77a045e902
-Reworked how meshes are treated by importer by using EditorSceneImporterMesh and EditorSceneImporterMeshNode. Instead of Mesh and MeshInstance, this allows more efficient processing of meshes before they are actually registered in the RenderingServer. -Integrated MeshOptimizer -Reworked internals of SurfaceTool to use arrays, making it more performant and easy to run optimizatons on.
334 lines
11 KiB
C++
334 lines
11 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 <math.h>
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#include <string.h>
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// This work is based on:
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// Pedro Sander, Diego Nehab and Joshua Barczak. Fast Triangle Reordering for Vertex Locality and Reduced Overdraw. 2007
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namespace meshopt
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{
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static void calculateSortData(float* sort_data, const unsigned int* indices, size_t index_count, const float* vertex_positions, size_t vertex_positions_stride, const unsigned int* clusters, size_t cluster_count)
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{
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size_t vertex_stride_float = vertex_positions_stride / sizeof(float);
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float mesh_centroid[3] = {};
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for (size_t i = 0; i < index_count; ++i)
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{
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const float* p = vertex_positions + vertex_stride_float * indices[i];
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mesh_centroid[0] += p[0];
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mesh_centroid[1] += p[1];
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mesh_centroid[2] += p[2];
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}
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mesh_centroid[0] /= index_count;
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mesh_centroid[1] /= index_count;
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mesh_centroid[2] /= index_count;
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for (size_t cluster = 0; cluster < cluster_count; ++cluster)
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{
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size_t cluster_begin = clusters[cluster] * 3;
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size_t cluster_end = (cluster + 1 < cluster_count) ? clusters[cluster + 1] * 3 : index_count;
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assert(cluster_begin < cluster_end);
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float cluster_area = 0;
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float cluster_centroid[3] = {};
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float cluster_normal[3] = {};
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for (size_t i = cluster_begin; i < cluster_end; i += 3)
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{
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const float* p0 = vertex_positions + vertex_stride_float * indices[i + 0];
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const float* p1 = vertex_positions + vertex_stride_float * indices[i + 1];
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const float* p2 = vertex_positions + vertex_stride_float * indices[i + 2];
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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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cluster_centroid[0] += (p0[0] + p1[0] + p2[0]) * (area / 3);
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cluster_centroid[1] += (p0[1] + p1[1] + p2[1]) * (area / 3);
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cluster_centroid[2] += (p0[2] + p1[2] + p2[2]) * (area / 3);
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cluster_normal[0] += normalx;
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cluster_normal[1] += normaly;
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cluster_normal[2] += normalz;
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cluster_area += area;
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}
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float inv_cluster_area = cluster_area == 0 ? 0 : 1 / cluster_area;
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cluster_centroid[0] *= inv_cluster_area;
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cluster_centroid[1] *= inv_cluster_area;
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cluster_centroid[2] *= inv_cluster_area;
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float cluster_normal_length = sqrtf(cluster_normal[0] * cluster_normal[0] + cluster_normal[1] * cluster_normal[1] + cluster_normal[2] * cluster_normal[2]);
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float inv_cluster_normal_length = cluster_normal_length == 0 ? 0 : 1 / cluster_normal_length;
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cluster_normal[0] *= inv_cluster_normal_length;
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cluster_normal[1] *= inv_cluster_normal_length;
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cluster_normal[2] *= inv_cluster_normal_length;
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float centroid_vector[3] = {cluster_centroid[0] - mesh_centroid[0], cluster_centroid[1] - mesh_centroid[1], cluster_centroid[2] - mesh_centroid[2]};
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sort_data[cluster] = centroid_vector[0] * cluster_normal[0] + centroid_vector[1] * cluster_normal[1] + centroid_vector[2] * cluster_normal[2];
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}
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}
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static void calculateSortOrderRadix(unsigned int* sort_order, const float* sort_data, unsigned short* sort_keys, size_t cluster_count)
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{
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// compute sort data bounds and renormalize, using fixed point snorm
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float sort_data_max = 1e-3f;
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for (size_t i = 0; i < cluster_count; ++i)
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{
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float dpa = fabsf(sort_data[i]);
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sort_data_max = (sort_data_max < dpa) ? dpa : sort_data_max;
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}
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const int sort_bits = 11;
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for (size_t i = 0; i < cluster_count; ++i)
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{
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// note that we flip distribution since high dot product should come first
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float sort_key = 0.5f - 0.5f * (sort_data[i] / sort_data_max);
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sort_keys[i] = meshopt_quantizeUnorm(sort_key, sort_bits) & ((1 << sort_bits) - 1);
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}
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// fill histogram for counting sort
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unsigned int histogram[1 << sort_bits];
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memset(histogram, 0, sizeof(histogram));
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for (size_t i = 0; i < cluster_count; ++i)
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{
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histogram[sort_keys[i]]++;
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}
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// compute offsets based on histogram data
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size_t histogram_sum = 0;
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for (size_t i = 0; i < 1 << sort_bits; ++i)
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{
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size_t count = histogram[i];
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histogram[i] = unsigned(histogram_sum);
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histogram_sum += count;
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}
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assert(histogram_sum == cluster_count);
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// compute sort order based on offsets
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for (size_t i = 0; i < cluster_count; ++i)
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{
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sort_order[histogram[sort_keys[i]]++] = unsigned(i);
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}
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}
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static unsigned int updateCache(unsigned int a, unsigned int b, unsigned int c, unsigned int cache_size, unsigned int* cache_timestamps, unsigned int& timestamp)
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{
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unsigned int cache_misses = 0;
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// if vertex is not in cache, put it in cache
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if (timestamp - cache_timestamps[a] > cache_size)
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{
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cache_timestamps[a] = timestamp++;
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cache_misses++;
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}
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if (timestamp - cache_timestamps[b] > cache_size)
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{
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cache_timestamps[b] = timestamp++;
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cache_misses++;
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}
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if (timestamp - cache_timestamps[c] > cache_size)
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{
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cache_timestamps[c] = timestamp++;
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cache_misses++;
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}
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return cache_misses;
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}
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static size_t generateHardBoundaries(unsigned int* destination, const unsigned int* indices, size_t index_count, size_t vertex_count, unsigned int cache_size, unsigned int* cache_timestamps)
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{
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memset(cache_timestamps, 0, vertex_count * sizeof(unsigned int));
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unsigned int timestamp = cache_size + 1;
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size_t face_count = index_count / 3;
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size_t result = 0;
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for (size_t i = 0; i < face_count; ++i)
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{
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unsigned int m = updateCache(indices[i * 3 + 0], indices[i * 3 + 1], indices[i * 3 + 2], cache_size, &cache_timestamps[0], timestamp);
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// when all three vertices are not in the cache it's usually relatively safe to assume that this is a new patch in the mesh
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// that is disjoint from previous vertices; sometimes it might come back to reference existing vertices but that frequently
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// suggests an inefficiency in the vertex cache optimization algorithm
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// usually the first triangle has 3 misses unless it's degenerate - thus we make sure the first cluster always starts with 0
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if (i == 0 || m == 3)
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{
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destination[result++] = unsigned(i);
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}
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}
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assert(result <= index_count / 3);
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return result;
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}
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static size_t generateSoftBoundaries(unsigned int* destination, const unsigned int* indices, size_t index_count, size_t vertex_count, const unsigned int* clusters, size_t cluster_count, unsigned int cache_size, float threshold, unsigned int* cache_timestamps)
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{
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memset(cache_timestamps, 0, vertex_count * sizeof(unsigned int));
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unsigned int timestamp = 0;
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size_t result = 0;
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for (size_t it = 0; it < cluster_count; ++it)
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{
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size_t start = clusters[it];
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size_t end = (it + 1 < cluster_count) ? clusters[it + 1] : index_count / 3;
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assert(start < end);
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// reset cache
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timestamp += cache_size + 1;
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// measure cluster ACMR
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unsigned int cluster_misses = 0;
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for (size_t i = start; i < end; ++i)
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{
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unsigned int m = updateCache(indices[i * 3 + 0], indices[i * 3 + 1], indices[i * 3 + 2], cache_size, &cache_timestamps[0], timestamp);
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cluster_misses += m;
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}
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float cluster_threshold = threshold * (float(cluster_misses) / float(end - start));
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// first cluster always starts from the hard cluster boundary
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destination[result++] = unsigned(start);
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// reset cache
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timestamp += cache_size + 1;
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unsigned int running_misses = 0;
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unsigned int running_faces = 0;
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for (size_t i = start; i < end; ++i)
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{
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unsigned int m = updateCache(indices[i * 3 + 0], indices[i * 3 + 1], indices[i * 3 + 2], cache_size, &cache_timestamps[0], timestamp);
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running_misses += m;
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running_faces += 1;
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if (float(running_misses) / float(running_faces) <= cluster_threshold)
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{
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// we have reached the target ACMR with the current triangle so we need to start a new cluster on the next one
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// note that this may mean that we add 'end` to destination for the last triangle, which will imply that the last
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// cluster is empty; however, the 'pop_back' after the loop will clean it up
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destination[result++] = unsigned(i + 1);
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// reset cache
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timestamp += cache_size + 1;
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running_misses = 0;
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running_faces = 0;
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}
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}
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// each time we reach the target ACMR we flush the cluster
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// this means that the last cluster is by definition not very good - there are frequent cases where we are left with a few triangles
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// in the last cluster, producing a very bad ACMR and significantly penalizing the overall results
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// thus we remove the last cluster boundary, merging the last complete cluster with the last incomplete one
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// there are sometimes cases when the last cluster is actually good enough - in which case the code above would have added 'end'
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// to the cluster boundary array which we need to remove anyway - this code will do that automatically
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if (destination[result - 1] != start)
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{
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result--;
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}
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}
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assert(result >= cluster_count);
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assert(result <= index_count / 3);
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return result;
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}
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} // namespace meshopt
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void meshopt_optimizeOverdraw(unsigned int* destination, const unsigned int* indices, size_t index_count, const float* vertex_positions, size_t vertex_count, size_t vertex_positions_stride, float threshold)
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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 > 0 && vertex_positions_stride <= 256);
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assert(vertex_positions_stride % sizeof(float) == 0);
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meshopt_Allocator allocator;
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// guard for empty meshes
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if (index_count == 0 || vertex_count == 0)
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return;
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// support in-place optimization
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if (destination == indices)
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{
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unsigned int* indices_copy = allocator.allocate<unsigned int>(index_count);
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memcpy(indices_copy, indices, index_count * sizeof(unsigned int));
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indices = indices_copy;
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}
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unsigned int cache_size = 16;
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unsigned int* cache_timestamps = allocator.allocate<unsigned int>(vertex_count);
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// generate hard boundaries from full-triangle cache misses
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unsigned int* hard_clusters = allocator.allocate<unsigned int>(index_count / 3);
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size_t hard_cluster_count = generateHardBoundaries(hard_clusters, indices, index_count, vertex_count, cache_size, cache_timestamps);
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// generate soft boundaries
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unsigned int* soft_clusters = allocator.allocate<unsigned int>(index_count / 3 + 1);
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size_t soft_cluster_count = generateSoftBoundaries(soft_clusters, indices, index_count, vertex_count, hard_clusters, hard_cluster_count, cache_size, threshold, cache_timestamps);
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const unsigned int* clusters = soft_clusters;
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size_t cluster_count = soft_cluster_count;
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// fill sort data
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float* sort_data = allocator.allocate<float>(cluster_count);
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calculateSortData(sort_data, indices, index_count, vertex_positions, vertex_positions_stride, clusters, cluster_count);
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// sort clusters using sort data
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unsigned short* sort_keys = allocator.allocate<unsigned short>(cluster_count);
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unsigned int* sort_order = allocator.allocate<unsigned int>(cluster_count);
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calculateSortOrderRadix(sort_order, sort_data, sort_keys, cluster_count);
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// fill output buffer
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size_t offset = 0;
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for (size_t it = 0; it < cluster_count; ++it)
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{
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unsigned int cluster = sort_order[it];
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assert(cluster < cluster_count);
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size_t cluster_begin = clusters[cluster] * 3;
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size_t cluster_end = (cluster + 1 < cluster_count) ? clusters[cluster + 1] * 3 : index_count;
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assert(cluster_begin < cluster_end);
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memcpy(destination + offset, indices + cluster_begin, (cluster_end - cluster_begin) * sizeof(unsigned int));
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offset += cluster_end - cluster_begin;
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}
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assert(offset == index_count);
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}
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