2432 lines
87 KiB
C++
2432 lines
87 KiB
C++
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// basisu_frontend.cpp
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// Copyright (C) 2019 Binomial LLC. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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// TODO:
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// This code originally supported full ETC1 and ETC1S, so there's some legacy stuff to be cleaned up in here.
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// Add endpoint tiling support (where we force adjacent blocks to use the same endpoints during quantization), for a ~10% or more increase in bitrate at same SSIM. The backend already supports this.
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//
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#include "transcoder/basisu.h"
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#include "basisu_frontend.h"
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#include <unordered_set>
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#include <unordered_map>
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#define BASISU_FRONTEND_VERIFY(c) do { if (!(c)) handle_verify_failure(__LINE__); } while(0)
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namespace basisu
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{
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const uint32_t cMaxCodebookCreationThreads = 8;
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const uint32_t BASISU_MAX_ENDPOINT_REFINEMENT_STEPS = 3;
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const uint32_t BASISU_MAX_SELECTOR_REFINEMENT_STEPS = 3;
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const uint32_t BASISU_ENDPOINT_PARENT_CODEBOOK_SIZE = 16;
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const uint32_t BASISU_SELECTOR_PARENT_CODEBOOK_SIZE = 16;
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// TODO - How to handle internal verifies in the basisu lib
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static inline void handle_verify_failure(int line)
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{
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fprintf(stderr, "ERROR: basisu_frontend: verify check failed at line %i!\n", line);
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abort();
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}
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bool basisu_frontend::init(const params &p)
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{
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#if 0
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// HACK HACK
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FILE* pFile;
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fopen_s(&pFile, "tv.bin", "rb");
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if (pFile)
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{
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debug_printf("Using tv.bin\n");
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fseek(pFile, 0, SEEK_END);
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uint32_t size = ftell(pFile);
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fseek(pFile, 0, SEEK_SET);
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uint32_t tv = size / sizeof(vec6F_quantizer::training_vec_with_weight);
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std::vector<vec6F_quantizer::training_vec_with_weight> v(tv);
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fread(&v[0], 1, sizeof(v[0]) * tv, pFile);
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for (uint32_t i = 0; i < tv; i++)
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m_endpoint_clusterizer.add_training_vec(v[i].first, v[i].second);
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m_endpoint_clusterizer.generate(16128);
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std::vector<uint_vec> codebook;
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m_endpoint_clusterizer.retrieve(codebook);
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printf("Generated %u entries\n", (uint32_t)codebook.size());
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fclose(pFile);
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exit(0);
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}
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#endif
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if (p.m_use_hybrid_selector_codebooks)
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{
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if (!p.m_pGlobal_sel_codebook)
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{
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assert(0);
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return false;
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}
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}
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debug_printf("basisu_frontend::init: Multithreaded: %u, NumEndpointClusters: %u, NumSelectorClusters: %u, Perceptual: %u, CompressionLevel: %u\n",
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p.m_multithreaded, p.m_max_endpoint_clusters, p.m_max_selector_clusters, p.m_perceptual, p.m_compression_level);
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debug_printf("Global sel codebook pal bits: %u, Global sel codebook mod bits: %u, Use hybrid selector codebook: %u, Hybrid codebook quality thresh: %f\n",
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p.m_num_global_sel_codebook_pal_bits,
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p.m_num_global_sel_codebook_mod_bits,
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p.m_use_hybrid_selector_codebooks,
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p.m_hybrid_codebook_quality_thresh);
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if ((p.m_max_endpoint_clusters < 1) || (p.m_max_endpoint_clusters > cMaxEndpointClusters))
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return false;
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if ((p.m_max_selector_clusters < 1) || (p.m_max_selector_clusters > cMaxSelectorClusters))
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return false;
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m_source_blocks.resize(0);
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append_vector(m_source_blocks, p.m_pSource_blocks, p.m_num_source_blocks);
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m_params = p;
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m_encoded_blocks.resize(m_params.m_num_source_blocks);
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memset(&m_encoded_blocks[0], 0, m_encoded_blocks.size() * sizeof(m_encoded_blocks[0]));
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m_num_endpoint_codebook_iterations = 1;
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m_num_selector_codebook_iterations = 1;
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switch (p.m_compression_level)
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{
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case 0:
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{
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m_endpoint_refinement = false;
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m_use_hierarchical_endpoint_codebooks = true;
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m_use_hierarchical_selector_codebooks = true;
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break;
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}
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case 1:
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{
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m_endpoint_refinement = true;
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m_use_hierarchical_endpoint_codebooks = true;
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m_use_hierarchical_selector_codebooks = true;
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break;
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}
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case 2:
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{
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m_endpoint_refinement = true;
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m_use_hierarchical_endpoint_codebooks = false;
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m_use_hierarchical_selector_codebooks = false;
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break;
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}
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case 3:
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{
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m_endpoint_refinement = true;
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m_use_hierarchical_endpoint_codebooks = true;
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m_use_hierarchical_selector_codebooks = true;
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m_num_endpoint_codebook_iterations = BASISU_MAX_ENDPOINT_REFINEMENT_STEPS;
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m_num_selector_codebook_iterations = BASISU_MAX_ENDPOINT_REFINEMENT_STEPS;
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break;
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}
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case 4:
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{
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m_endpoint_refinement = true;
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m_use_hierarchical_endpoint_codebooks = false;
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m_use_hierarchical_selector_codebooks = false;
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m_num_endpoint_codebook_iterations = BASISU_MAX_ENDPOINT_REFINEMENT_STEPS;
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m_num_selector_codebook_iterations = BASISU_MAX_ENDPOINT_REFINEMENT_STEPS;
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break;
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}
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case 5:
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{
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m_endpoint_refinement = true;
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m_use_hierarchical_endpoint_codebooks = false;
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m_use_hierarchical_selector_codebooks = false;
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m_num_endpoint_codebook_iterations = BASISU_MAX_ENDPOINT_REFINEMENT_STEPS*2;
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m_num_selector_codebook_iterations = BASISU_MAX_ENDPOINT_REFINEMENT_STEPS*2;
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break;
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}
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}
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if (m_params.m_disable_hierarchical_endpoint_codebooks)
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m_use_hierarchical_endpoint_codebooks = false;
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debug_printf("Endpoint refinement: %u, Hierarchical endpoint codebooks: %u, Hierarchical selector codebooks: %u, Endpoint codebook iters: %u, Selector codebook iters: %u\n",
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m_endpoint_refinement, m_use_hierarchical_endpoint_codebooks, m_use_hierarchical_selector_codebooks, m_num_endpoint_codebook_iterations, m_num_selector_codebook_iterations);
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return true;
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}
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bool basisu_frontend::compress()
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{
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debug_printf("basisu_frontend::compress\n");
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m_total_blocks = m_params.m_num_source_blocks;
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m_total_pixels = m_total_blocks * cPixelBlockTotalPixels;
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init_etc1_images();
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init_endpoint_training_vectors();
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generate_endpoint_clusters();
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for (uint32_t refine_endpoint_step = 0; refine_endpoint_step < m_num_endpoint_codebook_iterations; refine_endpoint_step++)
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{
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BASISU_FRONTEND_VERIFY(check_etc1s_constraints());
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if (refine_endpoint_step)
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{
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introduce_new_endpoint_clusters();
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}
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generate_endpoint_codebook(refine_endpoint_step);
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if ((m_params.m_debug_images) && (m_params.m_dump_endpoint_clusterization))
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{
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char buf[256];
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snprintf(buf, sizeof(buf), "endpoint_cluster_vis_pre_%u.png", refine_endpoint_step);
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dump_endpoint_clusterization_visualization(buf, false);
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}
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bool early_out = false;
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if (m_endpoint_refinement)
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{
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//dump_endpoint_clusterization_visualization("endpoint_clusters_before_refinement.png");
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if (!refine_endpoint_clusterization())
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early_out = true;
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if ((m_params.m_tex_type == basist::cBASISTexTypeVideoFrames) && (!refine_endpoint_step) && (m_num_endpoint_codebook_iterations == 1))
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{
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eliminate_redundant_or_empty_endpoint_clusters();
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generate_endpoint_codebook(refine_endpoint_step);
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}
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if ((m_params.m_debug_images) && (m_params.m_dump_endpoint_clusterization))
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{
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char buf[256];
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snprintf(buf, sizeof(buf), "endpoint_cluster_vis_post_%u.png", refine_endpoint_step);
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dump_endpoint_clusterization_visualization(buf, false);
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snprintf(buf, sizeof(buf), "endpoint_cluster_colors_vis_post_%u.png", refine_endpoint_step);
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dump_endpoint_clusterization_visualization(buf, true);
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}
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}
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eliminate_redundant_or_empty_endpoint_clusters();
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if (m_params.m_debug_stats)
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debug_printf("Total endpoint clusters: %u\n", (uint32_t)m_endpoint_clusters.size());
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if (early_out)
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break;
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}
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BASISU_FRONTEND_VERIFY(check_etc1s_constraints());
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generate_block_endpoint_clusters();
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create_initial_packed_texture();
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generate_selector_clusters();
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if (m_use_hierarchical_selector_codebooks)
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compute_selector_clusters_within_each_parent_cluster();
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if (m_params.m_compression_level == 0)
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{
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create_optimized_selector_codebook(0);
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find_optimal_selector_clusters_for_each_block();
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introduce_special_selector_clusters();
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}
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else
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{
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const uint32_t num_refine_selector_steps = m_params.m_pGlobal_sel_codebook ? 1 : m_num_selector_codebook_iterations;
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for (uint32_t refine_selector_steps = 0; refine_selector_steps < num_refine_selector_steps; refine_selector_steps++)
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{
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create_optimized_selector_codebook(refine_selector_steps);
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find_optimal_selector_clusters_for_each_block();
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introduce_special_selector_clusters();
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if ((m_params.m_compression_level >= 3) || (m_params.m_tex_type == basist::cBASISTexTypeVideoFrames))
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{
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if (!refine_block_endpoints_given_selectors())
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break;
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}
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}
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}
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optimize_selector_codebook();
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if (m_params.m_debug_stats)
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debug_printf("Total selector clusters: %u\n", (uint32_t)m_selector_cluster_indices.size());
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finalize();
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if (m_params.m_validate)
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{
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if (!validate_output())
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return false;
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}
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debug_printf("basisu_frontend::compress: Done\n");
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return true;
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}
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void basisu_frontend::introduce_special_selector_clusters()
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{
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debug_printf("introduce_special_selector_clusters\n");
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if (m_params.m_pGlobal_sel_codebook)
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return;
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uint32_t total_blocks_relocated = 0;
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const uint32_t initial_selector_clusters = (uint32_t)m_selector_cluster_indices.size();
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bool_vec block_relocated_flags(m_total_blocks);
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// Make sure the selector codebook always has pure flat blocks for each possible selector, to avoid obvious artifacts.
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// optimize_selector_codebook() will clean up any redundant clusters we create here.
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for (uint32_t sel = 0; sel < 4; sel++)
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{
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etc_block blk;
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clear_obj(blk);
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for (uint32_t j = 0; j < 16; j++)
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blk.set_selector(j & 3, j >> 2, sel);
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int k;
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for (k = 0; k < (int)m_optimized_cluster_selectors.size(); k++)
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if (m_optimized_cluster_selectors[k].get_raw_selector_bits() == blk.get_raw_selector_bits())
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break;
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if (k < (int)m_optimized_cluster_selectors.size())
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continue;
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debug_printf("Introducing sel %u\n", sel);
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const uint32_t new_selector_cluster_index = (uint32_t)m_optimized_cluster_selectors.size();
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m_optimized_cluster_selectors.push_back(blk);
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vector_ensure_element_is_valid(m_selector_cluster_indices, new_selector_cluster_index);
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for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
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{
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if (m_orig_encoded_blocks[block_index].get_raw_selector_bits() != blk.get_raw_selector_bits())
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continue;
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// See if using flat selectors actually decreases the block's error.
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const uint32_t old_selector_cluster_index = m_block_selector_cluster_index[block_index];
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etc_block cur_blk;
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const uint32_t endpoint_cluster_index = get_subblock_endpoint_cluster_index(block_index, 0);
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cur_blk.set_block_color5_etc1s(get_endpoint_cluster_unscaled_color(endpoint_cluster_index, false));
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cur_blk.set_inten_tables_etc1s(get_endpoint_cluster_inten_table(endpoint_cluster_index, false));
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cur_blk.set_raw_selector_bits(get_selector_cluster_selector_bits(old_selector_cluster_index).get_raw_selector_bits());
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const uint64_t cur_err = cur_blk.evaluate_etc1_error(get_source_pixel_block(block_index).get_ptr(), m_params.m_perceptual);
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|
||
|
|
cur_blk.set_raw_selector_bits(blk.get_raw_selector_bits());
|
||
|
|
|
||
|
|
const uint64_t new_err = cur_blk.evaluate_etc1_error(get_source_pixel_block(block_index).get_ptr(), m_params.m_perceptual);
|
||
|
|
|
||
|
|
if (new_err >= cur_err)
|
||
|
|
continue;
|
||
|
|
|
||
|
|
// Change the block to use the new cluster
|
||
|
|
m_block_selector_cluster_index[block_index] = new_selector_cluster_index;
|
||
|
|
|
||
|
|
m_selector_cluster_indices[new_selector_cluster_index].push_back(block_index);
|
||
|
|
|
||
|
|
block_relocated_flags[block_index] = true;
|
||
|
|
|
||
|
|
#if 0
|
||
|
|
int j = vector_find(m_selector_cluster_indices[old_selector_cluster_index], block_index);
|
||
|
|
if (j >= 0)
|
||
|
|
m_selector_cluster_indices[old_selector_cluster_index].erase(m_selector_cluster_indices[old_selector_cluster_index].begin() + j);
|
||
|
|
#endif
|
||
|
|
|
||
|
|
total_blocks_relocated++;
|
||
|
|
|
||
|
|
m_encoded_blocks[block_index].set_raw_selector_bits(blk.get_raw_selector_bits());
|
||
|
|
|
||
|
|
} // block_index
|
||
|
|
|
||
|
|
} // sel
|
||
|
|
|
||
|
|
if (total_blocks_relocated)
|
||
|
|
{
|
||
|
|
debug_printf("Fixing selector codebook\n");
|
||
|
|
|
||
|
|
for (int selector_cluster_index = 0; selector_cluster_index < (int)initial_selector_clusters; selector_cluster_index++)
|
||
|
|
{
|
||
|
|
uint_vec& block_indices = m_selector_cluster_indices[selector_cluster_index];
|
||
|
|
|
||
|
|
uint32_t dst_ofs = 0;
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < block_indices.size(); i++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = block_indices[i];
|
||
|
|
if (!block_relocated_flags[block_index])
|
||
|
|
block_indices[dst_ofs++] = block_index;
|
||
|
|
}
|
||
|
|
|
||
|
|
block_indices.resize(dst_ofs);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("Total blocks relocated to new flat selector clusters: %u\n", total_blocks_relocated);
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::optimize_selector_codebook()
|
||
|
|
{
|
||
|
|
debug_printf("optimize_selector_codebook\n");
|
||
|
|
|
||
|
|
const uint32_t orig_total_selector_clusters = (uint32_t)m_optimized_cluster_selectors.size();
|
||
|
|
|
||
|
|
bool_vec selector_cluster_was_used(m_optimized_cluster_selectors.size());
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
selector_cluster_was_used[m_block_selector_cluster_index[i]] = true;
|
||
|
|
|
||
|
|
int_vec old_to_new(m_optimized_cluster_selectors.size());
|
||
|
|
int_vec new_to_old;
|
||
|
|
uint32_t total_new_entries = 0;
|
||
|
|
|
||
|
|
std::unordered_map<uint32_t, uint32_t> selector_hashmap;
|
||
|
|
|
||
|
|
for (int i = 0; i < static_cast<int>(m_optimized_cluster_selectors.size()); i++)
|
||
|
|
{
|
||
|
|
if (!selector_cluster_was_used[i])
|
||
|
|
{
|
||
|
|
old_to_new[i] = -1;
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
|
||
|
|
const uint32_t raw_selector_bits = m_optimized_cluster_selectors[i].get_raw_selector_bits();
|
||
|
|
|
||
|
|
auto find_res = selector_hashmap.insert(std::make_pair(raw_selector_bits, total_new_entries));
|
||
|
|
if (!find_res.second)
|
||
|
|
{
|
||
|
|
old_to_new[i] = (find_res.first)->second;
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
|
||
|
|
old_to_new[i] = total_new_entries++;
|
||
|
|
new_to_old.push_back(i);
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_block_selector_cluster_index.size(); i++)
|
||
|
|
{
|
||
|
|
BASISU_FRONTEND_VERIFY((old_to_new[m_block_selector_cluster_index[i]] >= 0) && (old_to_new[m_block_selector_cluster_index[i]] < (int)total_new_entries));
|
||
|
|
m_block_selector_cluster_index[i] = old_to_new[m_block_selector_cluster_index[i]];
|
||
|
|
}
|
||
|
|
|
||
|
|
std::vector<etc_block> new_optimized_cluster_selectors(m_optimized_cluster_selectors.size() ? total_new_entries : 0);
|
||
|
|
basist::etc1_global_selector_codebook_entry_id_vec new_optimized_cluster_selector_global_cb_ids(m_optimized_cluster_selector_global_cb_ids.size() ? total_new_entries : 0);
|
||
|
|
std::vector<uint_vec> new_selector_cluster_indices(m_selector_cluster_indices.size() ? total_new_entries : 0);
|
||
|
|
bool_vec new_selector_cluster_uses_global_cb(m_selector_cluster_uses_global_cb.size() ? total_new_entries : 0);
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < total_new_entries; i++)
|
||
|
|
{
|
||
|
|
if (m_optimized_cluster_selectors.size())
|
||
|
|
new_optimized_cluster_selectors[i] = m_optimized_cluster_selectors[new_to_old[i]];
|
||
|
|
|
||
|
|
if (m_optimized_cluster_selector_global_cb_ids.size())
|
||
|
|
new_optimized_cluster_selector_global_cb_ids[i] = m_optimized_cluster_selector_global_cb_ids[new_to_old[i]];
|
||
|
|
|
||
|
|
if (m_selector_cluster_indices.size())
|
||
|
|
new_selector_cluster_indices[i] = m_selector_cluster_indices[new_to_old[i]];
|
||
|
|
|
||
|
|
if (m_selector_cluster_uses_global_cb.size())
|
||
|
|
new_selector_cluster_uses_global_cb[i] = m_selector_cluster_uses_global_cb[new_to_old[i]];
|
||
|
|
}
|
||
|
|
|
||
|
|
m_optimized_cluster_selectors.swap(new_optimized_cluster_selectors);
|
||
|
|
m_optimized_cluster_selector_global_cb_ids.swap(new_optimized_cluster_selector_global_cb_ids);
|
||
|
|
m_selector_cluster_indices.swap(new_selector_cluster_indices);
|
||
|
|
m_selector_cluster_uses_global_cb.swap(new_selector_cluster_uses_global_cb);
|
||
|
|
|
||
|
|
debug_printf("optimize_selector_codebook: Before: %u After: %u\n", orig_total_selector_clusters, total_new_entries);
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::init_etc1_images()
|
||
|
|
{
|
||
|
|
debug_printf("basisu_frontend::init_etc1_images\n");
|
||
|
|
|
||
|
|
m_etc1_blocks_etc1s.resize(m_total_blocks);
|
||
|
|
|
||
|
|
const uint32_t N = 4096;
|
||
|
|
for (uint32_t block_index_iter = 0; block_index_iter < m_total_blocks; block_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = block_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>(m_total_blocks, first_index + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index] {
|
||
|
|
|
||
|
|
for (uint32_t block_index = first_index; block_index < last_index; block_index++)
|
||
|
|
{
|
||
|
|
const pixel_block &source_blk = get_source_pixel_block(block_index);
|
||
|
|
|
||
|
|
etc1_optimizer optimizer;
|
||
|
|
etc1_optimizer::params optimizer_params;
|
||
|
|
etc1_optimizer::results optimizer_results;
|
||
|
|
|
||
|
|
if (m_params.m_compression_level == 0)
|
||
|
|
optimizer_params.m_quality = cETCQualityFast;
|
||
|
|
else if (m_params.m_compression_level == BASISU_MAX_COMPRESSION_LEVEL)
|
||
|
|
optimizer_params.m_quality = cETCQualityUber;
|
||
|
|
|
||
|
|
optimizer_params.m_num_src_pixels = 16;
|
||
|
|
optimizer_params.m_pSrc_pixels = source_blk.get_ptr();
|
||
|
|
optimizer_params.m_perceptual = m_params.m_perceptual;
|
||
|
|
|
||
|
|
uint8_t selectors[16];
|
||
|
|
optimizer_results.m_pSelectors = selectors;
|
||
|
|
optimizer_results.m_n = 16;
|
||
|
|
|
||
|
|
optimizer.init(optimizer_params, optimizer_results);
|
||
|
|
optimizer.compute();
|
||
|
|
|
||
|
|
etc_block &blk = m_etc1_blocks_etc1s[block_index];
|
||
|
|
|
||
|
|
memset(&blk, 0, sizeof(blk));
|
||
|
|
blk.set_block_color5_etc1s(optimizer_results.m_block_color_unscaled);
|
||
|
|
blk.set_inten_tables_etc1s(optimizer_results.m_block_inten_table);
|
||
|
|
blk.set_flip_bit(true);
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
blk.set_selector(x, y, selectors[x + y * 4]);
|
||
|
|
}
|
||
|
|
|
||
|
|
} );
|
||
|
|
}
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::init_endpoint_training_vectors()
|
||
|
|
{
|
||
|
|
debug_printf("init_endpoint_training_vectors\n");
|
||
|
|
|
||
|
|
vec6F_quantizer::array_of_weighted_training_vecs &training_vecs = m_endpoint_clusterizer.get_training_vecs();
|
||
|
|
|
||
|
|
training_vecs.resize(m_total_blocks * 2);
|
||
|
|
|
||
|
|
const uint32_t N = 16384;
|
||
|
|
for (uint32_t block_index_iter = 0; block_index_iter < m_total_blocks; block_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = block_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>(m_total_blocks, first_index + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &training_vecs] {
|
||
|
|
|
||
|
|
for (uint32_t block_index = first_index; block_index < last_index; block_index++)
|
||
|
|
{
|
||
|
|
const etc_block &blk = m_etc1_blocks_etc1s[block_index];
|
||
|
|
|
||
|
|
color_rgba block_colors[2];
|
||
|
|
blk.get_block_low_high_colors(block_colors, 0);
|
||
|
|
|
||
|
|
vec6F v;
|
||
|
|
v[0] = block_colors[0].r * (1.0f / 255.0f);
|
||
|
|
v[1] = block_colors[0].g * (1.0f / 255.0f);
|
||
|
|
v[2] = block_colors[0].b * (1.0f / 255.0f);
|
||
|
|
v[3] = block_colors[1].r * (1.0f / 255.0f);
|
||
|
|
v[4] = block_colors[1].g * (1.0f / 255.0f);
|
||
|
|
v[5] = block_colors[1].b * (1.0f / 255.0f);
|
||
|
|
|
||
|
|
training_vecs[block_index * 2 + 0] = std::make_pair(v, 1);
|
||
|
|
training_vecs[block_index * 2 + 1] = std::make_pair(v, 1);
|
||
|
|
|
||
|
|
} // block_index;
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // block_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::generate_endpoint_clusters()
|
||
|
|
{
|
||
|
|
debug_printf("Begin endpoint quantization\n");
|
||
|
|
|
||
|
|
const uint32_t parent_codebook_size = (m_params.m_max_endpoint_clusters >= 256) ? BASISU_ENDPOINT_PARENT_CODEBOOK_SIZE : 0;
|
||
|
|
uint32_t max_threads = 0;
|
||
|
|
max_threads = m_params.m_multithreaded ? minimum<int>(std::thread::hardware_concurrency(), cMaxCodebookCreationThreads) : 0;
|
||
|
|
|
||
|
|
debug_printf("Using %u threads to create codebook\n", max_threads);
|
||
|
|
bool status = generate_hierarchical_codebook_threaded(m_endpoint_clusterizer,
|
||
|
|
m_params.m_max_endpoint_clusters, m_use_hierarchical_endpoint_codebooks ? parent_codebook_size : 0,
|
||
|
|
m_endpoint_clusters,
|
||
|
|
m_endpoint_parent_clusters,
|
||
|
|
max_threads, m_params.m_pJob_pool);
|
||
|
|
BASISU_FRONTEND_VERIFY(status);
|
||
|
|
|
||
|
|
if (m_use_hierarchical_endpoint_codebooks)
|
||
|
|
{
|
||
|
|
if (!m_endpoint_parent_clusters.size())
|
||
|
|
{
|
||
|
|
m_endpoint_parent_clusters.resize(0);
|
||
|
|
m_endpoint_parent_clusters.resize(1);
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
{
|
||
|
|
m_endpoint_parent_clusters[0].push_back(i*2);
|
||
|
|
m_endpoint_parent_clusters[0].push_back(i*2+1);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
BASISU_ASSUME(BASISU_ENDPOINT_PARENT_CODEBOOK_SIZE <= UINT8_MAX);
|
||
|
|
|
||
|
|
m_block_parent_endpoint_cluster.resize(0);
|
||
|
|
m_block_parent_endpoint_cluster.resize(m_total_blocks);
|
||
|
|
vector_set_all(m_block_parent_endpoint_cluster, 0xFF);
|
||
|
|
for (uint32_t parent_cluster_index = 0; parent_cluster_index < m_endpoint_parent_clusters.size(); parent_cluster_index++)
|
||
|
|
{
|
||
|
|
const uint_vec &cluster = m_endpoint_parent_clusters[parent_cluster_index];
|
||
|
|
for (uint32_t j = 0; j < cluster.size(); j++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster[j] >> 1;
|
||
|
|
m_block_parent_endpoint_cluster[block_index] = static_cast<uint8_t>(parent_cluster_index);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
{
|
||
|
|
BASISU_FRONTEND_VERIFY(m_block_parent_endpoint_cluster[i] != 0xFF);
|
||
|
|
}
|
||
|
|
|
||
|
|
// Ensure that all the blocks within each cluster are all in the same parent cluster, or something is very wrong.
|
||
|
|
for (uint32_t cluster_index = 0; cluster_index < m_endpoint_clusters.size(); cluster_index++)
|
||
|
|
{
|
||
|
|
const uint_vec &cluster = m_endpoint_clusters[cluster_index];
|
||
|
|
|
||
|
|
uint32_t parent_cluster_index = 0;
|
||
|
|
for (uint32_t j = 0; j < cluster.size(); j++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster[j] >> 1;
|
||
|
|
if (!j)
|
||
|
|
{
|
||
|
|
parent_cluster_index = m_block_parent_endpoint_cluster[block_index];
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
BASISU_FRONTEND_VERIFY(m_block_parent_endpoint_cluster[block_index] == parent_cluster_index);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (m_params.m_debug_stats)
|
||
|
|
debug_printf("Total endpoint clusters: %u, parent clusters: %u\n", (uint32_t)m_endpoint_clusters.size(), (uint32_t)m_endpoint_parent_clusters.size());
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::generate_block_endpoint_clusters()
|
||
|
|
{
|
||
|
|
m_block_endpoint_clusters_indices.resize(m_total_blocks);
|
||
|
|
|
||
|
|
for (int cluster_index = 0; cluster_index < static_cast<int>(m_endpoint_clusters.size()); cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_indices = m_endpoint_clusters[cluster_index];
|
||
|
|
|
||
|
|
for (uint32_t cluster_indices_iter = 0; cluster_indices_iter < cluster_indices.size(); cluster_indices_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_indices[cluster_indices_iter] >> 1;
|
||
|
|
const uint32_t subblock_index = cluster_indices[cluster_indices_iter] & 1;
|
||
|
|
|
||
|
|
m_block_endpoint_clusters_indices[block_index][subblock_index] = cluster_index;
|
||
|
|
|
||
|
|
} // cluster_indices_iter
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
|
||
|
|
{
|
||
|
|
uint32_t cluster_0 = m_block_endpoint_clusters_indices[block_index][0];
|
||
|
|
uint32_t cluster_1 = m_block_endpoint_clusters_indices[block_index][1];
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster_0 == cluster_1);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::compute_endpoint_clusters_within_each_parent_cluster()
|
||
|
|
{
|
||
|
|
generate_block_endpoint_clusters();
|
||
|
|
|
||
|
|
m_endpoint_clusters_within_each_parent_cluster.resize(0);
|
||
|
|
m_endpoint_clusters_within_each_parent_cluster.resize(m_endpoint_parent_clusters.size());
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t cluster_index = m_block_endpoint_clusters_indices[block_index][0];
|
||
|
|
const uint32_t parent_cluster_index = m_block_parent_endpoint_cluster[block_index];
|
||
|
|
|
||
|
|
m_endpoint_clusters_within_each_parent_cluster[parent_cluster_index].push_back(cluster_index);
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_endpoint_clusters_within_each_parent_cluster.size(); i++)
|
||
|
|
{
|
||
|
|
uint_vec &cluster_indices = m_endpoint_clusters_within_each_parent_cluster[i];
|
||
|
|
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster_indices.size());
|
||
|
|
|
||
|
|
vector_sort(cluster_indices);
|
||
|
|
|
||
|
|
auto last = std::unique(cluster_indices.begin(), cluster_indices.end());
|
||
|
|
cluster_indices.erase(last, cluster_indices.end());
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::compute_endpoint_subblock_error_vec()
|
||
|
|
{
|
||
|
|
m_subblock_endpoint_quant_err_vec.resize(0);
|
||
|
|
|
||
|
|
const uint32_t N = 512;
|
||
|
|
for (uint32_t cluster_index_iter = 0; cluster_index_iter < m_endpoint_clusters.size(); cluster_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = cluster_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>((uint32_t)m_endpoint_clusters.size(), cluster_index_iter + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index] {
|
||
|
|
|
||
|
|
for (uint32_t cluster_index = first_index; cluster_index < last_index; cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_indices = m_endpoint_clusters[cluster_index];
|
||
|
|
|
||
|
|
assert(cluster_indices.size());
|
||
|
|
|
||
|
|
for (uint32_t cluster_indices_iter = 0; cluster_indices_iter < cluster_indices.size(); cluster_indices_iter++)
|
||
|
|
{
|
||
|
|
std::vector<color_rgba> cluster_pixels(8);
|
||
|
|
|
||
|
|
const uint32_t block_index = cluster_indices[cluster_indices_iter] >> 1;
|
||
|
|
const uint32_t subblock_index = cluster_indices[cluster_indices_iter] & 1;
|
||
|
|
|
||
|
|
const bool flipped = true;
|
||
|
|
|
||
|
|
const color_rgba *pSource_block_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
for (uint32_t pixel_index = 0; pixel_index < 8; pixel_index++)
|
||
|
|
{
|
||
|
|
cluster_pixels[pixel_index] = pSource_block_pixels[g_etc1_pixel_indices[flipped][subblock_index][pixel_index]];
|
||
|
|
}
|
||
|
|
|
||
|
|
const endpoint_cluster_etc_params &etc_params = m_endpoint_cluster_etc_params[cluster_index];
|
||
|
|
|
||
|
|
assert(etc_params.m_valid);
|
||
|
|
|
||
|
|
color_rgba block_colors[4];
|
||
|
|
etc_block::get_block_colors5(block_colors, etc_params.m_color_unscaled[0], etc_params.m_inten_table[0], true);
|
||
|
|
|
||
|
|
uint64_t total_err = 0;
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < 8; i++)
|
||
|
|
{
|
||
|
|
const color_rgba &c = cluster_pixels[i];
|
||
|
|
|
||
|
|
uint64_t best_err = UINT64_MAX;
|
||
|
|
//uint32_t best_index = 0;
|
||
|
|
|
||
|
|
for (uint32_t s = 0; s < 4; s++)
|
||
|
|
{
|
||
|
|
uint64_t err = color_distance(m_params.m_perceptual, c, block_colors[s], false);
|
||
|
|
if (err < best_err)
|
||
|
|
{
|
||
|
|
best_err = err;
|
||
|
|
//best_index = s;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
total_err += best_err;
|
||
|
|
}
|
||
|
|
|
||
|
|
subblock_endpoint_quant_err quant_err;
|
||
|
|
quant_err.m_total_err = total_err;
|
||
|
|
quant_err.m_cluster_index = cluster_index;
|
||
|
|
quant_err.m_cluster_subblock_index = cluster_indices_iter;
|
||
|
|
quant_err.m_block_index = block_index;
|
||
|
|
quant_err.m_subblock_index = subblock_index;
|
||
|
|
|
||
|
|
{
|
||
|
|
std::lock_guard<std::mutex> lock(m_lock);
|
||
|
|
|
||
|
|
m_subblock_endpoint_quant_err_vec.push_back(quant_err);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
} // cluster_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
} // cluster_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
vector_sort(m_subblock_endpoint_quant_err_vec);
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::introduce_new_endpoint_clusters()
|
||
|
|
{
|
||
|
|
debug_printf("introduce_new_endpoint_clusters\n");
|
||
|
|
|
||
|
|
generate_block_endpoint_clusters();
|
||
|
|
|
||
|
|
int num_new_endpoint_clusters = m_params.m_max_endpoint_clusters - (uint32_t)m_endpoint_clusters.size();
|
||
|
|
if (num_new_endpoint_clusters <= 0)
|
||
|
|
return;
|
||
|
|
|
||
|
|
compute_endpoint_subblock_error_vec();
|
||
|
|
|
||
|
|
const uint32_t num_orig_endpoint_clusters = (uint32_t)m_endpoint_clusters.size();
|
||
|
|
|
||
|
|
std::unordered_set<uint32_t> training_vector_was_relocated;
|
||
|
|
|
||
|
|
uint_vec cluster_sizes(num_orig_endpoint_clusters);
|
||
|
|
for (uint32_t i = 0; i < num_orig_endpoint_clusters; i++)
|
||
|
|
cluster_sizes[i] = (uint32_t)m_endpoint_clusters[i].size();
|
||
|
|
|
||
|
|
std::unordered_set<uint32_t> ignore_cluster;
|
||
|
|
|
||
|
|
while (num_new_endpoint_clusters)
|
||
|
|
{
|
||
|
|
if (m_subblock_endpoint_quant_err_vec.size() == 0)
|
||
|
|
break;
|
||
|
|
|
||
|
|
subblock_endpoint_quant_err subblock_to_move(m_subblock_endpoint_quant_err_vec.back());
|
||
|
|
|
||
|
|
m_subblock_endpoint_quant_err_vec.pop_back();
|
||
|
|
|
||
|
|
if (unordered_set_contains(ignore_cluster, subblock_to_move.m_cluster_index))
|
||
|
|
continue;
|
||
|
|
|
||
|
|
uint32_t training_vector_index = subblock_to_move.m_block_index * 2 + subblock_to_move.m_subblock_index;
|
||
|
|
|
||
|
|
if (cluster_sizes[subblock_to_move.m_cluster_index] <= 2)
|
||
|
|
continue;
|
||
|
|
|
||
|
|
if (unordered_set_contains(training_vector_was_relocated, training_vector_index))
|
||
|
|
continue;
|
||
|
|
|
||
|
|
if (unordered_set_contains(training_vector_was_relocated, training_vector_index ^ 1))
|
||
|
|
continue;
|
||
|
|
|
||
|
|
#if 0
|
||
|
|
const uint32_t block_index = subblock_to_move.m_block_index;
|
||
|
|
const etc_block& blk = m_etc1_blocks_etc1s[block_index];
|
||
|
|
uint32_t ls, hs;
|
||
|
|
blk.get_selector_range(ls, hs);
|
||
|
|
if (ls != hs)
|
||
|
|
continue;
|
||
|
|
#endif
|
||
|
|
|
||
|
|
const uint32_t new_endpoint_cluster_index = (uint32_t)m_endpoint_clusters.size();
|
||
|
|
|
||
|
|
enlarge_vector(m_endpoint_clusters, 1)->push_back(training_vector_index);
|
||
|
|
enlarge_vector(m_endpoint_cluster_etc_params, 1);
|
||
|
|
|
||
|
|
assert(m_endpoint_clusters.size() == m_endpoint_cluster_etc_params.size());
|
||
|
|
|
||
|
|
training_vector_was_relocated.insert(training_vector_index);
|
||
|
|
|
||
|
|
m_endpoint_clusters.back().push_back(training_vector_index ^ 1);
|
||
|
|
training_vector_was_relocated.insert(training_vector_index ^ 1);
|
||
|
|
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster_sizes[subblock_to_move.m_cluster_index] >= 2);
|
||
|
|
cluster_sizes[subblock_to_move.m_cluster_index] -= 2;
|
||
|
|
|
||
|
|
ignore_cluster.insert(subblock_to_move.m_cluster_index);
|
||
|
|
|
||
|
|
num_new_endpoint_clusters--;
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < num_orig_endpoint_clusters; i++)
|
||
|
|
{
|
||
|
|
uint_vec &cluster_indices = m_endpoint_clusters[i];
|
||
|
|
|
||
|
|
uint_vec new_cluster_indices;
|
||
|
|
for (uint32_t j = 0; j < cluster_indices.size(); j++)
|
||
|
|
{
|
||
|
|
uint32_t training_vector_index = cluster_indices[j];
|
||
|
|
|
||
|
|
if (!unordered_set_contains(training_vector_was_relocated, training_vector_index))
|
||
|
|
new_cluster_indices.push_back(training_vector_index);
|
||
|
|
}
|
||
|
|
|
||
|
|
if (cluster_indices.size() != new_cluster_indices.size())
|
||
|
|
{
|
||
|
|
BASISU_FRONTEND_VERIFY(new_cluster_indices.size() > 0);
|
||
|
|
cluster_indices.swap(new_cluster_indices);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
generate_block_endpoint_clusters();
|
||
|
|
}
|
||
|
|
|
||
|
|
// Given each endpoint cluster, gather all the block pixels which are in that cluster and compute optimized ETC1S endpoints for them.
|
||
|
|
// TODO: Don't optimize endpoint clusters which haven't changed.
|
||
|
|
void basisu_frontend::generate_endpoint_codebook(uint32_t step)
|
||
|
|
{
|
||
|
|
debug_printf("generate_endpoint_codebook\n");
|
||
|
|
|
||
|
|
m_endpoint_cluster_etc_params.resize(m_endpoint_clusters.size());
|
||
|
|
|
||
|
|
const uint32_t N = 128;
|
||
|
|
for (uint32_t cluster_index_iter = 0; cluster_index_iter < m_endpoint_clusters.size(); cluster_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = cluster_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>((uint32_t)m_endpoint_clusters.size(), cluster_index_iter + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, step ] {
|
||
|
|
|
||
|
|
for (uint32_t cluster_index = first_index; cluster_index < last_index; cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_indices = m_endpoint_clusters[cluster_index];
|
||
|
|
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster_indices.size());
|
||
|
|
|
||
|
|
const uint32_t total_pixels = (uint32_t)cluster_indices.size() * 8;
|
||
|
|
|
||
|
|
std::vector<color_rgba> cluster_pixels(total_pixels);
|
||
|
|
|
||
|
|
for (uint32_t cluster_indices_iter = 0; cluster_indices_iter < cluster_indices.size(); cluster_indices_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_indices[cluster_indices_iter] >> 1;
|
||
|
|
const uint32_t subblock_index = cluster_indices[cluster_indices_iter] & 1;
|
||
|
|
|
||
|
|
const bool flipped = true;
|
||
|
|
|
||
|
|
const color_rgba *pBlock_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
for (uint32_t pixel_index = 0; pixel_index < 8; pixel_index++)
|
||
|
|
{
|
||
|
|
const color_rgba &c = pBlock_pixels[g_etc1_pixel_indices[flipped][subblock_index][pixel_index]];
|
||
|
|
cluster_pixels[cluster_indices_iter * 8 + pixel_index] = c;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
endpoint_cluster_etc_params new_subblock_params;
|
||
|
|
|
||
|
|
{
|
||
|
|
etc1_optimizer optimizer;
|
||
|
|
etc1_solution_coordinates solutions[2];
|
||
|
|
|
||
|
|
etc1_optimizer::params cluster_optimizer_params;
|
||
|
|
cluster_optimizer_params.m_num_src_pixels = total_pixels;
|
||
|
|
cluster_optimizer_params.m_pSrc_pixels = &cluster_pixels[0];
|
||
|
|
|
||
|
|
cluster_optimizer_params.m_use_color4 = false;
|
||
|
|
cluster_optimizer_params.m_perceptual = m_params.m_perceptual;
|
||
|
|
|
||
|
|
if (m_params.m_compression_level == 0)
|
||
|
|
cluster_optimizer_params.m_quality = cETCQualityMedium;
|
||
|
|
else if (m_params.m_compression_level == BASISU_MAX_COMPRESSION_LEVEL)
|
||
|
|
cluster_optimizer_params.m_quality = cETCQualityUber;
|
||
|
|
|
||
|
|
etc1_optimizer::results cluster_optimizer_results;
|
||
|
|
|
||
|
|
std::vector<uint8_t> cluster_selectors(total_pixels);
|
||
|
|
cluster_optimizer_results.m_n = total_pixels;
|
||
|
|
cluster_optimizer_results.m_pSelectors = &cluster_selectors[0];
|
||
|
|
|
||
|
|
optimizer.init(cluster_optimizer_params, cluster_optimizer_results);
|
||
|
|
|
||
|
|
optimizer.compute();
|
||
|
|
|
||
|
|
new_subblock_params.m_color_unscaled[0] = cluster_optimizer_results.m_block_color_unscaled;
|
||
|
|
new_subblock_params.m_inten_table[0] = cluster_optimizer_results.m_block_inten_table;
|
||
|
|
new_subblock_params.m_color_error[0] = cluster_optimizer_results.m_error;
|
||
|
|
}
|
||
|
|
|
||
|
|
endpoint_cluster_etc_params &prev_etc_params = m_endpoint_cluster_etc_params[cluster_index];
|
||
|
|
|
||
|
|
bool use_new_subblock_params = false;
|
||
|
|
if ((!step) || (!prev_etc_params.m_valid))
|
||
|
|
use_new_subblock_params = true;
|
||
|
|
else
|
||
|
|
{
|
||
|
|
assert(prev_etc_params.m_valid);
|
||
|
|
|
||
|
|
uint64_t total_prev_err = 0;
|
||
|
|
|
||
|
|
{
|
||
|
|
color_rgba block_colors[4];
|
||
|
|
|
||
|
|
etc_block::get_block_colors5(block_colors, prev_etc_params.m_color_unscaled[0], prev_etc_params.m_inten_table[0], false);
|
||
|
|
|
||
|
|
uint64_t total_err = 0;
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < total_pixels; i++)
|
||
|
|
{
|
||
|
|
const color_rgba &c = cluster_pixels[i];
|
||
|
|
|
||
|
|
uint64_t best_err = UINT64_MAX;
|
||
|
|
//uint32_t best_index = 0;
|
||
|
|
|
||
|
|
for (uint32_t s = 0; s < 4; s++)
|
||
|
|
{
|
||
|
|
uint64_t err = color_distance(m_params.m_perceptual, c, block_colors[s], false);
|
||
|
|
if (err < best_err)
|
||
|
|
{
|
||
|
|
best_err = err;
|
||
|
|
//best_index = s;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
total_err += best_err;
|
||
|
|
}
|
||
|
|
|
||
|
|
total_prev_err += total_err;
|
||
|
|
}
|
||
|
|
|
||
|
|
// See if we should update this cluster's endpoints (if the error has actually fallen)
|
||
|
|
if (total_prev_err > new_subblock_params.m_color_error[0])
|
||
|
|
{
|
||
|
|
use_new_subblock_params = true;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (use_new_subblock_params)
|
||
|
|
{
|
||
|
|
new_subblock_params.m_valid = true;
|
||
|
|
|
||
|
|
prev_etc_params = new_subblock_params;
|
||
|
|
}
|
||
|
|
|
||
|
|
} // cluster_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // cluster_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
}
|
||
|
|
|
||
|
|
bool basisu_frontend::check_etc1s_constraints() const
|
||
|
|
{
|
||
|
|
std::vector<vec2U> block_clusters(m_total_blocks);
|
||
|
|
|
||
|
|
for (int cluster_index = 0; cluster_index < static_cast<int>(m_endpoint_clusters.size()); cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_indices = m_endpoint_clusters[cluster_index];
|
||
|
|
|
||
|
|
for (uint32_t cluster_indices_iter = 0; cluster_indices_iter < cluster_indices.size(); cluster_indices_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_indices[cluster_indices_iter] >> 1;
|
||
|
|
const uint32_t subblock_index = cluster_indices[cluster_indices_iter] & 1;
|
||
|
|
|
||
|
|
block_clusters[block_index][subblock_index] = cluster_index;
|
||
|
|
|
||
|
|
} // cluster_indices_iter
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
{
|
||
|
|
if (block_clusters[i][0] != block_clusters[i][1])
|
||
|
|
return false;
|
||
|
|
}
|
||
|
|
|
||
|
|
return true;
|
||
|
|
}
|
||
|
|
|
||
|
|
uint32_t basisu_frontend::refine_endpoint_clusterization()
|
||
|
|
{
|
||
|
|
debug_printf("refine_endpoint_clusterization\n");
|
||
|
|
|
||
|
|
if (m_use_hierarchical_endpoint_codebooks)
|
||
|
|
compute_endpoint_clusters_within_each_parent_cluster();
|
||
|
|
|
||
|
|
std::vector<vec2U> block_clusters(m_total_blocks);
|
||
|
|
|
||
|
|
for (int cluster_index = 0; cluster_index < static_cast<int>(m_endpoint_clusters.size()); cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_indices = m_endpoint_clusters[cluster_index];
|
||
|
|
|
||
|
|
for (uint32_t cluster_indices_iter = 0; cluster_indices_iter < cluster_indices.size(); cluster_indices_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_indices[cluster_indices_iter] >> 1;
|
||
|
|
const uint32_t subblock_index = cluster_indices[cluster_indices_iter] & 1;
|
||
|
|
|
||
|
|
block_clusters[block_index][subblock_index] = cluster_index;
|
||
|
|
|
||
|
|
} // cluster_indices_iter
|
||
|
|
}
|
||
|
|
|
||
|
|
//----------------------------------------------------------
|
||
|
|
|
||
|
|
// Create a new endpoint clusterization
|
||
|
|
|
||
|
|
uint_vec best_cluster_indices(m_total_blocks);
|
||
|
|
|
||
|
|
const uint32_t N = 1024;
|
||
|
|
for (uint32_t block_index_iter = 0; block_index_iter < m_total_blocks; block_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = block_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>(m_total_blocks, first_index + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &best_cluster_indices, &block_clusters] {
|
||
|
|
|
||
|
|
for (uint32_t block_index = first_index; block_index < last_index; block_index++)
|
||
|
|
{
|
||
|
|
const bool is_flipped = true;
|
||
|
|
|
||
|
|
const uint32_t cluster_index = block_clusters[block_index][0];
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster_index == block_clusters[block_index][1]);
|
||
|
|
|
||
|
|
const color_rgba *subblock_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
const uint32_t num_subblock_pixels = 16;
|
||
|
|
|
||
|
|
uint64_t best_cluster_err = UINT64_MAX;
|
||
|
|
uint32_t best_cluster_index = 0;
|
||
|
|
|
||
|
|
const uint32_t block_parent_endpoint_cluster_index = m_block_parent_endpoint_cluster.size() ? m_block_parent_endpoint_cluster[block_index] : 0;
|
||
|
|
const uint_vec *pCluster_indices = m_endpoint_clusters_within_each_parent_cluster.size() ? &m_endpoint_clusters_within_each_parent_cluster[block_parent_endpoint_cluster_index] : nullptr;
|
||
|
|
|
||
|
|
const uint32_t total_clusters = m_use_hierarchical_endpoint_codebooks ? (uint32_t)pCluster_indices->size() : (uint32_t)m_endpoint_clusters.size();
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < total_clusters; i++)
|
||
|
|
{
|
||
|
|
const uint32_t cluster_iter = m_use_hierarchical_endpoint_codebooks ? (*pCluster_indices)[i] : i;
|
||
|
|
|
||
|
|
color_rgba cluster_etc_base_color(m_endpoint_cluster_etc_params[cluster_iter].m_color_unscaled[0]);
|
||
|
|
uint32_t cluster_etc_inten = m_endpoint_cluster_etc_params[cluster_iter].m_inten_table[0];
|
||
|
|
|
||
|
|
uint64_t total_err = 0;
|
||
|
|
|
||
|
|
const uint32_t low_selector = 0;//subblock_etc_params_vec[j].m_low_selectors[0];
|
||
|
|
const uint32_t high_selector = 3;//subblock_etc_params_vec[j].m_high_selectors[0];
|
||
|
|
color_rgba subblock_colors[4];
|
||
|
|
// Can't assign it here - may result in too much error when selector quant occurs
|
||
|
|
if (cluster_etc_inten > m_endpoint_cluster_etc_params[cluster_index].m_inten_table[0])
|
||
|
|
{
|
||
|
|
total_err = UINT64_MAX;
|
||
|
|
goto skip_cluster;
|
||
|
|
}
|
||
|
|
|
||
|
|
etc_block::get_block_colors5(subblock_colors, cluster_etc_base_color, cluster_etc_inten);
|
||
|
|
|
||
|
|
for (uint32_t p = 0; p < num_subblock_pixels; p++)
|
||
|
|
{
|
||
|
|
uint64_t best_err = UINT64_MAX;
|
||
|
|
|
||
|
|
for (uint32_t r = low_selector; r <= high_selector; r++)
|
||
|
|
{
|
||
|
|
uint64_t err = color_distance(m_params.m_perceptual, subblock_pixels[p], subblock_colors[r], false);
|
||
|
|
best_err = minimum(best_err, err);
|
||
|
|
if (!best_err)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
|
||
|
|
total_err += best_err;
|
||
|
|
if (total_err > best_cluster_err)
|
||
|
|
break;
|
||
|
|
} // p
|
||
|
|
|
||
|
|
skip_cluster:
|
||
|
|
if ((total_err < best_cluster_err) ||
|
||
|
|
((cluster_iter == cluster_index) && (total_err == best_cluster_err)))
|
||
|
|
{
|
||
|
|
best_cluster_err = total_err;
|
||
|
|
best_cluster_index = cluster_iter;
|
||
|
|
|
||
|
|
if (!best_cluster_err)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
} // j
|
||
|
|
|
||
|
|
best_cluster_indices[block_index] = best_cluster_index;
|
||
|
|
|
||
|
|
} // block_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // block_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
std::vector<typename std::vector<uint32_t> > optimized_endpoint_clusters(m_endpoint_clusters.size());
|
||
|
|
uint32_t total_subblocks_reassigned = 0;
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t training_vector_index = block_index * 2 + 0;
|
||
|
|
|
||
|
|
const uint32_t orig_cluster_index = block_clusters[block_index][0];
|
||
|
|
const uint32_t best_cluster_index = best_cluster_indices[block_index];
|
||
|
|
|
||
|
|
optimized_endpoint_clusters[best_cluster_index].push_back(training_vector_index);
|
||
|
|
optimized_endpoint_clusters[best_cluster_index].push_back(training_vector_index + 1);
|
||
|
|
|
||
|
|
if (best_cluster_index != orig_cluster_index)
|
||
|
|
{
|
||
|
|
total_subblocks_reassigned++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("total_subblocks_reassigned: %u\n", total_subblocks_reassigned);
|
||
|
|
|
||
|
|
m_endpoint_clusters = optimized_endpoint_clusters;
|
||
|
|
|
||
|
|
return total_subblocks_reassigned;
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::eliminate_redundant_or_empty_endpoint_clusters()
|
||
|
|
{
|
||
|
|
debug_printf("eliminate_redundant_or_empty_endpoint_clusters\n");
|
||
|
|
|
||
|
|
// Step 1: Sort endpoint clusters by the base colors/intens
|
||
|
|
|
||
|
|
uint_vec sorted_endpoint_cluster_indices(m_endpoint_clusters.size());
|
||
|
|
for (uint32_t i = 0; i < m_endpoint_clusters.size(); i++)
|
||
|
|
sorted_endpoint_cluster_indices[i] = i;
|
||
|
|
|
||
|
|
indirect_sort((uint32_t)m_endpoint_clusters.size(), &sorted_endpoint_cluster_indices[0], &m_endpoint_cluster_etc_params[0]);
|
||
|
|
|
||
|
|
std::vector<std::vector<uint32_t> > new_endpoint_clusters(m_endpoint_clusters.size());
|
||
|
|
std::vector<endpoint_cluster_etc_params> new_subblock_etc_params(m_endpoint_clusters.size());
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_endpoint_clusters.size(); i++)
|
||
|
|
{
|
||
|
|
uint32_t j = sorted_endpoint_cluster_indices[i];
|
||
|
|
new_endpoint_clusters[i] = m_endpoint_clusters[j];
|
||
|
|
new_subblock_etc_params[i] = m_endpoint_cluster_etc_params[j];
|
||
|
|
}
|
||
|
|
|
||
|
|
new_endpoint_clusters.swap(m_endpoint_clusters);
|
||
|
|
new_subblock_etc_params.swap(m_endpoint_cluster_etc_params);
|
||
|
|
|
||
|
|
// Step 2: Eliminate redundant endpoint clusters, or empty endpoint clusters
|
||
|
|
|
||
|
|
new_endpoint_clusters.resize(0);
|
||
|
|
new_subblock_etc_params.resize(0);
|
||
|
|
|
||
|
|
for (int i = 0; i < (int)m_endpoint_clusters.size(); )
|
||
|
|
{
|
||
|
|
if (!m_endpoint_clusters[i].size())
|
||
|
|
{
|
||
|
|
i++;
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
|
||
|
|
int j;
|
||
|
|
for (j = i + 1; j < (int)m_endpoint_clusters.size(); j++)
|
||
|
|
{
|
||
|
|
if (!(m_endpoint_cluster_etc_params[i] == m_endpoint_cluster_etc_params[j]))
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
|
||
|
|
new_endpoint_clusters.push_back(m_endpoint_clusters[i]);
|
||
|
|
new_subblock_etc_params.push_back(m_endpoint_cluster_etc_params[i]);
|
||
|
|
|
||
|
|
for (int k = i + 1; k < j; k++)
|
||
|
|
{
|
||
|
|
append_vector(new_endpoint_clusters.back(), m_endpoint_clusters[k]);
|
||
|
|
}
|
||
|
|
|
||
|
|
i = j;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (m_endpoint_clusters.size() != new_endpoint_clusters.size())
|
||
|
|
{
|
||
|
|
if (m_params.m_debug_stats)
|
||
|
|
debug_printf("Eliminated %u redundant or empty clusters\n", (uint32_t)(m_endpoint_clusters.size() - new_endpoint_clusters.size()));
|
||
|
|
|
||
|
|
m_endpoint_clusters.swap(new_endpoint_clusters);
|
||
|
|
|
||
|
|
m_endpoint_cluster_etc_params.swap(new_subblock_etc_params);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::create_initial_packed_texture()
|
||
|
|
{
|
||
|
|
debug_printf("create_initial_packed_texture\n");
|
||
|
|
|
||
|
|
const uint32_t N = 4096;
|
||
|
|
for (uint32_t block_index_iter = 0; block_index_iter < m_total_blocks; block_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = block_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>(m_total_blocks, first_index + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index] {
|
||
|
|
|
||
|
|
for (uint32_t block_index = first_index; block_index < last_index; block_index++)
|
||
|
|
{
|
||
|
|
uint32_t cluster0 = m_block_endpoint_clusters_indices[block_index][0];
|
||
|
|
uint32_t cluster1 = m_block_endpoint_clusters_indices[block_index][1];
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster0 == cluster1);
|
||
|
|
|
||
|
|
const color_rgba *pSource_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
etc_block &blk = m_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
color_rgba unscaled[2] = { m_endpoint_cluster_etc_params[cluster0].m_color_unscaled[0], m_endpoint_cluster_etc_params[cluster1].m_color_unscaled[0] };
|
||
|
|
uint32_t inten[2] = { m_endpoint_cluster_etc_params[cluster0].m_inten_table[0], m_endpoint_cluster_etc_params[cluster1].m_inten_table[0] };
|
||
|
|
|
||
|
|
blk.set_block_color5(unscaled[0], unscaled[1]);
|
||
|
|
blk.set_flip_bit(true);
|
||
|
|
|
||
|
|
blk.set_inten_table(0, inten[0]);
|
||
|
|
blk.set_inten_table(1, inten[1]);
|
||
|
|
|
||
|
|
blk.determine_selectors(pSource_pixels, m_params.m_perceptual);
|
||
|
|
|
||
|
|
} // block_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // block_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
m_orig_encoded_blocks = m_encoded_blocks;
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::compute_selector_clusters_within_each_parent_cluster()
|
||
|
|
{
|
||
|
|
uint_vec block_selector_cluster_indices(m_total_blocks);
|
||
|
|
|
||
|
|
for (int cluster_index = 0; cluster_index < static_cast<int>(m_selector_cluster_indices.size()); cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_indices = m_selector_cluster_indices[cluster_index];
|
||
|
|
|
||
|
|
for (uint32_t cluster_indices_iter = 0; cluster_indices_iter < cluster_indices.size(); cluster_indices_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_indices[cluster_indices_iter];
|
||
|
|
|
||
|
|
block_selector_cluster_indices[block_index] = cluster_index;
|
||
|
|
|
||
|
|
} // cluster_indices_iter
|
||
|
|
|
||
|
|
} // cluster_index
|
||
|
|
|
||
|
|
m_selector_clusters_within_each_parent_cluster.resize(0);
|
||
|
|
m_selector_clusters_within_each_parent_cluster.resize(m_selector_parent_cluster_indices.size());
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t cluster_index = block_selector_cluster_indices[block_index];
|
||
|
|
const uint32_t parent_cluster_index = m_block_parent_selector_cluster[block_index];
|
||
|
|
|
||
|
|
m_selector_clusters_within_each_parent_cluster[parent_cluster_index].push_back(cluster_index);
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_selector_clusters_within_each_parent_cluster.size(); i++)
|
||
|
|
{
|
||
|
|
uint_vec &cluster_indices = m_selector_clusters_within_each_parent_cluster[i];
|
||
|
|
|
||
|
|
BASISU_FRONTEND_VERIFY(cluster_indices.size());
|
||
|
|
|
||
|
|
vector_sort(cluster_indices);
|
||
|
|
|
||
|
|
auto last = std::unique(cluster_indices.begin(), cluster_indices.end());
|
||
|
|
cluster_indices.erase(last, cluster_indices.end());
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::generate_selector_clusters()
|
||
|
|
{
|
||
|
|
debug_printf("generate_selector_clusters\n");
|
||
|
|
|
||
|
|
typedef vec<16, float> vec16F;
|
||
|
|
typedef tree_vector_quant<vec16F> vec16F_clusterizer;
|
||
|
|
|
||
|
|
vec16F_clusterizer::array_of_weighted_training_vecs training_vecs(m_total_blocks);
|
||
|
|
|
||
|
|
const uint32_t N = 4096;
|
||
|
|
for (uint32_t block_index_iter = 0; block_index_iter < m_total_blocks; block_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = block_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>(m_total_blocks, first_index + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &training_vecs] {
|
||
|
|
|
||
|
|
for (uint32_t block_index = first_index; block_index < last_index; block_index++)
|
||
|
|
{
|
||
|
|
const etc_block &blk = m_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
vec16F v;
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
v[x + y * 4] = static_cast<float>(blk.get_selector(x, y));
|
||
|
|
|
||
|
|
const uint32_t subblock_index = (blk.get_inten_table(0) > blk.get_inten_table(1)) ? 0 : 1;
|
||
|
|
|
||
|
|
color_rgba block_colors[2];
|
||
|
|
blk.get_block_low_high_colors(block_colors, subblock_index);
|
||
|
|
|
||
|
|
const uint32_t dist = color_distance(m_params.m_perceptual, block_colors[0], block_colors[1], false);
|
||
|
|
|
||
|
|
const uint32_t cColorDistToWeight = 300;
|
||
|
|
const uint32_t cMaxWeight = 4096;
|
||
|
|
uint32_t weight = clamp<uint32_t>(dist / cColorDistToWeight, 1, cMaxWeight);
|
||
|
|
|
||
|
|
training_vecs[block_index].first = v;
|
||
|
|
training_vecs[block_index].second = weight;
|
||
|
|
|
||
|
|
} // block_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // block_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
vec16F_clusterizer selector_clusterizer;
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
selector_clusterizer.add_training_vec(training_vecs[i].first, training_vecs[i].second);
|
||
|
|
|
||
|
|
const uint32_t parent_codebook_size = (m_params.m_max_selector_clusters >= 256) ? BASISU_SELECTOR_PARENT_CODEBOOK_SIZE : 0;
|
||
|
|
|
||
|
|
uint32_t max_threads = 0;
|
||
|
|
max_threads = m_params.m_multithreaded ? minimum<int>(std::thread::hardware_concurrency(), cMaxCodebookCreationThreads) : 0;
|
||
|
|
|
||
|
|
bool status = generate_hierarchical_codebook_threaded(selector_clusterizer,
|
||
|
|
m_params.m_max_selector_clusters, m_use_hierarchical_selector_codebooks ? parent_codebook_size : 0,
|
||
|
|
m_selector_cluster_indices,
|
||
|
|
m_selector_parent_cluster_indices,
|
||
|
|
max_threads, m_params.m_pJob_pool);
|
||
|
|
BASISU_FRONTEND_VERIFY(status);
|
||
|
|
|
||
|
|
if (m_use_hierarchical_selector_codebooks)
|
||
|
|
{
|
||
|
|
if (!m_selector_parent_cluster_indices.size())
|
||
|
|
{
|
||
|
|
m_selector_parent_cluster_indices.resize(0);
|
||
|
|
m_selector_parent_cluster_indices.resize(1);
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
m_selector_parent_cluster_indices[0].push_back(i);
|
||
|
|
}
|
||
|
|
|
||
|
|
BASISU_ASSUME(BASISU_SELECTOR_PARENT_CODEBOOK_SIZE <= UINT8_MAX);
|
||
|
|
|
||
|
|
m_block_parent_selector_cluster.resize(0);
|
||
|
|
m_block_parent_selector_cluster.resize(m_total_blocks);
|
||
|
|
vector_set_all(m_block_parent_selector_cluster, 0xFF);
|
||
|
|
|
||
|
|
for (uint32_t parent_cluster_index = 0; parent_cluster_index < m_selector_parent_cluster_indices.size(); parent_cluster_index++)
|
||
|
|
{
|
||
|
|
const uint_vec &cluster = m_selector_parent_cluster_indices[parent_cluster_index];
|
||
|
|
for (uint32_t j = 0; j < cluster.size(); j++)
|
||
|
|
m_block_parent_selector_cluster[cluster[j]] = static_cast<uint8_t>(parent_cluster_index);
|
||
|
|
}
|
||
|
|
for (uint32_t i = 0; i < m_total_blocks; i++)
|
||
|
|
{
|
||
|
|
BASISU_FRONTEND_VERIFY(m_block_parent_selector_cluster[i] != 0xFF);
|
||
|
|
}
|
||
|
|
|
||
|
|
// Ensure that all the blocks within each cluster are all in the same parent cluster, or something is very wrong.
|
||
|
|
for (uint32_t cluster_index = 0; cluster_index < m_selector_cluster_indices.size(); cluster_index++)
|
||
|
|
{
|
||
|
|
const uint_vec &cluster = m_selector_cluster_indices[cluster_index];
|
||
|
|
|
||
|
|
uint32_t parent_cluster_index = 0;
|
||
|
|
for (uint32_t j = 0; j < cluster.size(); j++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster[j];
|
||
|
|
if (!j)
|
||
|
|
{
|
||
|
|
parent_cluster_index = m_block_parent_selector_cluster[block_index];
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
BASISU_FRONTEND_VERIFY(m_block_parent_selector_cluster[block_index] == parent_cluster_index);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("Total selector clusters: %u, total parent selector clusters: %u\n", (uint32_t)m_selector_cluster_indices.size(), (uint32_t)m_selector_parent_cluster_indices.size());
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::create_optimized_selector_codebook(uint32_t iter)
|
||
|
|
{
|
||
|
|
debug_printf("create_optimized_selector_codebook\n");
|
||
|
|
|
||
|
|
const uint32_t total_selector_clusters = (uint32_t)m_selector_cluster_indices.size();
|
||
|
|
|
||
|
|
m_optimized_cluster_selectors.resize(total_selector_clusters);
|
||
|
|
|
||
|
|
if ((m_params.m_pGlobal_sel_codebook) && (!m_params.m_use_hybrid_selector_codebooks))
|
||
|
|
{
|
||
|
|
uint32_t total_clusters_processed = 0;
|
||
|
|
|
||
|
|
m_optimized_cluster_selector_global_cb_ids.resize(total_selector_clusters);
|
||
|
|
|
||
|
|
const uint32_t N = 256;
|
||
|
|
for (uint32_t cluster_index_iter = 0; cluster_index_iter < total_selector_clusters; cluster_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = cluster_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>((uint32_t)total_selector_clusters, cluster_index_iter + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &total_clusters_processed, &total_selector_clusters] {
|
||
|
|
|
||
|
|
for (uint32_t cluster_index = first_index; cluster_index < last_index; cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t> &cluster_block_indices = m_selector_cluster_indices[cluster_index];
|
||
|
|
|
||
|
|
if (!cluster_block_indices.size())
|
||
|
|
continue;
|
||
|
|
|
||
|
|
etc_block_vec etc_blocks;
|
||
|
|
pixel_block_vec pixel_blocks;
|
||
|
|
|
||
|
|
for (uint32_t cluster_block_index = 0; cluster_block_index < cluster_block_indices.size(); cluster_block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_block_indices[cluster_block_index];
|
||
|
|
|
||
|
|
etc_blocks.push_back(m_encoded_blocks[block_index]);
|
||
|
|
|
||
|
|
pixel_blocks.push_back(get_source_pixel_block(block_index));
|
||
|
|
}
|
||
|
|
|
||
|
|
uint32_t palette_index;
|
||
|
|
basist::etc1_global_palette_entry_modifier palette_modifier;
|
||
|
|
|
||
|
|
#if 0
|
||
|
|
m_params.m_pGlobal_sel_codebook->find_best_entry(etc_blocks.size(), pixel_blocks.get_ptr(), etc_blocks.get_ptr(),
|
||
|
|
palette_index, palette_modifier,
|
||
|
|
m_params.m_perceptual, 1 << m_params.m_num_global_sel_codebook_pal_bits, 1 << m_params.m_num_global_sel_codebook_mod_bits);
|
||
|
|
#else
|
||
|
|
etc1_global_selector_codebook_find_best_entry(*m_params.m_pGlobal_sel_codebook,
|
||
|
|
(uint32_t)etc_blocks.size(), &pixel_blocks[0], &etc_blocks[0],
|
||
|
|
palette_index, palette_modifier,
|
||
|
|
m_params.m_perceptual, 1 << m_params.m_num_global_sel_codebook_pal_bits, 1 << m_params.m_num_global_sel_codebook_mod_bits);
|
||
|
|
#endif
|
||
|
|
|
||
|
|
m_optimized_cluster_selector_global_cb_ids[cluster_index].set(palette_index, palette_modifier);
|
||
|
|
|
||
|
|
basist::etc1_selector_palette_entry pal_entry(m_params.m_pGlobal_sel_codebook->get_entry(palette_index, palette_modifier));
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
m_optimized_cluster_selectors[cluster_index].set_selector(x, y, pal_entry(x, y));
|
||
|
|
|
||
|
|
{
|
||
|
|
std::lock_guard<std::mutex> lock(m_lock);
|
||
|
|
|
||
|
|
total_clusters_processed++;
|
||
|
|
if ((total_clusters_processed % 63) == 0)
|
||
|
|
debug_printf("Global selector palette optimization: %3.1f%% complete\n", total_clusters_processed * 100.0f / total_selector_clusters);
|
||
|
|
}
|
||
|
|
|
||
|
|
} // cluster_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // cluster_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
const bool uses_hybrid_sel_codebook = ((m_params.m_pGlobal_sel_codebook) && (m_params.m_use_hybrid_selector_codebooks));
|
||
|
|
if (uses_hybrid_sel_codebook)
|
||
|
|
{
|
||
|
|
m_selector_cluster_uses_global_cb.resize(total_selector_clusters);
|
||
|
|
m_optimized_cluster_selector_global_cb_ids.resize(total_selector_clusters);
|
||
|
|
}
|
||
|
|
|
||
|
|
uint32_t total_clusters_processed = 0;
|
||
|
|
|
||
|
|
// For each selector codebook entry, and for each of the 4x4 selectors, determine which selector minimizes the error across all the blocks that use that quantized selector.
|
||
|
|
|
||
|
|
const uint32_t N = 256;
|
||
|
|
for (uint32_t cluster_index_iter = 0; cluster_index_iter < total_selector_clusters; cluster_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = cluster_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>((uint32_t)total_selector_clusters, cluster_index_iter + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &uses_hybrid_sel_codebook, &total_clusters_processed, &total_selector_clusters] {
|
||
|
|
|
||
|
|
for (uint32_t cluster_index = first_index; cluster_index < last_index; cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t> &cluster_block_indices = m_selector_cluster_indices[cluster_index];
|
||
|
|
|
||
|
|
if (!cluster_block_indices.size())
|
||
|
|
continue;
|
||
|
|
|
||
|
|
uint64_t overall_best_err = 0;
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
{
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
{
|
||
|
|
uint64_t best_err = UINT64_MAX;
|
||
|
|
uint32_t best_s = 0;
|
||
|
|
|
||
|
|
for (uint32_t s = 0; s < 4; s++)
|
||
|
|
{
|
||
|
|
uint32_t total_err = 0;
|
||
|
|
|
||
|
|
for (uint32_t cluster_block_index = 0; cluster_block_index < cluster_block_indices.size(); cluster_block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_block_indices[cluster_block_index];
|
||
|
|
|
||
|
|
const etc_block &blk = m_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
const color_rgba &orig_color = get_source_pixel_block(block_index)(x, y);
|
||
|
|
|
||
|
|
color_rgba block_color;
|
||
|
|
blk.get_block_color(block_color, blk.get_subblock_index(x, y), s);
|
||
|
|
total_err += color_distance(m_params.m_perceptual, block_color, orig_color, false);
|
||
|
|
|
||
|
|
if (total_err > best_err)
|
||
|
|
break;
|
||
|
|
|
||
|
|
} // block_index
|
||
|
|
|
||
|
|
if (total_err < best_err)
|
||
|
|
{
|
||
|
|
best_err = total_err;
|
||
|
|
best_s = s;
|
||
|
|
if (!best_err)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
|
||
|
|
} // s
|
||
|
|
|
||
|
|
m_optimized_cluster_selectors[cluster_index].set_selector(x, y, best_s);
|
||
|
|
|
||
|
|
overall_best_err += best_err;
|
||
|
|
|
||
|
|
} // x
|
||
|
|
} // y
|
||
|
|
|
||
|
|
if (uses_hybrid_sel_codebook)
|
||
|
|
{
|
||
|
|
etc_block_vec etc_blocks;
|
||
|
|
pixel_block_vec pixel_blocks;
|
||
|
|
|
||
|
|
for (uint32_t cluster_block_index = 0; cluster_block_index < cluster_block_indices.size(); cluster_block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_block_indices[cluster_block_index];
|
||
|
|
|
||
|
|
etc_blocks.push_back(m_encoded_blocks[block_index]);
|
||
|
|
|
||
|
|
pixel_blocks.push_back(get_source_pixel_block(block_index));
|
||
|
|
}
|
||
|
|
|
||
|
|
uint32_t palette_index;
|
||
|
|
basist::etc1_global_palette_entry_modifier palette_modifier;
|
||
|
|
|
||
|
|
#if 0
|
||
|
|
uint64_t best_global_cb_err = m_params.m_pGlobal_sel_codebook->find_best_entry(etc_blocks.size(), pixel_blocks.get_ptr(), etc_blocks.get_ptr(),
|
||
|
|
palette_index, palette_modifier,
|
||
|
|
m_params.m_perceptual, 1 << m_params.m_num_global_sel_codebook_pal_bits, 1 << m_params.m_num_global_sel_codebook_mod_bits);
|
||
|
|
#else
|
||
|
|
uint64_t best_global_cb_err = etc1_global_selector_codebook_find_best_entry(*m_params.m_pGlobal_sel_codebook, (uint32_t)etc_blocks.size(), &pixel_blocks[0], &etc_blocks[0],
|
||
|
|
palette_index, palette_modifier,
|
||
|
|
m_params.m_perceptual, 1 << m_params.m_num_global_sel_codebook_pal_bits, 1 << m_params.m_num_global_sel_codebook_mod_bits);
|
||
|
|
#endif
|
||
|
|
|
||
|
|
if (best_global_cb_err <= overall_best_err * m_params.m_hybrid_codebook_quality_thresh)
|
||
|
|
{
|
||
|
|
m_selector_cluster_uses_global_cb[cluster_index] = true;
|
||
|
|
|
||
|
|
m_optimized_cluster_selector_global_cb_ids[cluster_index].set(palette_index, palette_modifier);
|
||
|
|
|
||
|
|
basist::etc1_selector_palette_entry pal_entry(m_params.m_pGlobal_sel_codebook->get_entry(palette_index, palette_modifier));
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
m_optimized_cluster_selectors[cluster_index].set_selector(x, y, pal_entry(x, y));
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
m_optimized_cluster_selector_global_cb_ids[cluster_index].set(0, basist::etc1_global_palette_entry_modifier(0));
|
||
|
|
|
||
|
|
m_selector_cluster_uses_global_cb[cluster_index] = false;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (uses_hybrid_sel_codebook)
|
||
|
|
{
|
||
|
|
std::lock_guard<std::mutex> lock(m_lock);
|
||
|
|
|
||
|
|
total_clusters_processed++;
|
||
|
|
if ((total_clusters_processed % 63) == 0)
|
||
|
|
debug_printf("Global selector palette optimization: %3.1f%% complete\n", total_clusters_processed * 100.0f / total_selector_clusters);
|
||
|
|
}
|
||
|
|
|
||
|
|
} // cluster_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // cluster_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
} // if (m_params.m_pGlobal_sel_codebook)
|
||
|
|
|
||
|
|
if (m_params.m_debug_images)
|
||
|
|
{
|
||
|
|
uint32_t max_selector_cluster_size = 0;
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_selector_cluster_indices.size(); i++)
|
||
|
|
max_selector_cluster_size = maximum<uint32_t>(max_selector_cluster_size, (uint32_t)m_selector_cluster_indices[i].size());
|
||
|
|
|
||
|
|
if ((max_selector_cluster_size * 5) < 32768)
|
||
|
|
{
|
||
|
|
const uint32_t x_spacer_len = 16;
|
||
|
|
image selector_cluster_vis(x_spacer_len + max_selector_cluster_size * 5, (uint32_t)m_selector_cluster_indices.size() * 5);
|
||
|
|
|
||
|
|
for (uint32_t selector_cluster_index = 0; selector_cluster_index < m_selector_cluster_indices.size(); selector_cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t> &cluster_block_indices = m_selector_cluster_indices[selector_cluster_index];
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
selector_cluster_vis.set_clipped(x_spacer_len + x - 12, selector_cluster_index * 5 + y, color_rgba((m_optimized_cluster_selectors[selector_cluster_index].get_selector(x, y) * 255) / 3));
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < cluster_block_indices.size(); i++)
|
||
|
|
{
|
||
|
|
uint32_t block_index = cluster_block_indices[i];
|
||
|
|
|
||
|
|
const etc_block &blk = m_orig_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
selector_cluster_vis.set_clipped(x_spacer_len + x + 5 * i, selector_cluster_index * 5 + y, color_rgba((blk.get_selector(x, y) * 255) / 3));
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
char buf[256];
|
||
|
|
snprintf(buf, sizeof(buf), "selector_cluster_vis_%u.png", iter);
|
||
|
|
save_png(buf, selector_cluster_vis);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::find_optimal_selector_clusters_for_each_block()
|
||
|
|
{
|
||
|
|
debug_printf("find_optimal_selector_clusters_for_each_block\n");
|
||
|
|
|
||
|
|
m_block_selector_cluster_index.resize(m_total_blocks);
|
||
|
|
|
||
|
|
if (m_params.m_compression_level == 0)
|
||
|
|
{
|
||
|
|
// Don't do anything, just leave the blocks in their original selector clusters.
|
||
|
|
for (uint32_t i = 0; i < m_selector_cluster_indices.size(); i++)
|
||
|
|
{
|
||
|
|
for (uint32_t j = 0; j < m_selector_cluster_indices[i].size(); j++)
|
||
|
|
m_block_selector_cluster_index[m_selector_cluster_indices[i][j]] = i;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
std::vector< std::vector<uint32_t> > new_cluster_indices;
|
||
|
|
|
||
|
|
// For each block: Determine which quantized selectors best encode that block, given its quantized endpoints.
|
||
|
|
|
||
|
|
const uint32_t N = 1024;
|
||
|
|
for (uint32_t block_index_iter = 0; block_index_iter < m_total_blocks; block_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = block_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>(m_total_blocks, first_index + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &new_cluster_indices] {
|
||
|
|
|
||
|
|
for (uint32_t block_index = first_index; block_index < last_index; block_index++)
|
||
|
|
{
|
||
|
|
const color_rgba* pBlock_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
etc_block& blk = m_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
color_rgba trial_block_colors[4];
|
||
|
|
blk.get_block_colors(trial_block_colors, 0);
|
||
|
|
|
||
|
|
uint64_t best_cluster_err = UINT64_MAX;
|
||
|
|
uint32_t best_cluster_index = 0;
|
||
|
|
|
||
|
|
const uint32_t parent_selector_cluster = m_block_parent_selector_cluster.size() ? m_block_parent_selector_cluster[block_index] : 0;
|
||
|
|
const uint_vec *pCluster_indices = m_selector_clusters_within_each_parent_cluster.size() ? &m_selector_clusters_within_each_parent_cluster[parent_selector_cluster] : nullptr;
|
||
|
|
|
||
|
|
const uint32_t total_clusters = m_use_hierarchical_selector_codebooks ? (uint32_t)pCluster_indices->size() : (uint32_t)m_selector_cluster_indices.size();
|
||
|
|
|
||
|
|
for (uint32_t cluster_iter = 0; cluster_iter < total_clusters; cluster_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t cluster_index = m_use_hierarchical_selector_codebooks ? (*pCluster_indices)[cluster_iter] : cluster_iter;
|
||
|
|
|
||
|
|
const etc_block& cluster_blk = m_optimized_cluster_selectors[cluster_index];
|
||
|
|
|
||
|
|
uint64_t trial_err = 0;
|
||
|
|
for (int y = 0; y < 4; y++)
|
||
|
|
{
|
||
|
|
for (int x = 0; x < 4; x++)
|
||
|
|
{
|
||
|
|
const uint32_t sel = cluster_blk.get_selector(x, y);
|
||
|
|
|
||
|
|
trial_err += color_distance(m_params.m_perceptual, trial_block_colors[sel], pBlock_pixels[x + y * 4], false);
|
||
|
|
if (trial_err > best_cluster_err)
|
||
|
|
goto early_out;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
if (trial_err < best_cluster_err)
|
||
|
|
{
|
||
|
|
best_cluster_err = trial_err;
|
||
|
|
best_cluster_index = cluster_index;
|
||
|
|
if (!best_cluster_err)
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
|
||
|
|
early_out:
|
||
|
|
;
|
||
|
|
}
|
||
|
|
|
||
|
|
blk.set_raw_selector_bits(m_optimized_cluster_selectors[best_cluster_index].get_raw_selector_bits());
|
||
|
|
|
||
|
|
m_block_selector_cluster_index[block_index] = best_cluster_index;
|
||
|
|
|
||
|
|
{
|
||
|
|
std::lock_guard<std::mutex> lock(m_lock);
|
||
|
|
|
||
|
|
vector_ensure_element_is_valid(new_cluster_indices, best_cluster_index);
|
||
|
|
new_cluster_indices[best_cluster_index].push_back(block_index);
|
||
|
|
}
|
||
|
|
|
||
|
|
} // block_index
|
||
|
|
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // block_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
m_selector_cluster_indices.swap(new_cluster_indices);
|
||
|
|
}
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_selector_cluster_indices.size(); i++)
|
||
|
|
vector_sort(m_selector_cluster_indices[i]);
|
||
|
|
}
|
||
|
|
|
||
|
|
// TODO: Remove old ETC1 specific stuff, and thread this.
|
||
|
|
uint32_t basisu_frontend::refine_block_endpoints_given_selectors()
|
||
|
|
{
|
||
|
|
debug_printf("refine_block_endpoints_given_selectors\n");
|
||
|
|
|
||
|
|
for (int block_index = 0; block_index < static_cast<int>(m_total_blocks); block_index++)
|
||
|
|
{
|
||
|
|
//uint32_t selector_cluster = m_block_selector_cluster_index(block_x, block_y);
|
||
|
|
vec2U &endpoint_clusters = m_block_endpoint_clusters_indices[block_index];
|
||
|
|
|
||
|
|
m_endpoint_cluster_etc_params[endpoint_clusters[0]].m_subblocks.push_back(block_index * 2);
|
||
|
|
|
||
|
|
m_endpoint_cluster_etc_params[endpoint_clusters[1]].m_subblocks.push_back(block_index * 2 + 1);
|
||
|
|
}
|
||
|
|
|
||
|
|
uint32_t total_subblocks_refined = 0;
|
||
|
|
uint32_t total_subblocks_examined = 0;
|
||
|
|
|
||
|
|
for (uint32_t endpoint_cluster_index = 0; endpoint_cluster_index < m_endpoint_cluster_etc_params.size(); endpoint_cluster_index++)
|
||
|
|
{
|
||
|
|
endpoint_cluster_etc_params &subblock_params = m_endpoint_cluster_etc_params[endpoint_cluster_index];
|
||
|
|
|
||
|
|
const uint_vec &subblocks = subblock_params.m_subblocks;
|
||
|
|
//uint32_t total_pixels = subblock.m_subblocks.size() * 8;
|
||
|
|
|
||
|
|
std::vector<color_rgba> subblock_colors[2]; // [use_individual_mode]
|
||
|
|
uint8_vec subblock_selectors[2];
|
||
|
|
|
||
|
|
uint64_t cur_subblock_err[2] = { 0, 0 };
|
||
|
|
|
||
|
|
for (uint32_t subblock_iter = 0; subblock_iter < subblocks.size(); subblock_iter++)
|
||
|
|
{
|
||
|
|
uint32_t training_vector_index = subblocks[subblock_iter];
|
||
|
|
|
||
|
|
uint32_t block_index = training_vector_index >> 1;
|
||
|
|
uint32_t subblock_index = training_vector_index & 1;
|
||
|
|
const bool is_flipped = true;
|
||
|
|
|
||
|
|
const etc_block &blk = m_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
const bool use_individual_mode = !blk.get_diff_bit();
|
||
|
|
|
||
|
|
const color_rgba *pSource_block_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
color_rgba unpacked_block_pixels[16];
|
||
|
|
unpack_etc1(blk, unpacked_block_pixels);
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < 8; i++)
|
||
|
|
{
|
||
|
|
const uint32_t pixel_index = g_etc1_pixel_indices[is_flipped][subblock_index][i];
|
||
|
|
const etc_coord2 &coords = g_etc1_pixel_coords[is_flipped][subblock_index][i];
|
||
|
|
|
||
|
|
subblock_colors[use_individual_mode].push_back(pSource_block_pixels[pixel_index]);
|
||
|
|
|
||
|
|
cur_subblock_err[use_individual_mode] += color_distance(m_params.m_perceptual, pSource_block_pixels[pixel_index], unpacked_block_pixels[pixel_index], false);
|
||
|
|
|
||
|
|
subblock_selectors[use_individual_mode].push_back(static_cast<uint8_t>(blk.get_selector(coords.m_x, coords.m_y)));
|
||
|
|
}
|
||
|
|
} // subblock_iter
|
||
|
|
|
||
|
|
etc1_optimizer::results cluster_optimizer_results[2];
|
||
|
|
bool results_valid[2] = { false, false };
|
||
|
|
|
||
|
|
clear_obj(cluster_optimizer_results);
|
||
|
|
|
||
|
|
std::vector<uint8_t> cluster_selectors[2];
|
||
|
|
|
||
|
|
for (uint32_t use_individual_mode = 0; use_individual_mode < 2; use_individual_mode++)
|
||
|
|
{
|
||
|
|
const uint32_t total_pixels = (uint32_t)subblock_colors[use_individual_mode].size();
|
||
|
|
|
||
|
|
if (!total_pixels)
|
||
|
|
continue;
|
||
|
|
|
||
|
|
total_subblocks_examined += total_pixels / 8;
|
||
|
|
|
||
|
|
etc1_optimizer optimizer;
|
||
|
|
etc1_solution_coordinates solutions[2];
|
||
|
|
|
||
|
|
etc1_optimizer::params cluster_optimizer_params;
|
||
|
|
cluster_optimizer_params.m_num_src_pixels = total_pixels;
|
||
|
|
cluster_optimizer_params.m_pSrc_pixels = &subblock_colors[use_individual_mode][0];
|
||
|
|
|
||
|
|
cluster_optimizer_params.m_use_color4 = use_individual_mode != 0;
|
||
|
|
cluster_optimizer_params.m_perceptual = m_params.m_perceptual;
|
||
|
|
|
||
|
|
cluster_optimizer_params.m_pForce_selectors = &subblock_selectors[use_individual_mode][0];
|
||
|
|
cluster_optimizer_params.m_quality = cETCQualityUber;
|
||
|
|
|
||
|
|
cluster_selectors[use_individual_mode].resize(total_pixels);
|
||
|
|
|
||
|
|
cluster_optimizer_results[use_individual_mode].m_n = total_pixels;
|
||
|
|
cluster_optimizer_results[use_individual_mode].m_pSelectors = &cluster_selectors[use_individual_mode][0];
|
||
|
|
|
||
|
|
optimizer.init(cluster_optimizer_params, cluster_optimizer_results[use_individual_mode]);
|
||
|
|
|
||
|
|
if (!optimizer.compute())
|
||
|
|
continue;
|
||
|
|
|
||
|
|
if (cluster_optimizer_results[use_individual_mode].m_error < cur_subblock_err[use_individual_mode])
|
||
|
|
results_valid[use_individual_mode] = true;
|
||
|
|
|
||
|
|
} // use_individual_mode
|
||
|
|
|
||
|
|
for (uint32_t use_individual_mode = 0; use_individual_mode < 2; use_individual_mode++)
|
||
|
|
{
|
||
|
|
if (!results_valid[use_individual_mode])
|
||
|
|
continue;
|
||
|
|
|
||
|
|
uint32_t num_passes = use_individual_mode ? 1 : 2;
|
||
|
|
|
||
|
|
bool all_passed5 = true;
|
||
|
|
|
||
|
|
for (uint32_t pass = 0; pass < num_passes; pass++)
|
||
|
|
{
|
||
|
|
for (uint32_t subblock_iter = 0; subblock_iter < subblocks.size(); subblock_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t training_vector_index = subblocks[subblock_iter];
|
||
|
|
|
||
|
|
const uint32_t block_index = training_vector_index >> 1;
|
||
|
|
const uint32_t subblock_index = training_vector_index & 1;
|
||
|
|
const bool is_flipped = true;
|
||
|
|
|
||
|
|
etc_block &blk = m_encoded_blocks[block_index];
|
||
|
|
|
||
|
|
if (!blk.get_diff_bit() != static_cast<bool>(use_individual_mode != 0))
|
||
|
|
continue;
|
||
|
|
|
||
|
|
if (use_individual_mode)
|
||
|
|
{
|
||
|
|
blk.set_base4_color(subblock_index, etc_block::pack_color4(cluster_optimizer_results[1].m_block_color_unscaled, false));
|
||
|
|
blk.set_inten_table(subblock_index, cluster_optimizer_results[1].m_block_inten_table);
|
||
|
|
|
||
|
|
subblock_params.m_color_error[1] = cluster_optimizer_results[1].m_error;
|
||
|
|
subblock_params.m_inten_table[1] = cluster_optimizer_results[1].m_block_inten_table;
|
||
|
|
subblock_params.m_color_unscaled[1] = cluster_optimizer_results[1].m_block_color_unscaled;
|
||
|
|
|
||
|
|
total_subblocks_refined++;
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
const uint16_t base_color5 = blk.get_base5_color();
|
||
|
|
const uint16_t delta_color3 = blk.get_delta3_color();
|
||
|
|
|
||
|
|
uint32_t r[2], g[2], b[2];
|
||
|
|
etc_block::unpack_color5(r[0], g[0], b[0], base_color5, false);
|
||
|
|
bool success = etc_block::unpack_color5(r[1], g[1], b[1], base_color5, delta_color3, false);
|
||
|
|
assert(success);
|
||
|
|
BASISU_NOTE_UNUSED(success);
|
||
|
|
|
||
|
|
r[subblock_index] = cluster_optimizer_results[0].m_block_color_unscaled.r;
|
||
|
|
g[subblock_index] = cluster_optimizer_results[0].m_block_color_unscaled.g;
|
||
|
|
b[subblock_index] = cluster_optimizer_results[0].m_block_color_unscaled.b;
|
||
|
|
|
||
|
|
color_rgba colors[2] = { color_rgba(r[0], g[0], b[0], 255), color_rgba(r[1], g[1], b[1], 255) };
|
||
|
|
|
||
|
|
if (!etc_block::try_pack_color5_delta3(colors))
|
||
|
|
{
|
||
|
|
all_passed5 = false;
|
||
|
|
break;
|
||
|
|
}
|
||
|
|
|
||
|
|
if ((pass == 1) && (all_passed5))
|
||
|
|
{
|
||
|
|
blk.set_block_color5(colors[0], colors[1]);
|
||
|
|
blk.set_inten_table(subblock_index, cluster_optimizer_results[0].m_block_inten_table);
|
||
|
|
|
||
|
|
subblock_params.m_color_error[0] = cluster_optimizer_results[0].m_error;
|
||
|
|
subblock_params.m_inten_table[0] = cluster_optimizer_results[0].m_block_inten_table;
|
||
|
|
subblock_params.m_color_unscaled[0] = cluster_optimizer_results[0].m_block_color_unscaled;
|
||
|
|
|
||
|
|
total_subblocks_refined++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
} // subblock_iter
|
||
|
|
|
||
|
|
} // pass
|
||
|
|
|
||
|
|
} // use_individual_mode
|
||
|
|
|
||
|
|
} // endpoint_cluster_index
|
||
|
|
|
||
|
|
if (m_params.m_debug_stats)
|
||
|
|
debug_printf("Total subblock endpoints refined: %u (%3.1f%%)\n", total_subblocks_refined, total_subblocks_refined * 100.0f / total_subblocks_examined);
|
||
|
|
|
||
|
|
return total_subblocks_refined;
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::dump_endpoint_clusterization_visualization(const char *pFilename, bool vis_endpoint_colors)
|
||
|
|
{
|
||
|
|
debug_printf("dump_endpoint_clusterization_visualization\n");
|
||
|
|
|
||
|
|
uint32_t max_endpoint_cluster_size = 0;
|
||
|
|
|
||
|
|
std::vector<uint32_t> cluster_sizes(m_endpoint_clusters.size());
|
||
|
|
std::vector<uint32_t> sorted_cluster_indices(m_endpoint_clusters.size());
|
||
|
|
for (uint32_t i = 0; i < m_endpoint_clusters.size(); i++)
|
||
|
|
{
|
||
|
|
max_endpoint_cluster_size = maximum<uint32_t>(max_endpoint_cluster_size, (uint32_t)m_endpoint_clusters[i].size());
|
||
|
|
cluster_sizes[i] = (uint32_t)m_endpoint_clusters[i].size();
|
||
|
|
}
|
||
|
|
|
||
|
|
if (!max_endpoint_cluster_size)
|
||
|
|
return;
|
||
|
|
|
||
|
|
for (uint32_t i = 0; i < m_endpoint_clusters.size(); i++)
|
||
|
|
sorted_cluster_indices[i] = i;
|
||
|
|
|
||
|
|
//indexed_heap_sort(endpoint_clusters.size(), cluster_sizes.get_ptr(), sorted_cluster_indices.get_ptr());
|
||
|
|
|
||
|
|
image endpoint_cluster_vis(12 + minimum<uint32_t>(max_endpoint_cluster_size, 2048) * 5, (uint32_t)m_endpoint_clusters.size() * 3);
|
||
|
|
|
||
|
|
for (uint32_t unsorted_cluster_iter = 0; unsorted_cluster_iter < m_endpoint_clusters.size(); unsorted_cluster_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t cluster_iter = sorted_cluster_indices[unsorted_cluster_iter];
|
||
|
|
|
||
|
|
etc_block blk;
|
||
|
|
blk.clear();
|
||
|
|
blk.set_flip_bit(false);
|
||
|
|
blk.set_diff_bit(true);
|
||
|
|
blk.set_inten_tables_etc1s(m_endpoint_cluster_etc_params[cluster_iter].m_inten_table[0]);
|
||
|
|
blk.set_base5_color(etc_block::pack_color5(m_endpoint_cluster_etc_params[cluster_iter].m_color_unscaled[0], false));
|
||
|
|
|
||
|
|
color_rgba blk_colors[4];
|
||
|
|
blk.get_block_colors(blk_colors, 0);
|
||
|
|
for (uint32_t i = 0; i < 4; i++)
|
||
|
|
endpoint_cluster_vis.fill_box(i * 2, 3 * unsorted_cluster_iter, 2, 2, blk_colors[i]);
|
||
|
|
|
||
|
|
for (uint32_t subblock_iter = 0; subblock_iter < m_endpoint_clusters[cluster_iter].size(); subblock_iter++)
|
||
|
|
{
|
||
|
|
uint32_t training_vector_index = m_endpoint_clusters[cluster_iter][subblock_iter];
|
||
|
|
|
||
|
|
const uint32_t block_index = training_vector_index >> 1;
|
||
|
|
const uint32_t subblock_index = training_vector_index & 1;
|
||
|
|
|
||
|
|
const etc_block& blk2 = m_etc1_blocks_etc1s[block_index];
|
||
|
|
|
||
|
|
const color_rgba *pBlock_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
color_rgba subblock_pixels[8];
|
||
|
|
|
||
|
|
if (vis_endpoint_colors)
|
||
|
|
{
|
||
|
|
color_rgba colors[2];
|
||
|
|
blk2.get_block_low_high_colors(colors, subblock_index);
|
||
|
|
for (uint32_t i = 0; i < 8; i++)
|
||
|
|
subblock_pixels[i] = colors[subblock_index];
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
for (uint32_t i = 0; i < 8; i++)
|
||
|
|
subblock_pixels[i] = pBlock_pixels[g_etc1_pixel_indices[blk2.get_flip_bit()][subblock_index][i]];
|
||
|
|
}
|
||
|
|
|
||
|
|
endpoint_cluster_vis.set_block_clipped(subblock_pixels, 12 + 5 * subblock_iter, 3 * unsorted_cluster_iter, 4, 2);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
save_png(pFilename, endpoint_cluster_vis);
|
||
|
|
debug_printf("Wrote debug visualization file %s\n", pFilename);
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::finalize()
|
||
|
|
{
|
||
|
|
for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
|
||
|
|
{
|
||
|
|
for (uint32_t subblock_index = 0; subblock_index < 2; subblock_index++)
|
||
|
|
{
|
||
|
|
const uint32_t endpoint_cluster_index = get_subblock_endpoint_cluster_index(block_index, subblock_index);
|
||
|
|
|
||
|
|
m_endpoint_cluster_etc_params[endpoint_cluster_index].m_color_used[0] = true;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// The backend has remapped the block endpoints while optimizing the output symbols for better rate distortion performance, so let's go and reoptimize the endpoint codebook.
|
||
|
|
// This is currently the only place where the backend actually goes and changes the quantization and calls the frontend to fix things up.
|
||
|
|
// This is basically a bottom up clusterization stage, where some leaves can be combined.
|
||
|
|
void basisu_frontend::reoptimize_remapped_endpoints(const uint_vec &new_block_endpoints, int_vec &old_to_new_endpoint_cluster_indices, bool optimize_final_codebook, uint_vec *pBlock_selector_indices)
|
||
|
|
{
|
||
|
|
debug_printf("reoptimize_remapped_endpoints\n");
|
||
|
|
|
||
|
|
std::vector<uint_vec> new_endpoint_cluster_block_indices(m_endpoint_clusters.size());
|
||
|
|
for (uint32_t i = 0; i < new_block_endpoints.size(); i++)
|
||
|
|
new_endpoint_cluster_block_indices[new_block_endpoints[i]].push_back(i);
|
||
|
|
|
||
|
|
std::vector<uint8_t> cluster_valid(new_endpoint_cluster_block_indices.size());
|
||
|
|
std::vector<uint8_t> cluster_improved(new_endpoint_cluster_block_indices.size());
|
||
|
|
|
||
|
|
const uint32_t N = 256;
|
||
|
|
for (uint32_t cluster_index_iter = 0; cluster_index_iter < new_endpoint_cluster_block_indices.size(); cluster_index_iter += N)
|
||
|
|
{
|
||
|
|
const uint32_t first_index = cluster_index_iter;
|
||
|
|
const uint32_t last_index = minimum<uint32_t>((uint32_t)new_endpoint_cluster_block_indices.size(), cluster_index_iter + N);
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->add_job( [this, first_index, last_index, &cluster_improved, &cluster_valid, &new_endpoint_cluster_block_indices, &pBlock_selector_indices ] {
|
||
|
|
for (uint32_t cluster_index = first_index; cluster_index < last_index; cluster_index++)
|
||
|
|
{
|
||
|
|
const std::vector<uint32_t>& cluster_block_indices = new_endpoint_cluster_block_indices[cluster_index];
|
||
|
|
|
||
|
|
if (!cluster_block_indices.size())
|
||
|
|
continue;
|
||
|
|
|
||
|
|
const uint32_t total_pixels = (uint32_t)cluster_block_indices.size() * 16;
|
||
|
|
|
||
|
|
std::vector<color_rgba> cluster_pixels(total_pixels);
|
||
|
|
uint8_vec force_selectors(total_pixels);
|
||
|
|
|
||
|
|
etc_block blk;
|
||
|
|
blk.set_block_color5_etc1s(get_endpoint_cluster_unscaled_color(cluster_index, false));
|
||
|
|
blk.set_inten_tables_etc1s(get_endpoint_cluster_inten_table(cluster_index, false));
|
||
|
|
blk.set_flip_bit(true);
|
||
|
|
|
||
|
|
uint64_t cur_err = 0;
|
||
|
|
|
||
|
|
for (uint32_t cluster_block_indices_iter = 0; cluster_block_indices_iter < cluster_block_indices.size(); cluster_block_indices_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = cluster_block_indices[cluster_block_indices_iter];
|
||
|
|
|
||
|
|
const color_rgba *pBlock_pixels = get_source_pixel_block(block_index).get_ptr();
|
||
|
|
|
||
|
|
memcpy(&cluster_pixels[cluster_block_indices_iter * 16], pBlock_pixels, 16 * sizeof(color_rgba));
|
||
|
|
|
||
|
|
const uint32_t selector_cluster_index = pBlock_selector_indices ? (*pBlock_selector_indices)[block_index] : get_block_selector_cluster_index(block_index);
|
||
|
|
|
||
|
|
const etc_block &blk_selectors = get_selector_cluster_selector_bits(selector_cluster_index);
|
||
|
|
|
||
|
|
blk.set_raw_selector_bits(blk_selectors.get_raw_selector_bits());
|
||
|
|
|
||
|
|
cur_err += blk.evaluate_etc1_error(pBlock_pixels, m_params.m_perceptual);
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
force_selectors[cluster_block_indices_iter * 16 + x + y * 4] = static_cast<uint8_t>(blk_selectors.get_selector(x, y));
|
||
|
|
}
|
||
|
|
|
||
|
|
endpoint_cluster_etc_params new_endpoint_cluster_etc_params;
|
||
|
|
|
||
|
|
{
|
||
|
|
etc1_optimizer optimizer;
|
||
|
|
etc1_solution_coordinates solutions[2];
|
||
|
|
|
||
|
|
etc1_optimizer::params cluster_optimizer_params;
|
||
|
|
cluster_optimizer_params.m_num_src_pixels = total_pixels;
|
||
|
|
cluster_optimizer_params.m_pSrc_pixels = &cluster_pixels[0];
|
||
|
|
|
||
|
|
cluster_optimizer_params.m_use_color4 = false;
|
||
|
|
cluster_optimizer_params.m_perceptual = m_params.m_perceptual;
|
||
|
|
cluster_optimizer_params.m_pForce_selectors = &force_selectors[0];
|
||
|
|
|
||
|
|
if (m_params.m_compression_level == BASISU_MAX_COMPRESSION_LEVEL)
|
||
|
|
cluster_optimizer_params.m_quality = cETCQualityUber;
|
||
|
|
|
||
|
|
etc1_optimizer::results cluster_optimizer_results;
|
||
|
|
|
||
|
|
std::vector<uint8_t> cluster_selectors(total_pixels);
|
||
|
|
cluster_optimizer_results.m_n = total_pixels;
|
||
|
|
cluster_optimizer_results.m_pSelectors = &cluster_selectors[0];
|
||
|
|
|
||
|
|
optimizer.init(cluster_optimizer_params, cluster_optimizer_results);
|
||
|
|
|
||
|
|
optimizer.compute();
|
||
|
|
|
||
|
|
new_endpoint_cluster_etc_params.m_color_unscaled[0] = cluster_optimizer_results.m_block_color_unscaled;
|
||
|
|
new_endpoint_cluster_etc_params.m_inten_table[0] = cluster_optimizer_results.m_block_inten_table;
|
||
|
|
new_endpoint_cluster_etc_params.m_color_error[0] = cluster_optimizer_results.m_error;
|
||
|
|
new_endpoint_cluster_etc_params.m_color_used[0] = true;
|
||
|
|
new_endpoint_cluster_etc_params.m_valid = true;
|
||
|
|
}
|
||
|
|
|
||
|
|
if (new_endpoint_cluster_etc_params.m_color_error[0] < cur_err)
|
||
|
|
{
|
||
|
|
m_endpoint_cluster_etc_params[cluster_index] = new_endpoint_cluster_etc_params;
|
||
|
|
|
||
|
|
cluster_improved[cluster_index] = true;
|
||
|
|
}
|
||
|
|
|
||
|
|
cluster_valid[cluster_index] = true;
|
||
|
|
|
||
|
|
} // cluster_index
|
||
|
|
} );
|
||
|
|
|
||
|
|
} // cluster_index_iter
|
||
|
|
|
||
|
|
m_params.m_pJob_pool->wait_for_all();
|
||
|
|
|
||
|
|
uint32_t total_unused_clusters = 0;
|
||
|
|
uint32_t total_improved_clusters = 0;
|
||
|
|
|
||
|
|
old_to_new_endpoint_cluster_indices.resize(m_endpoint_clusters.size());
|
||
|
|
vector_set_all(old_to_new_endpoint_cluster_indices, -1);
|
||
|
|
|
||
|
|
int total_new_endpoint_clusters = 0;
|
||
|
|
|
||
|
|
for (uint32_t old_cluster_index = 0; old_cluster_index < m_endpoint_clusters.size(); old_cluster_index++)
|
||
|
|
{
|
||
|
|
if (!cluster_valid[old_cluster_index])
|
||
|
|
total_unused_clusters++;
|
||
|
|
else
|
||
|
|
old_to_new_endpoint_cluster_indices[old_cluster_index] = total_new_endpoint_clusters++;
|
||
|
|
|
||
|
|
if (cluster_improved[old_cluster_index])
|
||
|
|
total_improved_clusters++;
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("Total unused clusters: %u\n", total_unused_clusters);
|
||
|
|
debug_printf("Total improved_clusters: %u\n", total_improved_clusters);
|
||
|
|
debug_printf("Total endpoint clusters: %u\n", total_new_endpoint_clusters);
|
||
|
|
|
||
|
|
if (optimize_final_codebook)
|
||
|
|
{
|
||
|
|
cluster_subblock_etc_params_vec new_endpoint_cluster_etc_params(total_new_endpoint_clusters);
|
||
|
|
|
||
|
|
for (uint32_t old_cluster_index = 0; old_cluster_index < m_endpoint_clusters.size(); old_cluster_index++)
|
||
|
|
{
|
||
|
|
if (old_to_new_endpoint_cluster_indices[old_cluster_index] >= 0)
|
||
|
|
new_endpoint_cluster_etc_params[old_to_new_endpoint_cluster_indices[old_cluster_index]] = m_endpoint_cluster_etc_params[old_cluster_index];
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("basisu_frontend::reoptimize_remapped_endpoints: stage 1\n");
|
||
|
|
|
||
|
|
std::vector<uint_vec> new_endpoint_clusters(total_new_endpoint_clusters);
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < new_block_endpoints.size(); block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t old_endpoint_cluster_index = new_block_endpoints[block_index];
|
||
|
|
|
||
|
|
const int new_endpoint_cluster_index = old_to_new_endpoint_cluster_indices[old_endpoint_cluster_index];
|
||
|
|
BASISU_FRONTEND_VERIFY(new_endpoint_cluster_index >= 0);
|
||
|
|
|
||
|
|
BASISU_FRONTEND_VERIFY(new_endpoint_cluster_index < (int)new_endpoint_clusters.size());
|
||
|
|
|
||
|
|
new_endpoint_clusters[new_endpoint_cluster_index].push_back(block_index * 2 + 0);
|
||
|
|
new_endpoint_clusters[new_endpoint_cluster_index].push_back(block_index * 2 + 1);
|
||
|
|
|
||
|
|
BASISU_FRONTEND_VERIFY(new_endpoint_cluster_index < (int)new_endpoint_cluster_etc_params.size());
|
||
|
|
|
||
|
|
new_endpoint_cluster_etc_params[new_endpoint_cluster_index].m_subblocks.push_back(block_index * 2 + 0);
|
||
|
|
new_endpoint_cluster_etc_params[new_endpoint_cluster_index].m_subblocks.push_back(block_index * 2 + 1);
|
||
|
|
|
||
|
|
m_block_endpoint_clusters_indices[block_index][0] = new_endpoint_cluster_index;
|
||
|
|
m_block_endpoint_clusters_indices[block_index][1] = new_endpoint_cluster_index;
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("basisu_frontend::reoptimize_remapped_endpoints: stage 2\n");
|
||
|
|
|
||
|
|
m_endpoint_clusters = new_endpoint_clusters;
|
||
|
|
m_endpoint_cluster_etc_params = new_endpoint_cluster_etc_params;
|
||
|
|
|
||
|
|
eliminate_redundant_or_empty_endpoint_clusters();
|
||
|
|
|
||
|
|
debug_printf("basisu_frontend::reoptimize_remapped_endpoints: stage 3\n");
|
||
|
|
|
||
|
|
for (uint32_t new_cluster_index = 0; new_cluster_index < m_endpoint_clusters.size(); new_cluster_index++)
|
||
|
|
{
|
||
|
|
for (uint32_t cluster_block_iter = 0; cluster_block_iter < m_endpoint_clusters[new_cluster_index].size(); cluster_block_iter++)
|
||
|
|
{
|
||
|
|
const uint32_t subblock_index = m_endpoint_clusters[new_cluster_index][cluster_block_iter];
|
||
|
|
const uint32_t block_index = subblock_index >> 1;
|
||
|
|
|
||
|
|
m_block_endpoint_clusters_indices[block_index][0] = new_cluster_index;
|
||
|
|
m_block_endpoint_clusters_indices[block_index][1] = new_cluster_index;
|
||
|
|
|
||
|
|
const uint32_t old_cluster_index = new_block_endpoints[block_index];
|
||
|
|
|
||
|
|
old_to_new_endpoint_cluster_indices[old_cluster_index] = new_cluster_index;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("basisu_frontend::reoptimize_remapped_endpoints: stage 4\n");
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < m_encoded_blocks.size(); block_index++)
|
||
|
|
{
|
||
|
|
const uint32_t endpoint_cluster_index = get_subblock_endpoint_cluster_index(block_index, 0);
|
||
|
|
|
||
|
|
m_encoded_blocks[block_index].set_block_color5_etc1s(get_endpoint_cluster_unscaled_color(endpoint_cluster_index, false));
|
||
|
|
m_encoded_blocks[block_index].set_inten_tables_etc1s(get_endpoint_cluster_inten_table(endpoint_cluster_index, false));
|
||
|
|
}
|
||
|
|
|
||
|
|
debug_printf("Final (post-RDO) endpoint clusters: %u\n", m_endpoint_clusters.size());
|
||
|
|
}
|
||
|
|
|
||
|
|
//debug_printf("validate_output: %u\n", validate_output());
|
||
|
|
}
|
||
|
|
|
||
|
|
bool basisu_frontend::validate_output() const
|
||
|
|
{
|
||
|
|
debug_printf("validate_output\n");
|
||
|
|
|
||
|
|
if (!check_etc1s_constraints())
|
||
|
|
return false;
|
||
|
|
|
||
|
|
for (uint32_t block_index = 0; block_index < m_total_blocks; block_index++)
|
||
|
|
{
|
||
|
|
//#define CHECK(x) do { if (!(x)) { DebugBreak(); return false; } } while(0)
|
||
|
|
#define CHECK(x) BASISU_FRONTEND_VERIFY(x);
|
||
|
|
|
||
|
|
CHECK(get_output_block(block_index).get_flip_bit() == true);
|
||
|
|
|
||
|
|
const bool diff_flag = get_diff_flag(block_index);
|
||
|
|
CHECK(diff_flag == true);
|
||
|
|
|
||
|
|
etc_block blk;
|
||
|
|
memset(&blk, 0, sizeof(blk));
|
||
|
|
blk.set_flip_bit(true);
|
||
|
|
blk.set_diff_bit(true);
|
||
|
|
|
||
|
|
const uint32_t endpoint_cluster0_index = get_subblock_endpoint_cluster_index(block_index, 0);
|
||
|
|
const uint32_t endpoint_cluster1_index = get_subblock_endpoint_cluster_index(block_index, 1);
|
||
|
|
|
||
|
|
// basisu only supports ETC1S, so these must be equal.
|
||
|
|
CHECK(endpoint_cluster0_index == endpoint_cluster1_index);
|
||
|
|
|
||
|
|
CHECK(blk.set_block_color5_check(get_endpoint_cluster_unscaled_color(endpoint_cluster0_index, false), get_endpoint_cluster_unscaled_color(endpoint_cluster1_index, false)));
|
||
|
|
|
||
|
|
CHECK(get_endpoint_cluster_color_is_used(endpoint_cluster0_index, false));
|
||
|
|
|
||
|
|
blk.set_inten_table(0, get_endpoint_cluster_inten_table(endpoint_cluster0_index, false));
|
||
|
|
blk.set_inten_table(1, get_endpoint_cluster_inten_table(endpoint_cluster1_index, false));
|
||
|
|
|
||
|
|
const uint32_t selector_cluster_index = get_block_selector_cluster_index(block_index);
|
||
|
|
CHECK(selector_cluster_index < get_total_selector_clusters());
|
||
|
|
|
||
|
|
CHECK(vector_find(get_selector_cluster_block_indices(selector_cluster_index), block_index) != -1);
|
||
|
|
|
||
|
|
blk.set_raw_selector_bits(get_selector_cluster_selector_bits(selector_cluster_index).get_raw_selector_bits());
|
||
|
|
|
||
|
|
const etc_block &rdo_output_block = get_output_block(block_index);
|
||
|
|
|
||
|
|
CHECK(rdo_output_block.get_flip_bit() == blk.get_flip_bit());
|
||
|
|
CHECK(rdo_output_block.get_diff_bit() == blk.get_diff_bit());
|
||
|
|
CHECK(rdo_output_block.get_inten_table(0) == blk.get_inten_table(0));
|
||
|
|
CHECK(rdo_output_block.get_inten_table(1) == blk.get_inten_table(1));
|
||
|
|
CHECK(rdo_output_block.get_base5_color() == blk.get_base5_color());
|
||
|
|
CHECK(rdo_output_block.get_delta3_color() == blk.get_delta3_color());
|
||
|
|
CHECK(rdo_output_block.get_raw_selector_bits() == blk.get_raw_selector_bits());
|
||
|
|
|
||
|
|
if (m_params.m_pGlobal_sel_codebook)
|
||
|
|
{
|
||
|
|
bool used_global_cb = true;
|
||
|
|
if (m_params.m_use_hybrid_selector_codebooks)
|
||
|
|
used_global_cb = m_selector_cluster_uses_global_cb[selector_cluster_index];
|
||
|
|
|
||
|
|
if (used_global_cb)
|
||
|
|
{
|
||
|
|
basist::etc1_global_selector_codebook_entry_id pal_id(get_selector_cluster_global_selector_entry_ids()[selector_cluster_index]);
|
||
|
|
|
||
|
|
basist::etc1_selector_palette_entry pal_entry(m_params.m_pGlobal_sel_codebook->get_entry(pal_id));
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < 4; y++)
|
||
|
|
{
|
||
|
|
for (uint32_t x = 0; x < 4; x++)
|
||
|
|
{
|
||
|
|
CHECK(pal_entry(x, y) == blk.get_selector(x, y));
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
#undef CHECK
|
||
|
|
}
|
||
|
|
|
||
|
|
return true;
|
||
|
|
}
|
||
|
|
|
||
|
|
void basisu_frontend::dump_debug_image(const char *pFilename, uint32_t first_block, uint32_t num_blocks_x, uint32_t num_blocks_y, bool output_blocks)
|
||
|
|
{
|
||
|
|
gpu_image g;
|
||
|
|
g.init(cETC1, num_blocks_x * 4, num_blocks_y * 4);
|
||
|
|
|
||
|
|
for (uint32_t y = 0; y < num_blocks_y; y++)
|
||
|
|
{
|
||
|
|
for (uint32_t x = 0; x < num_blocks_x; x++)
|
||
|
|
{
|
||
|
|
const uint32_t block_index = first_block + x + y * num_blocks_x;
|
||
|
|
|
||
|
|
etc_block &blk = *(etc_block *)g.get_block_ptr(x, y);
|
||
|
|
|
||
|
|
if (output_blocks)
|
||
|
|
blk = get_output_block(block_index);
|
||
|
|
else
|
||
|
|
{
|
||
|
|
const bool diff_flag = get_diff_flag(block_index);
|
||
|
|
|
||
|
|
blk.set_diff_bit(diff_flag);
|
||
|
|
blk.set_flip_bit(true);
|
||
|
|
|
||
|
|
const uint32_t endpoint_cluster0_index = get_subblock_endpoint_cluster_index(block_index, 0);
|
||
|
|
const uint32_t endpoint_cluster1_index = get_subblock_endpoint_cluster_index(block_index, 1);
|
||
|
|
|
||
|
|
if (diff_flag)
|
||
|
|
blk.set_block_color5(get_endpoint_cluster_unscaled_color(endpoint_cluster0_index, false), get_endpoint_cluster_unscaled_color(endpoint_cluster1_index, false));
|
||
|
|
else
|
||
|
|
blk.set_block_color4(get_endpoint_cluster_unscaled_color(endpoint_cluster0_index, true), get_endpoint_cluster_unscaled_color(endpoint_cluster1_index, true));
|
||
|
|
|
||
|
|
blk.set_inten_table(0, get_endpoint_cluster_inten_table(endpoint_cluster0_index, !diff_flag));
|
||
|
|
blk.set_inten_table(1, get_endpoint_cluster_inten_table(endpoint_cluster1_index, !diff_flag));
|
||
|
|
|
||
|
|
const uint32_t selector_cluster_index = get_block_selector_cluster_index(block_index);
|
||
|
|
blk.set_raw_selector_bits(get_selector_cluster_selector_bits(selector_cluster_index).get_raw_selector_bits());
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
image img;
|
||
|
|
g.unpack(img);
|
||
|
|
|
||
|
|
save_png(pFilename, img);
|
||
|
|
}
|
||
|
|
|
||
|
|
} // namespace basisu
|
||
|
|
|