlet, 0xff if the vertex isn't used |
| 686 | unsigned char* used = allocator.allocate<unsigned char>(vertex_count); |
| 687 | memset(used, -1, vertex_count); |
| 688 | |
| 689 | meshopt_Meshlet meshlet = {}; |
| 690 | size_t meshlet_offset = 0; |
| 691 | |
| 692 | for (size_t i = 0; i < index_count; i += 3) |
| 693 | { |
| 694 | unsigned int a = indices[i + 0], b = indices[i + 1], c = indices[i + 2]; |
| 695 | assert(a < vertex_count && b < vertex_count && c < vertex_count); |
| 696 | |
| 697 | // appends triangle to the meshlet and writes previous meshlet to the output if full |
| 698 | meshlet_offset += appendMeshlet(meshlet, a, b, c, used, meshlets, meshlet_vertices, meshlet_triangles, meshlet_offset, max_vertices, max_triangles); |
| 699 | } |
| 700 | |
| 701 | if (meshlet.triangle_count) |
| 702 | { |
| 703 | finishMeshlet(meshlet, meshlet_triangles); |
| 704 | |
| 705 | meshlets[meshlet_offset++] = meshlet; |
| 706 | } |
| 707 | |
| 708 | assert(meshlet_offset <= meshopt_buildMeshletsBound(index_count, max_vertices, max_triangles)); |
| 709 | return meshlet_offset; |
| 710 | } |
| 711 | |
| 712 | 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) |
| 713 | { |
| 714 | using namespace meshopt; |
| 715 | |
| 716 | assert(index_count % 3 == 0); |
| 717 | assert(index_count / 3 <= kMeshletMaxTriangles); |
| 718 | assert(vertex_positions_stride >= 12 && vertex_positions_stride <= 256); |
| 719 | assert(vertex_positions_stride % sizeof(float) == 0); |
| 720 | |
| 721 | (void)vertex_count; |
| 722 | |
| 723 | size_t vertex_stride_float = vertex_positions_stride / sizeof(float); |
| 724 | |
| 725 | // compute triangle normals and gather triangle corners |
| 726 | float normals[kMeshletMaxTriangles][3]; |
| 727 | float corners[kMeshletMaxTriangles][3][3]; |
| 728 | size_t triangles = 0; |
| 729 | |
| 730 | for (size_t i = 0; i < index_count; i += 3) |
| 731 | { |
| 732 | unsigned int a = indices[i + 0], b = indices[i + 1], c = indices[i + 2]; |
| 733 | assert(a < vertex_count && b < vertex_count && c < vertex_count); |
| 734 | |
| 735 | const float* p0 = vertex_positions + vertex_stride_float * a; |
| 736 | const float* p1 = vertex_positions + vertex_stride_float * b; |
| 737 | const float* p2 = vertex_positions + vertex_stride_float * c; |
| 738 | |
| 739 | float p10[3] = {p1[0] - p0[0], p1[1] - p0[1], p1[2] - p0[2]}; |
| 740 | float p20[3] = {p2[0] - p0[0], p2[1] - p0[1], p2[2] - p0[2]}; |
| 741 | |
| 742 | float normalx = p10[1] * p20[2] - p10[2] * p20[1]; |
| 743 | float normaly = p10[2] * p20[0] - p10[0] * p20[2]; |
| 744 | float normalz = p10[0] * p20[1] - p10[1] * p20[0]; |
| 745 | |
| 746 | float area = sqrtf(normalx * normalx + normaly * normaly + normalz * normalz); |
| 747 | |
| 748 | // no need to include degenerate triangles - they will be invisible anyway |
| 749 | if (area == 0.f) |
| 750 | continue; |
| 751 | |
| 752 | // record triangle normals & corners for future use; normal and corner 0 define a plane equation |
| 753 | normals[triangles][0] = normalx / area; |
| 754 | normals[triangles][1] = normaly / area; |
| 755 | normals[triangles][2] = normalz / area; |
| 756 | memcpy(corners[triangles][0], p0, 3 * sizeof(float)); |
| 757 | memcpy(corners[triangles][1], p1, 3 * sizeof(float)); |
| 758 | memcpy(corners[triangles][2], p2, 3 * sizeof(float)); |
| 759 | triangles++; |
| 760 | } |
| 761 | |
| 762 | meshopt_Bounds bounds = {}; |
| 763 | |
| 764 | // degenerate cluster, no valid triangles => trivial reject (cone data is 0) |
| 765 | if (triangles == 0) |
| 766 | return bounds; |
| 767 | |
| 768 | // compute cluster bounding sphere; we'll use the center to determine normal cone apex as well |
| 769 | float psphere[4] = {}; |
| 770 | computeBoundingSphere(psphere, corners[0], triangles * 3); |
| 771 | |
| 772 | float center[3] = {psphere[0], psphere[1], psphere[2]}; |
| 773 | |
| 774 | // treating triangle normals as points, find the bounding sphere - the sphere center determines the optimal cone axis |
| 775 | float nsphere[4] = {}; |
| 776 | computeBoundingSphere(nsphere, normals, triangles); |
| 777 | |
| 778 | float axis[3] = {nsphere[0], nsphere[1], nsphere[2]}; |
| 779 | float axislength = sqrtf(axis[0] * axis[0] + axis[1] * axis[1] + axis[2] * axis[2]); |
| 780 | float invaxislength = axislength == 0.f ? 0.f : 1.f / axislength; |
| 781 | |
| 782 | axis[0] *= invaxislength; |
| 783 | axis[1] *= invaxislength; |
| 784 | axis[2] *= invaxislength; |
| 785 | |
| 786 | // compute a tight cone around all normals, mindp = cos(angle/2) |
| 787 | float mindp = 1.f; |
| 788 | |
| 789 | for (size_t i = 0; i < triangles; ++i) |
| 790 | { |
| 791 | float dp = normals[i][0] * axis[0] + normals[i][1] * axis[1] + normals[i][2] * axis[2]; |
| 792 | |
| 793 | mindp = (dp < mindp) ? dp : mindp; |
| 794 | } |
| 795 | |
| 796 | // fill bounding sphere info; note that below we can return bounds without cone information for degenerate cones |
| 797 | bounds.center[0] = center[0]; |
| 798 | bounds.center[1] = center[1]; |
| 799 | bounds.center[2] = center[2]; |
| 800 | bounds.radius = psphere[3]; |
| 801 | |
| 802 | // degenerate cluster, normal cone is larger than a hemisphere => trivial accept |
| 803 | // note that if mindp is positive but close to 0, the triangle intersection code below gets less stable |
| 804 | // we arbitrarily decide that if a normal cone is ~168 degrees wide or more, the cone isn't useful |
| 805 | if (mindp <= 0.1f) |
| 806 | { |
| 807 | bounds.cone_cutoff = 1; |
| 808 | bounds.cone_cutoff_s8 = 127; |
| 809 | return bounds; |
| 810 | } |
| 811 | |
| 812 | float maxt = 0; |
| 813 | |
| 814 | // we need to find the point on center-t*axis ray that lies in negative half-space of all triangles |
| 815 | for (size_t i = 0; i < triangles; ++i) |
| 816 | { |
| 817 | // dot(center-t*axis-corner, trinormal) = 0 |
| 818 | // dot(center-corner, trinormal) - t * dot(axis, trinormal) = 0 |
| 819 | float cx = center[0] - corners[i][0][0]; |
| 820 | float cy = center[1] - corners[i][0][1]; |
| 821 | float cz = center[2] - corners[i][0][2]; |
| 822 | |
| 823 | float dc = cx * normals[i][0] + cy * normals[i][1] + cz * normals[i][2]; |
| 824 | float dn = axis[0] * normals[i][0] + axis[1] * normals[i][1] + axis[2] * normals[i][2]; |
| 825 | |
| 826 | // dn should be larger than mindp cutoff above |
| 827 | assert(dn > 0.f); |
| 828 | float t = dc / dn; |
| 829 | |
| 830 | maxt = (t > maxt) ? t : maxt; |
| 831 | } |
| 832 | |
| 833 | // cone apex should be in the negative half-space of all cluster triangles by construction |
| 834 | bounds.cone_apex[0] = center[0] - axis[0] * maxt; |
| 835 | bounds.cone_apex[1] = center[1] - axis[1] * maxt; |
| 836 | bounds.cone_apex[2] = center[2] - axis[2] * maxt; |
| 837 | |
| 838 | // note: this axis is the axis of the normal cone, but our test for perspective camera effectively negates the axis |
| 839 | bounds.cone_axis[0] = axis[0]; |
| 840 | bounds.cone_axis[1] = axis[1]; |
| 841 | bounds.cone_axis[2] = axis[2]; |
| 842 | |
| 843 | // cos(a) for normal cone is mindp; we need to add 90 degrees on both sides and invert the cone |
| 844 | // which gives us -cos(a+90) = -(-sin(a)) = sin(a) = sqrt(1 - cos^2(a)) |
| 845 | bounds.cone_cutoff = sqrtf(1 - mindp * mindp); |
| 846 | |
| 847 | // quantize axis & cutoff to 8-bit SNORM format |
| 848 | bounds.cone_axis_s8[0] = (signed char)(meshopt_quantizeSnorm(bounds.cone_axis[0], 8)); |
| 849 | bounds.cone_axis_s8[1] = (signed char)(meshopt_quantizeSnorm(bounds.cone_axis[1], 8)); |
| 850 | bounds.cone_axis_s8[2] = (signed char)(meshopt_quantizeSnorm(bounds.cone_axis[2], 8)); |
| 851 | |
| 852 | // for the 8-bit test to be conservative, we need to adjust the cutoff by measuring the max. error |
| 853 | float cone_axis_s8_e0 = fabsf(bounds.cone_axis_s8[0] / 127.f - bounds.cone_axis[0]); |
| 854 | float cone_axis_s8_e1 = fabsf(bounds.cone_axis_s8[1] / 127.f - bounds.cone_axis[1]); |
| 855 | float cone_axis_s8_e2 = fabsf(bounds.cone_axis_s8[2] / 127.f - bounds.cone_axis[2]); |
| 856 | |
| 857 | // note that we need to round this up instead of rounding to nearest, hence +1 |
| 858 | int cone_cutoff_s8 = int(127 * (bounds.cone_cutoff + cone_axis_s8_e0 + cone_axis_s8_e1 + cone_axis_s8_e2) + 1); |
| 859 | |
| 860 | bounds.cone_cutoff_s8 = (cone_cutoff_s8 > 127) ? 127 : (signed char)(cone_cutoff_s8); |
| 861 | |
| 862 | return bounds; |
| 863 | } |
| 864 | |
| 865 | 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) |
| 866 | { |
| 867 | using namespace meshopt; |
| 868 | |
| 869 | assert(triangle_count <= kMeshletMaxTriangles); |
| 870 | assert(vertex_positions_stride >= 12 && vertex_positions_stride <= 256); |
| 871 | assert(vertex_positions_stride % sizeof(float) == 0); |
| 872 | |
| 873 | unsigned int indices[kMeshletMaxTriangles * 3]; |
| 874 | |
| 875 | for (size_t i = 0; i < triangle_count * 3; ++i) |
| 876 | { |
| 877 | unsigned int index = meshlet_vertices[meshlet_triangles[i]]; |
| 878 | assert(index < vertex_count); |
| 879 | |
| 880 | indices[i] = index; |
| 881 | } |
| 882 | |
| 883 | return meshopt_computeClusterBounds(indices, triangle_count * 3, vertex_positions, vertex_count, vertex_positions_stride); |
| 884 | } |
| 885 | |