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basisu_frontend.cpp
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basisu_frontend.cpp
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// basisu_frontend.cpp
// Copyright (C) 2017-2019 Binomial LLC. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// TODO:
// This code originally supported full ETC1 and ETC1S, so there's some legacy stuff to be cleaned up in here.
// 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.
//
#include "transcoder/basisu.h"
#include "basisu_frontend.h"
#include <unordered_set>
#define BASISU_FRONTEND_VERIFY(c) verify(c, __LINE__);
namespace basisu
{
const uint32_t BASISU_MAX_ENDPOINT_REFINEMENT_STEPS = 3;
const uint32_t BASISU_MAX_SELECTOR_REFINEMENT_STEPS = 3;
// TODO - How to handle internal verifies in the basisu lib
static inline void verify(bool condition, int line)
{
if (!condition)
{
fprintf(stderr, "basisu_frontend: verify check failed at line %i!\n", line);
abort();
}
}
bool basisu_frontend::init(const params &p)
{
if (p.m_use_hybrid_selector_codebooks)
{
if (!p.m_pGlobal_sel_codebook)
{
assert(0);
return false;
}
}
debug_printf("basisu_frontend::init: NumEndpointClusters: %u, NumSelectorClusters: %u, EndpointRefinement: %u, Perceptual: %u, Faster: %u\n",
p.m_max_endpoint_clusters, p.m_max_selector_clusters, p.m_endpoint_refinement, p.m_perceptual, p.m_faster);
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",
p.m_num_global_sel_codebook_pal_bits,
p.m_num_global_sel_codebook_mod_bits,
p.m_use_hybrid_selector_codebooks,
p.m_hybrid_codebook_quality_thresh);
if ((p.m_max_endpoint_clusters < 1) || (p.m_max_endpoint_clusters > cMaxEndpointClusters))
return false;
if ((p.m_max_selector_clusters < 1) || (p.m_max_selector_clusters > cMaxSelectorClusters))
return false;
m_source_blocks.resize(0);
append_vector(m_source_blocks, p.m_pSource_blocks, p.m_num_source_blocks);
m_params = p;
m_encoded_blocks.resize(m_params.m_num_source_blocks);
memset(&m_encoded_blocks[0], 0, m_encoded_blocks.size() * sizeof(m_encoded_blocks[0]));
return true;
}
bool basisu_frontend::compress()
{
debug_printf("basisu_frontend::compress\n");
m_total_blocks = m_params.m_num_source_blocks;
m_total_pixels = m_total_blocks * cPixelBlockTotalPixels;
init_etc1_images();
init_endpoint_training_vectors();
generate_endpoint_clusters();
const uint32_t num_refine_endpoint_steps = m_params.m_endpoint_refinement ? (m_params.m_faster ? 1 : BASISU_MAX_ENDPOINT_REFINEMENT_STEPS) : 1;
for (uint32_t refine_endpoint_step = 0; refine_endpoint_step < num_refine_endpoint_steps; refine_endpoint_step++)
{
BASISU_FRONTEND_VERIFY(check_etc1s_constraints());
if (refine_endpoint_step)
{
introduce_new_endpoint_clusters();
}
generate_endpoint_codebook(refine_endpoint_step);
if ((m_params.m_debug_images) && (m_params.m_dump_endpoint_clusterization))
{
char buf[256];
#ifdef _WIN32
sprintf_s(buf, sizeof(buf), "endpoint_cluster_vis_pre_%u.png", refine_endpoint_step);
#else
snprintf(buf, sizeof(buf), "endpoint_cluster_vis_pre_%u.png", refine_endpoint_step);
#endif
dump_endpoint_clusterization_visualization(buf);
}
bool early_out = false;
if (m_params.m_endpoint_refinement)
{
//dump_endpoint_clusterization_visualization("endpoint_clusters_before_refinement.png");
if (!refine_endpoint_clusterization())
early_out = true;
if ((m_params.m_debug_images) && (m_params.m_dump_endpoint_clusterization))
{
char buf[256];
#ifdef _WIN32
sprintf_s(buf, sizeof(buf), "endpoint_cluster_vis_post_%u.png", refine_endpoint_step);
#else
snprintf(buf, sizeof(buf), "endpoint_cluster_vis_post_%u.png", refine_endpoint_step);
#endif
dump_endpoint_clusterization_visualization(buf);
}
}
eliminate_redundant_or_empty_endpoint_clusters();
if (m_params.m_debug_stats)
debug_printf("Total endpoint clusters: %u\n", (uint32_t)m_endpoint_clusters.size());
if (early_out)
break;
}
BASISU_FRONTEND_VERIFY(check_etc1s_constraints());
generate_block_endpoint_clusters();
create_initial_packed_texture();
create_selector_clusters();
const uint32_t num_refine_selector_steps = m_params.m_pGlobal_sel_codebook ? 1 : (m_params.m_faster ? 1 : BASISU_MAX_SELECTOR_REFINEMENT_STEPS);
for (uint32_t refine_selector_steps = 0; refine_selector_steps < num_refine_selector_steps; refine_selector_steps++)
{
create_optimized_selector_codebook(refine_selector_steps);
find_optimal_selector_clusters_for_each_block();
if (!m_params.m_faster)
{
if (!refine_block_endpoints_given_selectors())
break;
}
}
optimize_selector_codebook();
if (m_params.m_debug_stats)
debug_printf("Total selector clusters: %u\n", (uint32_t)m_selector_cluster_indices.size());
finalize();
if (m_params.m_validate)
{
if (!validate_output())
return false;
}
debug_printf("basisu_frontend::compress: Done\n");
return true;
}
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;
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;
}
int j;
for (j = 0; j < i; j++)
{
if (m_optimized_cluster_selectors[i].get_raw_selector_bits() == m_optimized_cluster_selectors[j].get_raw_selector_bits())
break;
}
if (j < i)
{
old_to_new[i] = old_to_new[j];
continue;
}
old_to_new[i] = total_new_entries++;
new_to_old.push_back(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);
for (uint32_t i = 0; i < m_block_selector_cluster_index.size(); i++)
m_block_selector_cluster_index[i] = old_to_new[m_block_selector_cluster_index[i]];
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);
m_etc1_blocks_etc1s_unpacked.resize(m_total_blocks);
#pragma omp parallel for
for (int block_index = 0; block_index < static_cast<int>(m_total_blocks); block_index++)
{
const pixel_block &source_blk = get_source_pixel_block(block_index);
pack_etc1_block_context pack_context;
basis_etc1_pack_params etc1_pack_params;
etc1_pack_params.m_perceptual = m_params.m_perceptual;
etc1_pack_params.m_force_etc1s = true;
etc1_pack_params.m_flip_bias = 0.0f;
pack_etc1_block(m_etc1_blocks_etc1s[block_index], source_blk.get_ptr(), etc1_pack_params, pack_context, NULL);
assert(m_etc1_blocks_etc1s[block_index].get_flip_bit());
unpack_etc1(m_etc1_blocks_etc1s[block_index], m_etc1_blocks_etc1s_unpacked[block_index].get_ptr());
}
}
void basisu_frontend::init_endpoint_training_vectors()
{
debug_printf("init_endpoint_training_vectors\n");
std::vector<vec6F> training_vecs(m_total_blocks);
#pragma omp parallel for
for (int block_index = 0; block_index < (int)m_total_blocks; block_index++)
{
const color_rgba *pSource_pixels = get_source_pixel_block(block_index).get_ptr();
etc1_optimizer optimizer;
etc1_optimizer::params optimizer_params;
etc1_optimizer::results optimizer_results;
optimizer_params.m_num_src_pixels = 16;
optimizer_params.m_pSrc_pixels = pSource_pixels;
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();
color_rgba block_colors[4];
etc_block::get_block_colors5(block_colors, optimizer_results.m_block_color_unscaled, optimizer_results.m_block_inten_table, false);
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[3].r * (1.0f / 255.0f);
v[4] = block_colors[3].g * (1.0f / 255.0f);
v[5] = block_colors[3].b * (1.0f / 255.0f);
training_vecs[block_index] = v;
} // block_index
for (int block_index = 0; block_index < (int)m_total_blocks; block_index++)
{
const vec6F &v = training_vecs[block_index];
m_endpoint_clusterizer.add_training_vec(v, 1);
m_endpoint_clusterizer.add_training_vec(v, 1);
}
}
void basisu_frontend::generate_endpoint_clusters()
{
debug_printf("Begin endpoint quantization\n");
m_endpoint_clusterizer.generate(m_params.m_max_endpoint_clusters);
m_endpoint_clusterizer.retrieve(m_endpoint_clusters);
if (m_params.m_debug_stats)
debug_printf("Total endpoint clusters: %u\n", (uint32_t)m_endpoint_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_subblock_error_vec()
{
m_subblock_endpoint_quant_err_vec.resize(0);
#pragma omp parallel for
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];
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;
#pragma omp critical
{
m_subblock_endpoint_quant_err_vec.push_back(quant_err);
}
}
}
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());
const bool is_etc1s_block = true;
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 (is_etc1s_block)
{
if (cluster_sizes[subblock_to_move.m_cluster_index] <= 2)
continue;
}
else
{
if (cluster_sizes[subblock_to_move.m_cluster_index] <= 1)
continue;
}
if (unordered_set_contains(training_vector_was_relocated, training_vector_index))
continue;
if (is_etc1s_block)
{
if (unordered_set_contains(training_vector_was_relocated, training_vector_index ^ 1))
continue;
}
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);
if (is_etc1s_block)
{
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;
}
else
{
BASISU_FRONTEND_VERIFY(cluster_sizes[subblock_to_move.m_cluster_index] >= 1);
cluster_sizes[subblock_to_move.m_cluster_index]--;
}
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();
}
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());
#pragma omp parallel for
for (int cluster_index = 0; cluster_index < static_cast<int>(m_endpoint_clusters.size()); cluster_index++)
{
//debug_printf("%u of %u\n", cluster_index, clusters.size());
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++)
{
cluster_pixels[cluster_indices_iter * 8 + pixel_index] = pBlock_pixels[g_etc1_pixel_indices[flipped][subblock_index][pixel_index]];
}
}
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;
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] + new_subblock_params.m_color_error[1]))
{
use_new_subblock_params = true;
}
}
if (use_new_subblock_params)
{
new_subblock_params.m_valid = true;
prev_etc_params = new_subblock_params;
}
} // cluster_index
}
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");
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);
#pragma omp parallel for
for (int block_index = 0; block_index < (int)m_total_blocks; 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;
for (uint32_t cluster_iter = 0; cluster_iter < m_endpoint_clusters.size(); cluster_iter++)
{
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
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");
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);
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");
#pragma omp parallel for
for (int block_index = 0; block_index < static_cast<int>(m_total_blocks); 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
m_orig_encoded_blocks = m_encoded_blocks;
}
void basisu_frontend::create_selector_clusters()
{
debug_printf("create_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);
#pragma omp parallel for
for (int block_index = 0; block_index < static_cast<int>(m_total_blocks); 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[4];
blk.get_block_colors(block_colors, subblock_index);
const uint32_t dist = color_distance(m_params.m_perceptual, block_colors[0], block_colors[3], 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;
}
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);
selector_clusterizer.generate(m_params.m_max_selector_clusters);
selector_clusterizer.retrieve(m_selector_cluster_indices);
}
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);
#pragma omp parallel for
for (int cluster_index = 0; cluster_index < static_cast<int>(total_selector_clusters); 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++)